Stocks & Commodities - March 2015.pdf

THE TRADERS’ MAGAZINE SINCE 1982

Fundamental Analysis And forex trading

Moving Averages Some finer properties

10 16

Trading System Design A statistical approach for better predictability

News Sentiment Data for retail traders

28 32

INTERVIEW

Les Masonson of Cash Management Resources

REVIEW

36

n OptionStrategist.com (part 2)

MARCH 2015

www.traders.com

MARCH 2015

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FIND MORE ideas that fit your strategy.

FILTERS Markets Uptrend Stocks

Technicals

Options

3% on 15% Higher Vol

DESCRIPTIONS

Symbol

Last

Chg

% Chg

Bid

Ask

Volume

DEC

5.22

1.232

30.89

5.20

5.23

9,148,849

RTF

56.70

5.04

9.76

55.90

57.95

354,664

1.05

0.10

10.53

1.04

1.05

20,110,933

LDPE RMA

10.78

0.85

8.56

10.70

10.72

81,673,172

BTS

1.22

0.08

7.02

1.21

1.22

1,475,961

NABP

5.30

0.22

4.33

4.64

5.39

4,299,779

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CONTENTS 10 Trading Forex: Fundamental Analysis

by Imran Mukati Forex traders need to keep an eye on fundamental data such as interest rates, central bank policies, and economic data. Here in part 5 of this six-part series, we’ll take an in-depth look at these fundamental variables.

15 Q&A

by Don Bright This professional trader answers a few of your questions.

FEATURE ARTICLE

16 Moving Averages: Some Finer Properties

by Giorgos E. Siligardos, PhD Find the answers here to common questions about different types of moving averages.

23 Futures For You

by Carley Garner Here’s how the futures market really works.

24 MACD-Suitable Stocks

by Kevin Luo Trading signals generated by the crossover of Gerald Appel’s moving average convergence/ divergence and signal lines are popular and simple to use. Do they work for all stocks in all market conditions? Find out here.

MARCH 2015, Volume 33 Number 3

28 Trading System Design: A Statistical Approach

TIPS

by John F. Ehlers and Ric Way Here’s how to start with the basics and determine if an identifiable event has a statistical edge in predicting future prices—before you even start to build a trading system.

32 News Sentiment

by Stephen Massel News data, which has long been the province of institutional traders, is now making its way into the hands of retail traders. Here’s a look at how you can incorporate this data into your trading strategies.

INTERVIEW

36 Using ETF Momentum Strategies With Les Masonson

by Jayanthi Gopalakrishnan Leslie Masonson is president of Cash Management Resources, a financial consulting firm that he founded in 1987. Masonson’s 44-year career has spanned trading, investing, financial advisory services, bank operations management, teaching, and corporate cash/ treasury management consulting. We spoke with him about trading and investing in ETFs using momentum strategies.

REVIEW 44 • OptionStrategist.com (Part 2) Product review: The Option Strategist newsletter and its related services

DEPARTMENTS

6 Opening Position 8 Letters To S&C 22 †Traders’ Glossary 47 Traders’ Tips 55 Trade News & Products 56 Futures Liquidity 57 Advertisers’ Index 57 Editorial Resource Index 58 Books For Traders 59 Classified Advertising 59 Traders’ Resource

42 Explore Your Options

by Tom Gentile Got a question about options?

AT THE CLOSE

62 Play The Markets And Keep Your Day Job

by Azeez Mustapha Not ready to be a full-time trader? Here’s a high-probability, part-time trading strategy that will help you master the markets before you commit to it full time.

TIPS

This article is the basis for Traders’ Tips this month.

n Cover: Wlliam L. Brown n Cover concept: Christine Morrison

Copyright © 2015 Technical Analysis, Inc. All rights reserved. Information in this publication must not be stored or reproduced in any form without written permission from the publisher. Technical Analysis of Stocks & Commodities™ (ISSN 0738-3355) is published monthly with a Bonus Issue in March for $89.99 per year by Technical Analysis, Inc., 4757 California Ave. S.W., Seattle, WA 98116-4499. Periodicals postage paid at Seattle, WA and at additional mailing offices. Postmaster: Send address changes to Technical Analysis of Stocks & Commodities™ 4757 California Ave. S.W., Seattle, WA 98116-4499 U.S.A.

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4 • March 2015 • Technical Analysis of Stocks & Commodities

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March 2006 • Volume 24, Number 3 March 2015 • Volume 33, Number 3

Opening PENING P Position OSITION O

The Traders’ Magazine TM The Traders’ MagazineTM EDITORIAL

[email protected]

EDITORIAL

Editor in Chief Jack K. Hutson [email protected] Editor Jayanthi Gopalakrishnan Editor in Chief JackElizabeth K. HutsonM.S. Flynn Managing Editor

Editor Jayanthi Gopalakrishnan Production Manager Karen E. Wasserman Production Manager Karen E. Wasserman Art Director Christine Morrison Graphic Designer Yamanaka Art Director ChristineSharon Morrison Editorial Intern Emilie Graphic Designer WayneRommel Shaw

Technical Penn Staff Writer Writer Dennis David D. Peterson Staff Writers Dennis D. Peterson, Bruce Faber Webmaster Han J. Kim Webmaster Han J. Kim Contributing Editors John Ehlers, Contributing Editors Anthony W. Warren, Ph.D.John Ehlers, Kevin Lund, Anthony W. Warren, Ph.D. Contributing Writers Don Bright, Thomas Bulkowski, Contributing Writers Don Bright, Thomas Bulkowski, Martin Pring, Barbara Star, Markos Katsanos Martin Pring, Adrienne Toghraie

OFFICE OFFICEOF OFTHE THEPublisher PUBLISHER

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O T

nce again we got a reminder of just hishow calendar yearthe so far has been filled sensitive financial markets withsaw surprising have had a are. We a major events selloff that in the Japanese significant impact— onas people’s trading accounts.a markets, which expected — triggered First, there’s the price of crude throughout oil, which condomino effect on markets the tinues to slide We’ve had some surprising world. Add lower. disappointing earnings numbers announcements by various banks—the from US corporations andcentral you have a situaSwiss National with tion that just gotBank worse. Sotheir whatshocking started offanas nouncement to ended abandon currencyand cap on the a strong year upthe correcting, rather Swiss franc, and the Reserve of India and rapidly. I must admit that Bank although correcthe Bank Canada in you inter-have a 2% drop, it gets you thinking. tions areof healthy forannouncing any market,cuts when est rates. next? Anything, by theI usually time you read this, at many more Prior What’s to the Federal Reserve’s really, FOMC and meeting, take a look the yield significant taken place that would thegeneral financial markets. curve. At events present,may it’s have looking a little flat, and givenaffect that the consensus Such events clearly pointtototighten something we January have always butI am failconcerned to come to is that the Fed is going at their 31st known meeting, grips with: Anything can happen in the markets. that the yield curve may be heading in the direction of being inverted. And if that were Yet we think of the as something money for us. I’m We rush to happen, thatmarkets would not be a goodthat signwill formake the US economy. not into stocks after aboutto them from someone else, whether financial suggesting that hearing we are going go through a recessionary period.it’s Butthe given that media oranything someone’s Twitter feed. As muchhurt as Itoam a fan of information almost can happen, it doesn’t expect thetechnology, worst. If nothing else, overload makes it easy forcapital. us to focus on unnecessary information, which clouds it helps to preserve your our judgment. The result is we end up losing money. And that defeats the purpose of our being in the markets.

So

M

with that in mind, you can see why it’s important to design a trading system that gets you out of the market at the right time. When access to the markets number of increases. Thisofmakes aybe is weeasy, need the to approach theoptions marketsavailable a different way. Instead think-it important thorough withofthe different types of orders, front-end software, and ingtoofbethem in terms profits, think of them in terms of losses. Thinking systems that that are out Leibfarth, hishelp article “The Automated oftrading them as something willthere. makeLee us lose money in may us create defensive Daytrader” pagefirst 22, step addresses the various options are available and strategies forstarting trading.onThe in creating a strategy is that to understand your how you can takeare advantage of them. personality. There a multitude of ways that you can approach the markets, but before getting to the that stagematch of placing that trade, you to understand the youBut need to apply strategies your personality. It’s need tempting to be driven you are trading. You should be able If toyou do so after reading Paolo hasty Pezzutti’s tomarket buy something that someone else bought. find yourself making de“Understanding Market The hit markets follow different behavior patcisions without doing yourStructure.” due diligence, the brakes before you press that buy and youGo need to determine if it is volatile, in aone, trading range, moving orterns, sell button. back to your plan—and if youtrending, don’t have now’s the time to strongly direction, orto moving not with much momentum. go back tointheone drawing board create but one—and make your trading decisions only when you know what the structure of the market is if will able to apply afterOnly going through all your checkpoints. Place a trade only allyou yourberequirements themet. correct trading technique. that’s doing just the firstdue step. You still to have are Making hasty decisionsBut without your diligence is have a recipe for discipline, you will afind out after reading this month’s Analysis of disaster, as isasfollowing trading strategy that doesn’t matchTechnical your personality. & COMMODITIES interview with Ken Only then youit be able to STOCKS Your success as a trader lies in the quality of Tower. your trading plan.will Make a defenknow exit. sive onewhen that to approaches the markets as a battlefield where you are likely to lose money. Think of the risks you will encounter, and create steps that will lessen your to smart trading! chances of encounteringHere’s those risks. Take it one step at a time. It’s the small steps that will lead to success in the long run.

8 • March 2006 • Technical Analysis of STOCKS & COMMODITIES 6 • March 2015 • Technical Analysis of Stocks & Commodities

Jayanthi Gopalakrishnan, Editor Jayanthi Gopalakrishnan, Editor

NOTICE OF CLASS ACTION SETTLEMENT If you purchased, sold or held NYMEX Light Sweet Crude Oil, NYMEX New York Harbor Heating Oil or NYMEX New York Harbor Gasoline futures contracts at any time from March 2, 2007 through March 26, 2007, inclusive, then your rights will be affected and you may be entitled to a benefit. A Settlement has been proposed in a class action lawsuit concerning the allegedly improper trading of three futures contracts on the New York Mercantile Exchange (“NYMEX”) from March 2, 2007 through March 26, 2007, inclusive. The Settlement will provide $16.75 million to pay claims from Persons who bought, sold, or held the referenced futures contracts at any time from March 2-26, 2007. If you qualify, you may send in a Proof of Claim form to potentially get benefits, or you can exclude yourself from the Settlement, or object to it. The United States District Court for the Southern District of New York (500 Pearl St., New York, NY 10007-1312) authorized this notice. Before any money is paid, the Court will hold a Fairness Hearing to decide whether to approve the Settlement. Who’s Included? You are a “Settlement Class Member” if you purchased, sold or held NYMEX Light Sweet Crude Oil futures contracts, NYMEX New York Harbor Heating Oil futures contracts or NYMEX New York Harbor Gasoline futures contracts at any time from March 2, 2007 through March 26, 2007, inclusive. Excluded from the Settlement Class are (i) members of the judiciary assigned to this case, including their immediate family members; (ii) Class Counsel and their employees; (iii) Defendants and any parent, subsidiary, affiliate, employee or agent of any Defendant, including Defendants’ counsel; and (iv) Opt Outs. Contact your futures broker or futures commission merchant to see if you purchased, sold or held the referenced contracts. If you’re not sure you are included, you can get more information, including the Settlement Agreement, Mailed Notice, Plan of Allocation, Proof of Claim and other important documents, at www.nymextassettlement.com (“Settlement Website”) or by calling toll free 1-866-778-9470. What’s This About? The lawsuit claims that Defendants Optiver US LLC, Optiver Holding B.V., Optiver VOF, Christopher Dowson, Bastiaan van Kempen, and Randal Meijer (“Defendants”) caused and aided and abetted the causation of artificial prices of certain futures contracts on the New York Mercantile Exchange from March 2-26, 2007, inclusive, by amassing dominant NYMEX trading at settlement (“TAS”) contract positions and offsetting such positions through NYMEX futures contracts transactions in the opposite direction of the TAS positions during the closing period for the futures contracts at the end of the day. Defendants deny any wrongdoing that Plaintiffs allege in the lawsuit and maintain that they have complied with their legal obligations. The Court did not decide which side is right. But both sides agreed to the Settlement to resolve the case and get benefits to potentially affected market participants. The two sides disagree on how much money could have been won if the Plaintiffs had prevailed at trial. What Does the Settlement Provide? Under the Settlement, Defendant Optiver US agreed to pay $16.75 million into a Settlement Fund. If the Court approves the Settlement, potential Settlement Class Members who qualify and send in valid Proof of Claim forms will receive a share of the Settlement Fund, after it is reduced by the payment of certain expenses. The Settlement Agreement, available at the Settlement Website, describes all of the details about the proposed Settlement. The exact amount each qualifying Settlement Class Member will receive from the Settlement Fund cannot be calculated until (1) the Court approves the Settlement; (2) certain amounts identified in the full Settlement Agreement are deducted from the Settlement Fund; and (3) the number of participating Class Members and the amount of their Allowed Claims are determined. In addition, each Settlement Class Member’s share of the Settlement Fund will vary depending on the information the Settlement Class Member provides on their Proof of Claim form. Generally, however, if you bought, sold or held more contracts, you will get more money. And if you bought, sold or held fewer contracts, you will get less money. The number of claimants who send in claims varies widely from case to case. If less than 100% of the Settlement Class sends in a Proof of Claim form, you could get more money. How Do You Ask For a Payment? If you are a Settlement Class Member, you may seek to participate in the Settlement by submitting a Proof of Claim to the Settlement Administrator at the address below postmarked no later than August 3, 2015. You may obtain a Proof of Claim on the Settlement Website or by calling the toll free number referenced above. If you are a Settlement Class Member but do not file a Proof of Claim, you will still be bound by the releases set forth in the Settlement Agreement if the Court enters an order approving the Settlement Agreement. What Are Your Other Options? If you don’t want to be legally bound by the Settlement, you must exclude yourself by April 14, 2015, or you won’t be able to sue, or continue to sue, Defendants about the legal claims in this case. If you exclude yourself, you can’t get money from this Settlement. If you stay in the Settlement, you may object to it by April 27, 2015. All objections to or requests to be excluded from the Settlement must be made in accordance with the instructions set forth in the formal Mailed Notice. The Mailed Notice available at www.nymextassettlement.com explains how to exclude yourself or object. The Court will hold a Fairness Hearing in this case (In re: Optiver Commodities Litigation, Case No. 1:08-cv-06842-LAP) on May 19, 2015, at 1:00 p.m. in Courtroom 12A, United States Courthouse, 500 Pearl Street, New York, NY 10007, to consider whether to approve the Settlement and a request by the lawyers representing all Settlement Class Members (Lovell Stewart Halebian Jacobson LLP, Lowey Dannenberg Cohen & Hart, P.C., and Robins Kaplan Miller & Ciresi L.L.P.) for an award of attorneys’ fees of no more than one-third (i.e., 33 1/3%) of the Settlement Fund for investigating the facts, litigating the case, and negotiating the Settlement, and for reimbursement of their costs and expenses in the amount of no more than approximately $275,000. The lawyers for the Settlement Class may also seek additional reimbursement of fees, costs and expenses in connection with services provided after the Fairness Hearing. These payments will also be deducted from the Settlement Fund before any distributions are made to the Settlement Class. You may ask to appear at the Fairness Hearing, but you don’t have to. For more information, call toll free 1-866-778-9470, visit the Website www.nymextassettlement.com, or write to IN RE OPTIVER COMMODITIES LITIGATION SETTLEMENT, c/o A.B. DATA, LTD., PO BOX 170500, MILWAUKEE, WI 53217-8091.

The editors of S&C invite readers to submit their opinions and information on subjects relating to technical analysis and this magazine. This column is our means of communication with our readers. Is there something you would like to know more (or less) about? Tell us about it. Without a source of new ideas and subjects coming from our readers, this magazine would not exist. Email your correspondence to [email protected] or address your correspondence to: Editor, Stocks & Commodities, 4757 California Ave. SW, Seattle, WA 98116-4499. All letters become the property of Technical Analysis, Inc. Letter-writers must include their full name and address for verification. Letters may be edited for length or clarity. The opinions expressed in this column do not necessarily represent those of the magazine.—Editor

SUPERSMOOTHER OSCILLATOR AND EXCEL SPREADSHEET Editor, I really enjoyed John Ehlers’ article “Whiter Is Brighter” in your January 2015 issue. He has a way of translating unfamiliar concepts into something useful to us. And the results and final equation prove that out. The article’s pseudocode of b1 in the calculation for the SuperSmoother uses

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angles for the cosine. To code it using radians, for example, in Excel, the cell pseudocode for the tunable constant b1 would look like this: b1 = 2*a1*COS(RADIANS (1.414*3.14159/BandEdge)) Also, Ron McAllister’s spreadsheet that he presented in the Traders’ Tips section of that same issue contains a small error in it: In cell A21, where he computes the tunable constant a1, he gives: =EXP(-1.414*3/A19), where the 3 should instead be pi (3.14159). I noticed this when my tunable constants for BandEdge=20 did not exactly agree with his. For those readers wanting to know the exact values of the SuperSmoother tunable constants when BandEdge=20, so that they can check out their own formulations, they are: a1=0.8008, c2=b1=1.5623, c3=-0.6413 and c1=0.0790. Note that c1+c2+c3 = 1.0000. Don Kraska Author John Ehlers replies: I am glad you enjoyed my article “Whiter Is Brighter” in the January 2015 issue and that you appreciate my efforts to bring a little science to this art of trading. It is my custom to write an exponential moving average (EMA) in the form: Output = a*Input + (1-a)*Output[1];

Written this way, you can check by inspection that the two coefficients of the equation sum to unity. This means the EMA is guaranteed to have unity gain at

8 • March 2015 • Technical Analysis of Stocks & Commodities

zero frequency. However, if I additionally multiply the input by K, then I simply give the EMA a gain of K at zero frequency. In a nutshell, that is what I did in the article. I just changed the terminology to make the philosophical point, and the scale factor is irrelevant. My shift in terminology produced a one-bar difference as the expression for the white spectrum. But a one-bar difference produces a 6 dB increase in the high-pass filter gain at the Nyquist frequency. I then added a zero of transmission to the one-bar difference filter at the Nyquist frequency to mitigate the filter gain (in effect, noise gain) at that spectral point. I think the really important part of my article is that the “pink noise” shape of the market data spectrum must be leveled if analysts are to make reasonable filters and indicators. Editor: Ron McAllister’s revised spreadsheet that adds the pi function is available at our website, www.traders.com, in the Traders’Tips area for our January 2015 issue. To reach the Traders’ Tips area at our website, choose the Traders’ Tips menu item from the Home–S&C button on our homepage at www.traders.com. SUGGESTIONS Editor, Please try to publish one or two recommendations on stocks, commodities, forex, and indexes in every issue, if possible. The best way to do so would be to ask the author of an article to recommend a security or two at the end of his or her article using the same method or trading setup he or she is writing about. This would quickly filter out real traders with life experience versus writers with no practical “war-zone” experiences, per se.

LETTERS Please ask the articles’ authors to provide some backtesting and verifiable results on their recommended trade setup as well. This would cement the deal for the writers’ own reputations and personas. A few but solid actionable recommendations each month from your contributing writers would make your magazine much more appealing to the financial junta than the typical financial magazine that offers only repetitive, boring articles on topics like MACD, SMA, EMA and any other trading setups. This would also help writers to work hard and write something compelling that back their observations, theories, and data, not just plain old dry articles without much meat. Thank you. Jack Mirza Thank you for your feedback and your suggestions. Since we are an educational, how-to magazine on technical analysis, our objective is to help people to learn to trade using technical trading tools or systems. That has been our focus in Technical Analysis of Stocks & Commodities magazine since its inception. We try to present trading systems or ideas for trading setups with backtesting results when possible. We try to ensure the reader will be able to see the logic in an idea presented, and be able to replicate the strategy for implementation or for further testing. But our mission is also to provide a variety of material in every issue, for all different levels of traders. Not every article can present a tradable system with backtesting results. Some articles are designed to help introduce basic concepts to new or next-generation traders. As an aside, we’d remind readers that regardless of whether or not an author can provide backtest results on his method, system, or idea, we encourage readers to perform their own backtests to their own satisfaction. That is the only way to become comfortable with a system or strategy, and that is what we preach. We try to provide the tools to do this, including the ready-to-use code provided by software developers in our Traders’ Tips section each month to implement a selected strategy discussed in that issue. While it’s important for a reader to

be able to glance at an article to see if he feels it’s worth pursuing for himself, it’s also important to understand that most approaches will only work in some markets some of the time. It’s imperative that the trader change his approach when something stops working. Our online publication, Traders.com Advantage, contains some content that may be more in line with what you are suggesting, since Traders.com Advantage articles often discuss a specific stock, index, ETF, or forex pair. Brief analyses are often provided based mainly on technical analysis, and the authors sometimes suggest securities to trade. We publish articles on a daily or weekly basis in Traders.com Advantage, which makes them timelier than in a print publication. Thank you again for taking the time to write; we value feedback from our readers.—Editor

March 2015

RETHINKING DIVERSIFICATION Editor, I really enjoyed Dirk Vandycke’s article in the January 2015 issue, “Rethinking Diversification.” Well written, clear, and to the point. Thanks to him for sharing his thoughts in this article. Looking forward to reading part 2. MC Readers will find part 2 of Dirk Vandycke’s two-part series on risk in our February 2015 issue. The article is titled “Fine-Tuning Your Risks.”—Editor Errata: NINJATRADER FILE In the January 2015 Traders’ Tips section, NinjaTrader’s Traders’ Tip refers to an incorrect filename. The download for the universal oscillator technique can be found at www.ninjatrader.com/ SC/January2015SC.zip, not www.ninjatrader.com/SC/January2014SC.zip.

• Technical Analysis of Stocks & Commodities • 9

J

ust as in equity trading, there are two basic approaches to formulating forex trading strategies. In my previous articles in this series, I already introduced you to technical analysis. Its counterpart is fundamental analysis, which looks at issues like interest rates, central bank policies, and economics to make trading decisions. In this way, it is similar to dissecting the financial statements of a company when deciding whether to buy its stock.

Necessary & Useful

Trading Forex: Fundamental Analysis Part 5

their place Because of the nature of the underlying mechanics, fundamental analysis is geared more for longerterm trading. Technical analysis tends to be more appropriate for short-term trading. However, it is possible to combine aspects of both. For example, fundamentals might indicate the future course a currency is likely to take; the only question would be the exact timing of the move. Technical indicators can provide the signals to show when that movement is beginning. In some cases, collective trader psychology might mean following the technical indicators even when the underlying fundamentals don’t justify the price movement. As an example, billionaire hedge fund mogul George Soros—who is famous for, among other things, making fantastically profitable trades on the Thai baht and the British pound, earning a $1 billion profit on a $10 billion trade on the latter currency—bet billions on gold in 2010. Even though he knew that the fundamentals pointed to a bubble in gold prices, the technical indicators showed that traders were nevertheless flocking to buy, and he made money buying the upward trend.

Forex traders need to keep an eye on fundamental data such as interest rates, central bank policies, and economic data. In part 5 of this six-part series, we’ll take an in-depth Central banks look at these fundamental variables. and interest rates One important factor that distinby Imran Mukati guishes forex from equities is the 10 • March 2015 • Technical Analysis of Stocks & Commodities

MAGHEN BROWN

Fundamentals have

FOREX FOCUS

existence of central banks. While companies Interest Rate Demand (Borrowers) Supply (Lenders) (Shortfall)/Surplus 1% $1,000 $50 ($950) take actions intended to affect the price of their 2% $600 $100 ($500) stock, in most cases they have little power to 3% $500 $200 ($300) affect it substantially; the market makes those 4% $400 $400 $0 5% $200 $500 $300 decisions. A currency, however, is not just 6% $100 $600 $500 something to be traded in the marketplace; it Figure 1: different levels of demand for borrowing at different interest rates. is the economic lifeblood of a country. ValuHere you see hypothetical numbers to show you how much borrowers are willing to borrow and how much ations that are too strong or weak have real commercial banks have available to lend at different interest rate levels. and important impacts on the economy, so each central bank is charged with governing its currency. (if they can get one at all) since they are a higher risk. First, I’ll talk about who the players are. Just about every There are varying levels of demand for money (loans) at country has a central bank, but you won’t be trading every different interest rates. If you want to borrow money to buy currency. The central banks that govern the majors are: a boat, remodel your house, or expand your business, and the bank tells you the interest rate will be 18%, you will probably n US Federal Reserve decide that borrowing simply isn’t worth the cost. Instead, n European Central Bank you’ll save up the money (and savings rates, by the way, will probably be quite generous) or just forgo whatever it is you n Bank of Japan were going to purchase with the loan. n Bank of England But what if the bank is lending at 0.5%? If you can get a loan at that rate, you’ll probably sign up right away. After all, that’s n Reserve Bank of Australia nearly free money! So what we find is that there are different n Swiss National Bank. levels of demand for borrowing at different interest rates. Look at the table in Figure 1 for some hypothetical numDon’t assume that central banks are focused solely on currency bers. Here you see how much borrowers are willing to borrow values—their responsibilities are much more complex than (demand) and how much commercial banks have available to that. The US Federal Reserve (the “Fed”) has by law a dual lend (supply) at each interest rate level. Remember that banks mandate: to maximize employment while controlling infla- are taking deposits from savers and using that money to make tion. (The Fed’s standard for controlled inflation, by the way, loans. However, a bank can’t loan out everything it has. Cenis 2% to 3%.) At the end of the day, any central bank wants its tral banks establish reserve requirements, which dictate what nation’s economy to grow as fast as possible while minimizing proportion of its deposits a commercial bank has to have on negative economic effects like bubbles (consider the effects hand as cash or other liquid assets, like securities. of the popping of the US housing bubble in 2008); recessions If a bank has $1 billion in deposits and the reserve reor depressions; and inflation or deflation. Basically, they are quirement is 10%, the bank can’t loan out more than $900 looking for the Goldilocks standard in their economy—not million; it must keep at least $100 million. This, by the way, too hot, not too cold, but just right. is another tool in the central banker’s toolbox. Adjusting reThere is one major tool that central banks use to pursue serve requirements up or down can free up more money for these goals, which is normally labeled monetary policy. loans or reduce what’s available, causing money to flow into Informally you may hear it called setting interest rates, but or out of the economy. It’s also part of what caused the 2008 this is misleading in that the central bank doesn’t simply say, financial crisis. Some of the liquid assets commercial banks “This is the new rate,” despite the impression you might get were holding as part of their reserves were mortgage-backed from the news media in the wake of, for example, a meeting securities (MBSs). When it became clear that no one really of the Federal Reserve Open Market Committee (FOMC). knew how many bad mortgages were rolled into those MBSs The reality is more complex. and therefore what they were worth, the banks no longer knew Understand that an interest rate is basically the price of what they had in reserves. Their response was to hold onto money—specifically, the price to borrow it. In simple terms, their cash by basically stopping all lending. if you are a saver, you give your money to a bank. The bank, Going back to the table, 4% is the hypothetical equilibrium which will be using your funds to make loans, pays you a cer- rate—the rate at which commercial banks have as much money tain interest rate. If you are a borrower, the bank will charge to lend as people and companies want to borrow. While banks you a certain interest rate as well. That rate is, needless to might love to make even more loans at 1%, 2%, or 3%, since say, quite a bit higher than what the saver is receiving. Part their profit margins are basically the same at each rate, they of the difference is what the bank uses to cover its expenses don’t have the reserves to do so. and make a profit; another part is a risk premium—an amount Enter the central bank, which, among other things, acts as a paid to cover the risk that some borrowers will fail to repay bank for banks. Central banks charge interest to commercial their loans by making up those losses. That’s why a person or banks for loans as well. If they are loaning at 1%, commercial a company that is a poor credit risk will pay more for a loan banks might need to charge 3% or 4% to be profitable. But March 2015

• Technical Analysis of Stocks & Commodities • 11

Fundamentals in the news

You should make it a habit to know the central bank targets for GDP growth and inflation in each country whose currency you plan to trade.

if the central bank cuts the rate it charges banks to 0.5% or 0.25%, suddenly the commercial banks can loan money at 1% or 2% and still be profitable. In essence, the central bank makes up the shortfall in the available lending pool, which pumps money into the system and drives rates down. Increasing rates works in just the opposite manner. Why don’t central banks just leave rates low all the time, encouraging borrowing and therefore causing the economy to expand constantly? Well, there’s a little matter of inflation. When more money enters the system, it means people and companies can make more purchases, which means there are more dollars competing for basically the same amount of goods. It also means expanding companies need to hire more workers, and with more competition for basically the same number of workers, wages start rising. This drives inflation, which, if it gets out of control, is very hard to rein in and can destroy an economy. However, a certain amount of inflation is a necessary evil, because it comes along with a growing economy. You might have wondered earlier why the Fed has an inflation target of 2% to 3%. Wouldn’t zero inflation be better? It might seem like a great thing, but it would mean a stagnant economy. Inflation tends to be low or nonexistent—or even turns negative into deflation—during recessions. That leads us to the concept of real and nominal interest rates. The nominal rate is the official or declared rate. Let’s say that it’s 5%. However, if you are lucky enough to earn 5% on your money, that won’t be your actual growth in terms of purchasing power. That’s because inflation eats away at the value of your dollar (or your euro, or your pound, or your franc) each year, reducing how much it can buy. So if the inflation rate is 3% while the interest rate is 5%, the real interest rate or the actual increase in purchasing power is only 2%. Clearly, what matters in trading is the real rate. A currency with a nominal rate of 6% might look great until you find out that the inflation rate is 5%, at which point the one with a 4% nominal rate but only 1.5% inflation looks a lot better. Because interest rate and inflation conditions are likely to differ from country to country, there is trading value in the differences. If the real rate on the yen is 1% while the Swiss franc has a real rate of 2%, holding the franc will be more profitable thanks to the 1% differential. In other words, it becomes practical to borrow yen to buy the franc. Since the franc is more attractive, traders will tend to flock to it over the yen, which means the price will rise. 12 • March 2015 • Technical Analysis of Stocks & Commodities

Fundamental analysis relies heavily on the news. Governments, central banks, and independent entities like the Conference Board, which produces the monthly US Consumer Confidence Index, are constantly announcing economic data. Central bankers also announce policy decisions; in the US, analysts who follow the Federal Reserve and parse its announcements are nicknamed Fed watchers. Because the US dollar is so important in the forex markets, US economic data is king. The top five information groups, ranked beginning with the highest significance to forex trading, are: n

Nonfarm payroll report

n

Retail sales

n

International trade reports

n

Federal Reserve policy decisions

n

Consumer Price Index.

Just as analysts do with corporate earnings announcements in the equity markets, observers will anticipate specific economic numbers prior to the release of the data. This provides an opportunity to play the news based on how the actual numbers compare to the expectations. If the numbers come out as expected, the currency is likely to be flat—any buying or selling attributable to the data has already been done. This is known as pricing the data into the market. If, however, the numbers are better or worse than expected, you can expect to see buying or selling (respectively) as traders adjust their positions accordingly—and sometimes, frantically. Naturally, there are two ways to play economic data announcements and other news: proactive or reactive. Proactive trading means placing your trades beforehand, in expectation of what will happen once the news is released. This is most useful when you have reason to believe the actual numbers will not match the expectation (usually called the consensus); you can be in position to profit when the currency price comes to you in reaction to the news. While this is the more profitable approach, it is also much more difficult and will produce some losses on those occasions when you are inevitably wrong. Reactive trading merely follows the news and trades based on what was released. In this case, you can use limit orders above and below the current trading range so that you can take a long position should the news be positive and the currency rise, or a short position should it be negative and the currency fall. Be aware that because trading volume picks up substantially just before and after such announcements, a phenomenon known as slippage will occur. This is a condition in which prices change so quickly that it becomes difficult to enter a trade at exactly the price you intended. In order to reduce trading volume and mitigate slippage, brokers tend to increase the spreads on trades around the time of significant announcements. By raising the price of forex trades temporarily, brokers try

to keep casual traders out of the market and limit activity to those who are serious about trading the news.

Economic fundamentals

for forex trading As we said in the introduction, fundamental analysis usually takes a longer view of trading. That is because many of the economic factors that affect currency valuations are slowermoving. The first factor is economic growth. Determining whether an economy is growing (or contracting) and how quickly means measuring its size, and the size of an economy is measured by its gross domestic product (GDP). GDP is composed of four elements: n

Consumption

n

Investment

n

Government spending

n

International trade balance.

Consumption is essentially consumer spending, which as we’ve heard over and over is the largest component of the US economy—about 70%. Investment is not the type of investment represented by buying stocks and bonds (or currency pairs); rather, it is capital investment—the purchase of assets, like factories and machinery, by companies. Government spending is self-explanatory, and the international trade balance is simply the value of exports minus the value of imports. (The trade balance can either add to or subtract from GDP. The US has run a trade deficit for many years, meaning we import more than we export; major exporters like China run a trade surplus.) Once we measure the size of an economy, it becomes possible to measure it each year and determine the net change. An expanding economy is a great thing, but obviously that doesn’t happen every year. If the economy contracts for two (or more) consecutive quarters, it is said to be in a recession. Growth rates of 2% to 4% have been typical for the US, which is a mature economy, but younger expanding economies like that of China may grow from 7% to 9% or even more each year. Remember, an economy that is hot and growing fast will produce a good bit of inflation, and for that reason, central banks in emerging nations are often quite comfortable with 6% and 7% inflation rates. Speaking of inflation, just as there are nominal and real interest rates, there is nominal and real GDP growth. Just because the economy grew at a rate of 5% last year doesn’t mean 5% more goods and services were produced. If inflation was 3%, those goods and services increased in price 3%, but the same quantity was produced. Real GDP growth would be only 2% in this case. GDP growth and interest rates have an inverse relationship. That means that as interest rates rise, GDP growth will fall. Less money being borrowed means less expansion of companies and fewer new companies, and therefore less economic activity. Conversely, central banks lower interest rates in order

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Watch the Cops and Kings chase down the elusive Convict Live Charting Room Free to First 100 every week. to spur economic growth. All of this is done with one eye on the inflation rate to make sure it doesn’t get out of hand. You should make it a habit to know the central bank targets for GDP growth and inflation in each country whose currency you plan to trade. Some very important economic data announcements won’t mean nearly so much to you if you don’t. The international trade balance is important as well. In discussing the basics of forex, one of the reasons for currency trading I mentioned was the exchange of currencies by multinational companies. To recap, a US company that manufactures in China and sells in Europe has to trade dollars for yuan to pay workers and suppliers in China (a transaction that pushes down the value of the dollar) and trade euros for dollars to bring profits home (which pushes up the value of the dollar). All of these many transactions each day have a real collective impact on the prices of currencies, so it can be expected that a country with a large trade deficit will tend to have a weaker currency. The existence of a trade deficit isn’t necessarily a bad thing in and of itself. Successful and strong economies—the US topping the list—routinely run such deficits. This is in part because profits from transactions taking place in foreign countries aren’t included in the balance-of-trade calculation. However, the period-to-period change in trade deficits will still tend to affect currency values simply because of the unavoidable need to exchange one for another, as outlined earlier. Central banks manage the relative strength of their currency against others because overly strong and weak currencies have negative economic effects. International trade is one of the main arenas where this is the case. A strong currency makes March 2015

• Technical Analysis of Stocks & Commodities • 13

FOREX FOCUS

a nation’s exports more expensive in its customer nations. When talking about Germany selling Mercedes cars in the US, a vehicle that costs 20,000 euros (wholesale, of course!) costs $26,000 when the euro is worth $1.30 but $32,000 when the euro is worth $1.60. The reduced buying power of the dollar against the euro means US consumers can’t afford as many euro-denominated goods, and European exports to the US will fall. That’s not good for European companies that are exporters! This is why China goes to great lengths to keep its currency value low. Its economy relies on exports, so it wants its products to be cheap in every country to which it sells its goods. Of course, a currency can’t be allowed to get too weak, or that nation’s consumers won’t be able to afford things that are imported— and every country imports something. In the US, a big one is oil, which can get more expensive the weaker the dollar gets. Since American consumers (who are also voters) get up in arms about high gasoline prices, the Fed has to keep the dollar strong enough to keep oil prices at least somewhat in check. Clearly, then, central bank policies are an important component of currency values over the short and long terms, and bear a close watch. Capital flows or movement of money between countries also bear watching. These flows can take a few different forms. The obvious one is what takes place in the various financial markets—stocks, bonds, and forex. But money can also flow into a country via direct investment such as when a foreign company builds a factory, mine, or distribution center there, and by acquisitions of domestic companies by foreign buyers. The flow of capital into a country will generally cause its economy to expand and its currency to appreciate. Finally, it is important to consider political stability. This can mean many things, from orderly government transitions— that is, via fair and open elections rather than coups or rigged elections—and consistent government policies to the lack of conflict internally or with neighbors. Investors like predictability, so countries that have a reputation of arbitrary actions—like the nationalization of industries or government confiscation of foreign assets—will suffer. Investors either won’t do business there at all, or if they do, they will demand a heavy risk premium. This reduced demand for the currency in question will drive its value down. Speaking of political stability, on that note I’ll close with the mention of the US dollar and its resilience as a reserve currency. Many pundits have long made noise about how the dollar would gradually disappear as the world’s primary reserve currency—one of the factors that makes it so dominant in the forex markets. First it was forecast to be replaced by the yen until the Japanese economy hit the doldrums in the early 1990s—a result of demographics, specifically its aging population. As its population gets even older, Japan’s economic woes will grow, not fade away, so the yen is no longer a candidate. Next it was the euro, the currency of the collective of European Union countries. But the 2008 financial crisis revealed the cracks in the euro’s foundation, namely that weaker economies in the European periphery (think Ireland, Greece, and Portugal as examples) were enjoying interest rates in the 14 • March 2015 • Technical Analysis of Stocks & Commodities

bond markets that resulted from the strength of their wealthier northern neighbors, like Germany and France. That strength was based on assumptions that stronger EU nations would bail out weaker ones should the need ever arise, which it did. That bailout is taking place now—up to a point. The danger is that if larger but still-troubled economies like Spain or Italy run into crisis, the bailout costs will be so high as to probably be unsustainable. That would severely damage the euro or end it altogether.

The US dollar

still reigns So it was that even after the credit rating of US sovereign debt was downgraded in 2011, and even after the Fed repeatedly printed money to dump into the economy, rates on US Treasury notes fell to historic lows of under 2%. Despite all the hand-wringing over the years about the US dollar, when push came to shove, the flight to quality still landed on US shores. While no one can guarantee the future, let this serve as an important lesson that the chorus of “experts” you hear on a daily basis won’t always be right.

Imran Mukati is the Managing Director of fixed income securities at Fairbridge Capital Markets, Inc. He may be reached via http://www.linkedin.com/imranmukati or via email at [email protected].

Further reading

Mukati, Imran [2014]. “Trading Forex: Understanding The Basics (Part 1),” Technical Analysis of Stocks & Commodities, Volume 32: November. [2014]. “Trading Forex: Markets & Trading (Part 2),” Technical Analysis of Stocks & Commodities, Volume 32: December. [2015]. “Trading Forex: Charting Your Way (Part 3),” Technical Analysis of Stocks & Commodities, Volume 33: January. [2015]. “Trading Forex: More On Charting (Part 4),” Technical Analysis of Stocks & Commodities, Volume 33: February.

Q&A SINCE YOU ASKED Confused about some aspect of trading? Professional trader Don Bright of Bright Trading (www.stocktrading.com), an equity trading corporation, answers a few of your questions. To submit a question, post your question to our website at http:// Message-Boards.Traders.com. Answers will be posted there, and selected questions will appear in a future issue of S&C. Don Bright of Bright Trading

Note to readers I want to thank Rob Friesen (president and COO of Bright Trading) for his help with this column for the last couple of months. His contributions are always appreciated. I was dealing with some health issues—I had a second heart valve replacement in November 2014. The procedure appears to be a success. I want to thank our readers for their emails of support. I’m looking forward to a much healthier 2015. A sincere thanks to all. Now, digging into some recent questions, here is one paraphrased from two similar questions from readers: MAKING SENSE OF THE PROGNOSTICATIONS Mr. Bright, at the start of every year I just shake my head in disbelief when I suffer through stock market predictions from a variety of “experts.” I see complete 180-degree comments from many pundits, sometimes within the same organization. Do you or any of your traders use any of these prognostications with any benefit? Traders, news organizations, and the ever-increasing list of forums, chat rooms or similar services—some free while some not even worth that, and some who get away with charging sometimes exorbitant monthly or annual fees—never cease to crack me up (while they laugh all the way to the bank). I have to laugh, or else my sympathy or empathy for their audience will cause tears. I am writing this column in early January 2015, which you’ll be reading sometime in March. I thought, What the heck! Rather than reviewing predictions from last year, which you can easily do, why not toss a few out for 2015 that you can check against what really happens.

Before you do the exercise of checking reality against predictions, let me say that professional traders of my acquaintance do read and even pass along many of these thoughts—if it fits their own biased agenda. Much like our current political climate, many traders, too, only get their information from sources they tend to agree with. But let me tell you this: Traders who make a good living (with a few exceptions) will digest the information and then do their own homework to come up with something simple—that is, by developing their own analysis tools from an objective viewpoint. This sounds simple, but similar to the way people tend to feel “right” in their political views, many traders tend to give a result from some prejudice. Bulls and bears, obviously, tend to only see good or bad.

Many traders only get their information from sources they tend to agree with. I like the idea of jotting down alternative narratives and then creating some simple if–then statements to help determine the possible results from whichever side you see as the most likely to occur. At the same time, calculate the then result if things go badly. I am going to paraphrase some market forecasts from various sources, purposely without credit or labels. My idea is not to see who might be right or wrong but simply to make a point about the vast disparity in thinking. Here are the narratives I’m going to track: 1. Total return: 10%–12%, or even a little higher. March 2015

2. Bullish, but not wildly bullish. Total return: 6%–10%. Not bad. 3. Total return: 8%—a decent amount of upside from here. 4. Total return: somewhere between -5% and 5%. 5. Great returns, less stable conditions. 6. The S&P could gain 10% with a 2% dividend that will give a total return of 12%. 7. Last year I predicted a stock meltup—growth would return and up we’d go. That prediction was off by one year. The market will be a surprise in 2015, going higher before leveling off in the third quarter. 8. I expect more of the same—interest rates dragging the bottom, averageto-poor job creation with part-time jobs leading the way, more good stock performance, but with unpredictable and unexplainable panic selloffs and volatility. 9. US stocks will be down 5% for the year. 10. A more negative outlook for the year, including a prediction of global deflation. The Fed will return to quantitative easing. 11. The market has been long for so long. I think we’ll have our first correction in 2015. Pick the predictions you like from above—not really!—and see how that goes, or do the research, prepare your own if–then statements, and have a successful 2015. As for me and my team, we’ll continue to play offense and defense by responding to the what is vs. the what might be.

• Technical Analysis of Stocks & Commodities • 15

16 • March 2015 • Technical Analysis of Stocks & Commodities

TRADING TECHNIQUES

Know Thy Weapons

Moving Averages: Some Finer Properties What is the difference between the 10-period of a five-period moving average and a 15-period moving average? Does the sum of moving averages equal the moving average of the sum? How does the smoothing of a ratio differ from the ratio of smoothing? How can you algorithmically calculate the weights of a smoothing procedure? Find the answers to such technical questions here.

A

ll technical analysts eventually engage in creating their own indicators and methods. And they all eventually use some kind of smoothing method to filter out noise. Various moving average methods can be used to smooth a series of values. In this article, I will discuss four interesting properties of simple and exponential moving averages (hereafter referred to as SMAs and EMAs, respectively). These two averaging methods are the most popular in the technical analysis world, and their weighting scheme is simple, so they have clear and nice properties. Those who aspire to create indicators should find the concepts discussed here useful. I will denote the n-period simple and exponential moving averages of an indicator P as SMAn(P), and EMAn(P), respectively.

WILLIAM L. BROWN

Moreover, MAn(P) will denote either SMAn(P) or EMAn(P). Linearity The first property of SMAs and EMAs worth remembering has to do with the way they treat the addition

of indicators and products of numbers with indicators. Here’s a more precise look at the properties. First property If P and Q are indicators and t is a constant number, then: SMAn (t • P + Q) = t • SMAn(P) + SMAn(Q) and EMAn (t • P + Q) = t • EMAn(P) + EMAn(Q) This property can easily be proved with basic mathematics. Example Say you want to smooth the typical price (TP) using a five-period EMA. The TP has the following formula:

where H, L, and C represent the high, low, and close of a bar, respectively. It doesn’t make a difference whether you take the five-period EMA of TP or sum the five-period EMAs of H, L, and C and then divide the sum by three. That is,

Commutative property You may not realize it, but in successive smoothing, using either an SMA or an EMA (or both) can change the order of averages without affecting the outcome.

by Giorgos E. Siligardos, PhD March 2015

• Technical Analysis of Stocks & Commodities • 17

Second property If P is an indicator, then MA1n (MA2k(P)) = MA2k(MA1n(P)) where MA1n and MA2k are SMAs or EMAs. Example If you want to smooth the closing price (C) three successive times using a five-period EMA, a 10-period SMA, and a 15-period SMA, then you can do it in whatever order you want, since all orders will have the same result. For example, taking the 5-EMA of the 10-SMA of the 15-SMA of C is exactly the same as taking the 15-SMA of the 10-SMA of the 5-EMA of C. That is, EMA5(SMA10(SMA15(C))) = SMA15(SMA10(EMA5(C)))

Figure 1: weighting schemes of successive ema smoothings. The weighting scheme of five successive 15-period EMA smoothings is shown using different colors. EMA(15) is the weighting scheme of the 15-period EMA, EMA(15,15) is the weighting scheme of the 15-period EMA of the 15-period EMA, and so on. The weights are expressed as percentages of their total sum of 100% and they are the y coordinates in the graph. The x coordinates are the ages of the weights in ascending order from right to left.

Like linearity, commutative properties in successive smoothing can be proved using simple mathematics, but it is a tedious task. If you only want to grasp the underlying reasons behind why this property holds using a simple approach, try proving that: SMA2(SMA3(P)) = SMA3(SMA2(P)) It’s simple.

Weighting effect in

successive smoothing What is the effect of successive smoothing of an indicator? The most logical answer would be that you would end up with an extremely smooth version of the indicator. Well, that’s true, but how does successive smoothing differ from, say, increasing the period of single smoothing? For example, what is the difference between EMA5(EMA10(P)) and EMA15(P)? Let me cut to the chase and give you the answer in simple terms.

Figure 2: weighting schemes of successive Sma smoothings. Similarly here, this chart illustrates the percentage weighting scheme of five successive five-period SMAs as a function of age. For comparison purposes, the weighting scheme of the 25-period SMA is also shown.

18 • March 2015 • Technical Analysis of Stocks & Commodities

Third property Successive application of MAs in an indicator creates a smoothed version of the indicator, where the percentage weighting scheme as a function of age of data resembles the shape of a bell. The more MAs applied and the higher their period, the smoother the indicator you get and the more widespread, symmetric, short, and chubby the bell-shaped weighting scheme becomes. In Figures 1 & 2, you see examples of the weighting schemes of successive smoothing five repeated times using 15-period EMAs and five-period SMAs, respectively. The weights are expressed as percentages of their total sum, which is 100%. In Figure 1, the EMA(15)

is the weighting scheme of EMA15(P), the EMA(15,15) is the weighting scheme of EMA15(EMA15(P)), the EMA(15,15,15) is the weighting scheme of EMA15(EMA15(EMA15(P))), and so on. The weights are sorted in ascending order of age from right to left so that the weight corresponding to age zero (which is the weight put to the most recent value of the indicator P) is the rightmost one. Similar notation is used for the case of SMAs in Figure 2. For comparison purposes, there is also the weighting scheme of SMA25(P) in Figure 2 [denoted as SMA(25)]. This general rule of bell-shaped weighting scheme also holds for successive smoothing using combinations of SMAs and EMAs. What does the change in shape of the weighting scheme show as new smoothings are applied? Does the change in shape make sense? It does, because the basic function of moving averages is to raise the contribution (weights) of old data at the cost of the contribution (weights) of the younger data. In effect, the more EMAs or SMAs you apply on top of one another, the more the older values appear in the calculations (thus getting comparably bigger weights) and the newer data gets comparably smaller weights. This has the effect of a bell shape in the weighting (as a function of their age), which moves like a wave to the left as new EMAs or SMAs are applied. Moreover, as the span of ages having significant percentage weights increases—due to the involvement of more and more indicator values as new MAs are applied—the bell becomes wider, relatively chubbier, and its maximum height becomes shorter.

Calculating the weights

In the cases you have seen so far, the weights depend only on the time instances in terms of age (and not on other factors like the values of some indicator or the volume of shares). For example, let P0, P1, P2… be the values of indicator P where the subscript denotes the age of its values (P0 is its most recent value, P1 is its value one bar ago, P2 is its value two bars ago, and so on). Let’s consider the EMA3(EMA3(P)), which is the three-period EMA of the three-period EMA of the indicator P. It is profound that the value of EMA3(EMA3(P)) for the latest bar (that is, for the bar of age zero) eventually equals a sum of type: w0P0 + w1P1 + w2P2 + …

(Equation 1)

where the weights w0, w1, w2… are constant numbers independent of the values of P. These weights are not greater than 1; their total sum is 1, and they represent the contribution of the respective P’s value to the creation of EMA3(EMA3(P)). For example, you can see that w0 = 0.25 or 25%, w1 = 0.25 (or 25%), and w2 = 0.1875 (or 18.75%), so 25% of the latest value of EMA3(EMA3(P)) is attributed to the most recent value of P (which is P0), another 25% of the latest value of EMA3(EMA3(P)) is attributed to the value of P one bar ago (which is P1) and another 18.75% of the latest value of EMA3(EMA3(P)) is attributed to the value of P two bars ago (which is P2). It is when the weights of a smoothing procedure depend on only the time instances in terms of age (like in the previ-

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ous example) that you can create stable charts like those of Figures 1 & 2. If you create a smoothing procedure that can be eventually formulated in a weighting scheme like the one of equation 1, where the weights depend only on the age of data, you can use a spreadsheet program like Excel to calculate and visualize the weights via charts no matter how complex your procedure is. To accomplish this, you create an artificial indicator P such that all its values are zero, and you write the formulas that dynamically calculate your smoothing function from P’s values. If you now change the value of P0 to 1, then the last value of your smoothing function will be equal to w0. That’s because, as you can see in equation 1, when P0 equals 1 and all other older values of P equal zero, then the last value of the smoothing function equals w0. So you copy this w0 and paste it somewhere else in your spreadsheet. You then again set P0=0 and proceed to set P1 equal to 1. This will make the last value of your smoothing function equal to w1. You copy w1 and paste it below w0. By setting P1 back to zero and setting P2 equal to 1, you can get the value of w2 and put it below w1. If you continue this way, you will be able to get all the weights of your smoothing procedure and chart them as a function of their age. In fact, this is the way the charts of Figures 1 & 2 were constructed. Using this technique, you can also verify the first and second properties stated earlier. Unfortunately, since this approach requires repeated substitution of values and copying & pasting, you will need to use macros in Excel if you want to calculate a large number of weights for various cases of successive smoothing. For educational purposes, the file “succ_EMA_weights.xlsm,” March 2015

• Technical Analysis of Stocks & Commodities • 19

sidebar Figure 1: the four sections of the spreadsheet. The Excel spreadsheet is divided into four sections and has a button labeled calc weights to call the macro, which will calculate the weights for all ages.

Using Excel To Calculate The SMOOTHING Weights

Excel is a simple and quick solution for the calculation and visualization of the distribution of weights in a smoothing method. In Sidebar Figure 1 you see a screenshot of the spreadsheet used to create the chart in the article’s Figure 1. The spreadsheet is divided into four sections and offers a button to call a macro. Section 1 is where you enter the desired periods for the five successive EMAs in the green cells. The respective alphas for the periods are automatically calculated below the periods according to the standard formula: alpha =2/(period+1). Section 2 contains the functions that calculate the successive EMAs’ values in descending order of age for an indicator whose values are in the indicator values column. The spreadsheet assumes 88 historical values for the indicator so

that the 88th value (the one that has an age of 88) is the oldest and the 0th value is the newest. All values of the indicator are initially set to zero. When only the 0th value (in terms of age) of the indicator becomes 1, then the 0th values (in terms of age) of EMAs—that is, the newest values of EMAs—will become equal to the EMAs’ weights for age zero (namely, w0). Similarly, when only the first value of the indicator becomes 1, then the 0th values of EMAs will become equal to the EMAs’ weights for age 1 (namely, w1) and, generally, when only the kth value of the indicator becomes 1, then the 0th values of EMAs will become equal to the EMAs’ weights for age k (namely, wk). Section 3 offers a quick way to calculate the weights of EMAs for an age. When you enter the age directly into the cell labeled age, the value of the indicator for that age in section 2 becomes 1 automatically, and the second row of section 3 labeled weight is populated with the weights of the EMAs (in alignment with section 1) for that age, which are exactly those in the last row of the table of section 2. Section 4 and button: When you click the button labeled calc weights, a macro runs in the background that repeatedly changes the age in section 3 starting from zero and increasing by 1 until it gets to 88. For every change in age, the macro copies the weight row of section 3 and pastes it in the table of section 4, populating it from the top cell and down. The table of section 4 is linked to a chart that offers a visualization of the weights like the one in Sidebar Figure 2. The labels of the chart are automatically updated according to the periods of section 1 as soon as the button is clicked. In Sidebar Figure 2, you can see the chart that corresponds to the data in Sidebar Figure 1.

sidebar Figure 2: charting the weights. As soon as you click the calc weights button, both the section 4 and its linked chart are updated. The chart shown here is based on the inputs and calculated weights of Sidebar Figure 1.

20 • March 2015 • Technical Analysis of Stocks & Commodities

The Excel spreadsheet discussed here can be downloaded from the Subscriber Area at our website, www.traders.com, in the Article Code area, as well as from http://traders.com/files/ succ_EMA_weights.xlsm.zip.

which I used to create the chart in Figure 1, is provided in the Subscriber Area of www.traders.com (as well as from http:// traders.com/files/succ_EMA_weights.xlsm.zip). It works in Excel version 2007 and above, and you need to enable macros to make the calculations. You can find out more details in the sidebar “Using Excel To Calculate The Smoothing Weights.”

Smoothing ratios

of indicators Ratios of indicators are widely used in technical analysis, mostly as a way to produce normalized percentage values. George Lane’s stochastics oscillator is such an example. I will now introduce the fourth property of MAs (which deals with smoothing indicator ratios) using a hypothetical example. Suppose you want to divide indicator P by the positive indicator Q so that you get a new indicator P/Q. This new indicator has proved to be erratic and you want a smoothed version of it using, say, a three-period SMA. You have two options:

Option 1 Calculate the three-period SMAs of P and Q separately and then divide them:

Option 2 Simply take the three-period SMA of P/Q; that is:

All technical analysts eventually use some kind of smoothing method to filter out noise.

where more weight is given to the values of P/Q, where Q is larger. Similarly,

results in a modification of

where, again, more weight is given to the values of P/Q, where Q is larger. The mathematically inclined might want to try and see that the underlying reason for this property is the same one that makes the harmonic mean give less significance to high-value outliers. If you don’t understand this peculiar connection, don’t get discouraged. Here is how you can get an idea of why the fourth property holds in this hypothetical example: If P0, P1, P2 are the three most recent values of P, and Q0, Q1, Q2 are the three most recent values of Q (where, as usual, the subscripts denote the age of the values), then the SMA3 assigns equal weights to the three most recent values. More precisely, the latest values of SMA3 for P and Q are: SMA3(P) = 1/3 P0 + 1/3 P1 + 1/3 P2

Technical analysts would consider the first option as a realistic solution, since it allows for occasional and isolated zero values for Q (it is more difficult for SMA3(Q) to be zero than for Q to be zero) but if Q is always nonzero, then either of the two options could be chosen. So what is the difference between these two smoothing options and how can you determine which one better suits your preferences? The answer lies in the fourth property for MAs: Fourth property If P and Q are indicators and Q is positive, then the formula

results in a modification of

and SMA3(Q) = 1/3 Q0 + 1/3 Q1 + 1/3 Q2 Using simple algebra, you can see that:



(Equation 2)

where:





(Equation 3)

for i = 0, 1, 2. It is clear from equation 2 that the latest value of SMA3(P)/ SMA3(Q) is just a weighted average of P/Q, where all three March 2015

• Technical Analysis of Stocks & Commodities • 21

The basic function of moving averages is to raise the contribution (weights) of old data at the cost of the contribution (weights) of the younger data. wis have the same denominator. Consequently, the numerator Qi in equation 3 is the one that determines the relative sizes of the wis. As a result, the higher the Qi (in relation to the other two values of Q), the higher the weight wi for P/Q and the higher the contribution of the ith value of P/Q (in terms of age) to the latest value of SMA3(P) / SMA3(Q). Which of the two smoothing options best suits your purposes? By choosing SMA3(P/Q), you assign equal weights to the three most recent values of P/Q, whereas by choosing SMA3(P)/SMA3(Q), you demand that the weights in the three most recent values of P/Q are analogous to the sizes of the respective values of Q. Note that charts like those in Figures 1 & 2 cannot be constructed for SMAk(P)/SMAk(Q) or EMAk(P)/EMAk(Q), since the weights of P/Q are not determined purely from the time instances in terms of age; they are also affected by the values of Q. As new price data and new values of P and Q are introduced, the weights assigned to the values of P/Q will change according to the relative sizes of the values of Q among each other.

Smoother is easier

This article may differ from other technical analysis articles in that it doesn’t promote a specific trading style or system. My main purpose here is to make the aspiring creator of new indicators familiar with four interesting properties of simple and

Commodity Channel Index—Developed by Donald Lambert, this price momentum indicator measures the price “excursions” from the mean. Exponential Moving Average—A variation of the moving average, the EMA places more weight on the most recent closing price. Harmonic Mean—An average obtained by taking the reciprocal of the arithmetic mean of the reciprocals of a set of nonzero numbers. One of the three Pythagorean means, where the harmonic mean is always the least of the three means. Since it tends toward the least, compared to the arithmetic mean, it can help mitigate the impact of large outliers. Heuristic Method—Problem-solving approached by trying out several different methods and comparing which provides the best solution. In behavioral finance, trial-and-error learning leading to the use of rules of thumb for decisions. High-Pass Frequency Filter—A detrending filter that lets pass the high-frequency noise and rejects low-frequency trend. Implemented by first applying a low-pass filter to the data, then subtracting the filtered data from the original data. Noisy Signal—A signal in which the effects of random influences can22 • March 2015 • Technical Analysis of Stocks & Commodities

exponential moving averages and give you a way to calculate the distribution of weights algorithmically for some moving average cases. The first two properties may save you some time when you try different combinations of ideas, whereas the other two uncover the effects of successive smoothing and the effect of separate smoothing of numerator and denominator in ratios so you can know beforehand what kind of smoothing you can use with respect to how you want your final indicator to react. SMAs and EMAs are widely used smoothing methods. If this article has increased your knowledge about these methods, then it has fulfilled its purpose. Giorgos Siligardos holds a doctorate in mathematics and a market maker certificate from the Athens Exchange. He is a financial software developer, coauthor of academic books in finance, a frequent contributor to this magazine, and scientific contributor in the Department of Finance and Insurance at the Technological Institute of Crete. Material from his course writings on derivatives has been used in educational enchiridia for bank managers. His academic website is http://www.tem. uoc.gr/~siligard and his current views on the markets can be found at http://market-calchas.blogspot.gr/. He may be reached at [email protected]. The Excel spreadsheet referenced in this article is available at the Subscriber Area at our website, www.traders.com, in the Article Code area. The spreadsheet is also downloadable from http://traders.com/ files/succ_EMA_weights.xlsm.zip.

Further reading

Siligardos, Giorgos E. [2013]. “The Average Age Of Averages,” Technical Analysis of Stocks & Commodities, Volume 31: April. ‡Excel (Microsoft Corp.)

‡See Editorial Resource Index

not be dismissed. Optimization—A methodology by which a system is developed with rules tailored to fit the data in question precisely. Outlier—A value removed from the other values to such an extreme that its presence cannot be attributed to the random combination of chance causes. Relative Strength Index (RSI)—An indicator invented by J. Welles Wilder and used to ascertain overbought/oversold and divergent situations. Smoothing—Simply, mathematical technique that removes excess data variability while maintaining a correct appraisal of the underlying trend. Probability Density Function—A graph showing the probability of occurrence of a particular datapoint (price). Probability Distribution Function—A function whose integral over any set gives the probability that a random variable has values in this set. Describes the relative likelihood for a random variable to take on a given value. Find more terms defined in the Traders’ Glossary at Traders.com.

FUTURES FOR YOU INSIDE THE FUTURES WORLD Want to find out how the futures markets really work? Carley Garner is the senior strategist for DeCarley Trading, a division of Zaner Group, where she also works as a broker. She authors widely distributed e-newsletters; for your free subscription, visit www.DeCarleyTrading.com. Her books—Currency Trading In The Forex And Futures Markets; A Trader’s First Book On Commodities; and Commodity Options—were published by FT Press. To submit a question, post your question at http://Message-Boards.Traders.com. Answers will be posted there, and selected questions will appear in a future issue of S&C.

oil, he is essentially selling dollars, that is, exchanging dollars for crude. If this were pairs trading, it might be identified as a symbol such as USD/CL. You’ve probably concluded that a trader who sells oil is buying the USD. Keep in mind that it is only possible to value one asset if you have an asset to compare it with. This concept is true in our daily lives; when we buy a gallon of milk at the grocery store, we are, in essence, selling our dollars. It is interesting to note that the value of crude oil priced in gold, rather than the US dollar, has been relatively stable for decades. In 2014, the price of crude oil per ounce of gold changed very little. Accordingly, it appears as though the price of the dollar is precisely why crude oil has fallen. This theory is corroborated by weakness in other commodity markets such as the grains, metals, and natural gas. Agricultural products such as corn and wheat underwent historical bear markets as the greenback marched higher. Similarly, the high-flying natural gas market in early

2014 quickly succumbed to pressure, forcing prices under $3.00. Although the relationship between grains and the currency market isn’t as absolute as that between crude oil and the dollar, it is difficult to argue the correlation doesn’t exist. Once again, grain buyers are also dollar sellers. Of course, there are additional factors that weighed on pricing. For starters, the US Energy Information Administration (EIA) consistently reported increases in crude oil stocks, creating what some referred to as a supply glut. On the demand side of the equation, slower growth in China and economic weakness in European nations resulted in a change of heart in the energy sector. In my opinion, the second predominate influence of crude oil in 2014 was simply trader emotion and margin call issues. Specifically, crude oil speculators began the year with near-record bullish positions. As these formerly bullish traders were being forced to exit their holdings Continued on page 43

QST Desktop

OPPOSITES ATTRACT Some are blaming the 2014 crude oil collapse on the strength of the US dollar; what are your thoughts? The hideous decline in crude oil during the latter half of 2014 was the result of several factors at work; however, I believe the biggest role player was the currency market. At the time of this writing, the correlation between crude oil and the greenback was hovering near 91%. In other words, in roughly nine out of 10 occasions, the price of crude oil had moved in the opposite direction as the dollar (during a 180-day dataset). Thus, any significant repricing in the dollar vs. other major currencies has a profound impact on crude oil. A quick look at the chart in Figure 1 tells a profound story of the relationship between crude oil and the US dollar. In July of 2014, the greenback found footing and forged a sharp rally; crude oil simultaneously peaked and fell precipitously. It is difficult to argue that each market is moving independently of the other. Some believe crude oil prices react to the dollar simply because oil is priced globally in terms of the greenback. Thus, as the dollar strengthens, crude oil feels more expensive to foreign buyers driving the demand and value lower. Further, a higher greenback means it takes fewer dollars to buy the same amount of underlying crude oil, thus lowering the asking price for the commodity. Another way to look at it is similar to trading the forex markets, that is, trading assets as pairs. If a trader buys the US dollar, he is simultaneously selling another currency; and vice versa. We don’t think of commodities as trading in pairs, but we should. When a trader buys crude

Carley Garner

Figure 1: crude oil vs. us dollar. On this weekly chart you can see that in July 2014, the US dollar forged a sharp rally. Crude oil simultaneously peaked and fell. March 2015

• Technical Analysis of Stocks & Commodities • 23

Gauging Momentum

MACD-Suitable Stocks by Kevin Luo

The

moving average convergence/divergence (MACD) signal line crossover is a popular technical indicator used by many traders and investors. The MACD was developed by Gerald Appel in the 1960s and is readily found in trading platforms of all types. It generates trading signals upon crossovers of its MACD and signal lines. The method is considered simple to use; however, many have doubts about how effective the method is. To find out whether the technique works, I conducted a backtest on a large portfolio of stocks traded on the major exchanges. The results of the backtest will help determine the level of effectiveness of the MACD method.

Here’s what I found

In the study, I selected approximately one third or 1,816 stocks traded on the NYSE and NASDAQ for the backtest. These 24 • March 2015 • Technical Analysis of Stocks & Commodities

stocks met the following selection criteria: 1. Are common stock 2. Trading at $2.00 or higher 3. Had continuous historical daily data (date, open, high, low, and close) from January 1, 2005 to August 31, 2014 4. Had no data errors, such as unadjusted price data from stock splits. My objective in backtesting using this process was to produce test summary statistics from the simulated trades (long trades only) of a portfolio of stocks. The scale of the backtesting is sufficient to make a reasonable conclusion about the effectiveness of MACD. The parameter setting used is the default at 12/26/9 (12-day EMA, 26-day EMA for MACD line, and nine-day EMA of MACD for the signal line). This study employs the MACD signal line crossover method as the trading rules for the backtesting. A buy takes place when an upward crossover occurs. A sell takes place when a downward crossover occurs. For calculation consistency and standardization, the close prices on the crossover days are used as the buy or sell price. For example,

ARROWS: Zmiter/COLLAGE: JOAN BARRETT

Trading signals generated by the crossover of Gerald Appel’s moving average convergence/divergence and signal lines are popular and simple to use. Do they work for all stocks in all market conditions? Find out here.

Intrendstocks.com

Figure 1: MACD Signal line crossover. The up arrow points to an upward crossover while the down arrow points to a downward crossover.

in Figure 1, the up arrow points to an upward crossover, while it is unlikely to make a profit over time on a portfolio of the down arrow points to a downward crossover, which is randomly selected stocks using only the MACD signal line the crossover immediately after the upward crossover. The crossover strategy. buy happens on the up arrow day and the sell occurs on the Why was the MACD signal line crossover method inefdown arrow day. The close prices on these days are recorded fective in the backtest? The methodology should not take the as the entry and exit price, respectively. The difference be- entire blame, because markets are not static. In fact, no study tween the exit price and the entry price is the simulated result has proved that a technical method works on all stocks all the computed in percentage terms. Using a custom-built stock time. Trading a group of randomly selected stocks using the analysis system, I ran the backtest and analyzed all trades in MACD or any other simple technique is unlikely to generate the 1,816 stocks. The summary of the backtesting results for the portfolio can be seen in the table in Figure 2. The value displayed in the fourth column of the table shows that from January 1, 2005 to August Figure 2: backtesting summary statistics for selected stocks. The annualized profit/loss for the 31, 2014, for the 1,816 stocks, the an- MACD from January 1, 2005 to August 31, 2014 was only 1.45%. nualized profit/loss was only 1.45%. I calculated this profit/loss figure based on an equal-weighted approach, that is, the same weight was assigned to each of the stocks in the portfolio regardless of stock prices. I used the following FIGURE 3: PRICE STATISTICS ON SIGNAL DAYS. The crossovers for signal days are the ones with the larger price movements. equation: Annualized profit/loss = Total profit/loss / Number of stocks / Time period (or 9.7 years) The results of this backtest showed that the MACD method did not produce a meaningful return. The finding suggests

The selected stock groups show significant improvements in profitability.

a meaningful profit over time. Methods are available to improve your results. One approach is to select suitable stocks. It’s an approach designed to make the MACD method more effective without revising the MACD setting or directly incorporating other technical indicators into the technique. How do you identify suitable stocks? One way is to connect to the root of the MACD. The MACD is considered a trending momentum indicator. In the table in Figure 3, the statistics from the backtesting process show that the crossover, or signal days, are the ones with the larger price movements. On the entry signal day, the average close high/low, expressed as closetoday – closeyesterday in percent, is 2.18% (column 2) compared to 0.44% March 2015 • Technical Analysis of

Stocks & Commodities • 25

FIGURE 4: TREND CHART. Here you see the isolated up and downtrends for Alcoa Inc. (AA).

Stocks with greater trend range and number of uptrends are considered suitable for MACD trading and could be sought for further analysis.

What does this tell you?

This suggests that the MACD was developed with the intention to catch the uptrend movements by taking a long position when the upside momentum surges and exiting the position when the (in column 3) on average for a typical uptrend day (I’ll discuss downside momentum moves in. If this assumption can be stock trends later). On the exit day, the average close high/low confirmed, it means the characteristics of an uptrend must be is -1.92% (column 4) compared to -0.55% (column 5) daily, related to the trading performance of the MACD. Mathematically, if the entry price remains the same, then on average, during a typical downtrend. the higher the exit price, the greater the profit. It is reasonable to assume that this price range from the entry to the exit is positively related to the stock trend range. The next step is to confirm the existence of such a relationship. To establish the connection, I need information on stock trends. FIGURE 5: RANK OF TREND CHARACTERISTICS. When the trend ranges of a stock are found to be suitable for MACD To understand the charactrading, selecting the stocks with a higher number of uptrends produces the greater profit. Stocks with greater trend ranges teristics of a price trend, it is and number of uptrends are considered MACD-suitable stocks. necessary to first isolate all stock trends from the raw datasets. In this study, there are two types of trends: An uptrend is recognized when the uptrend range is measured at or greater than 20%. A downtrend is recognized when the downtrend range is FIGURE 6: BACKTESTING SUMMARY FOR THE TOP-RANKED STOCKS. The selected stock groups had much better measured at 20% or greater. profitability results. The highest-ranked stocks had the highest return. 26 • March 2015 • Technical Analysis of Stocks & Commodities

INDICATORS

In Figure 4 you see the isolated trends for Alcoa Inc. (AA). The software, which was used in the backtesting, is capable of isolating the stock trends. After the trends of 1,816 stocks were isolated, the trend range traits can be summarized. The software outputs and exhibits the statistics of trend range and number of uptrends for the period that is being studied (see the table in Figure 5). The number of uptrends statistic (column 3) is considered as important as trend range. It refers to the trend count for a specific stock. If the trend ranges of a stock are suitable for MACD trading, then the higher values for the number of uptrends produce the greater profit. Therefore, stocks with greater trend range and number of uptrends are considered suitable for MACD trading and could be sought for further analysis. In order to pick out stocks fitting that description from the 1,816 stocks, each stock was ranked according to uptrend range and number of uptrends. The higher rank is given to the stocks with the greater trend range and number of uptrends combination (column 4). The rank number is merely for sorting stocks. I used three groups of stocks. Group 1 contains the top-25 ranked stocks. Group 2 holds 25 stocks ranked from 26 to 50. Group 3 includes 25 stocks ranked from 51 to 75. The stocks are mutually exclusive but are considered to be the more suitable stocks for the MACD signal line crossover method. The expectation is that group 1 outperforms group 2, and group 2 outperforms group 3 in the backtesting because of the rank levels. After the software implemented the tasks of reorganizing and summarizing the backtesting results according to the three groups, it resulted in the statistics you see in the table in Figure 6. Comparing these results with the initial backtesting results, it is clear that the selected stock groups show significant improvements in profitability (column 5) over the 1.45% profit generated from the random portfolio of 1,818 stocks (Figure 2). If you look at the average profit & loss per trade in column 6, you’ll see that group 1 has the highest return, followed by group 2, then group 3. This indicates a positive relationship between the ranking and MACD profit. There was only one unprofitable stock in group 2. All other stocks generated profits in the backtests (columns 7–8).

It works

A given technical indicator is popular for a reason: It works when it is properly used. By understanding of basics of the MACD signal line crossover method, I have established, through this study, that there is a positive relationship between the method and traits of a stock trend, trend range, and number of uptrends. The successful confirmation of the relationship in turn helps to find suitable stocks that can be used for MACD backtesting. This approach translates to a significant improvement in the effectiveness of the crossover method. More important, it is easy to implement. Kevin Luo is an independent technical analysis researcher who focuses on automated price trend–related analysis and generation of trading strategies. He and his project partners have developed an automated trend analysis and backtesting system for high- and low-frequency trading. He may be reached via email at [email protected].

Further reading

Appel, Gerald [1979]. The Moving Average Convergence/ Divergence Method, Traders Press. Pankhania, Ajay [2013]. “Muscle Up Those Averages,” Technical Analysis of Stocks & Commodities, Volume 31: September. Star, Barbara [1994]. “The MACD Momentum Oscillator,” Technical Analysis of Stocks & Commodities, Volume 12: February. ‡Intrendstocks.com

‡See Editorial Resource Index

Sneak preview … Coming soon! Dissecting Warren Buffett’s Macro Buy–Sell Indicator by Matt Blackman When it comes to investing, the Oracle of Omaha usually plays his cards close to his chest. But here is one favorite indicator that he has been willing to share.

Spatial Pattern-Recognition Skills by Martha Stokes There’s more to chart patterns than merely identifying them. Find out how you can see relationships between candlestick bars and patterns to better asses what price is likely to do.

2015 Readers’ Choice Awards Stocks & Commodities presents the 2015 Readers’ Choice Awards for products and services that our subscribers find useful, in more than 20 categories.

March 2015 • Technical Analysis of

Stocks & Commodities • 27

Judging By The Numbers

Here’s how to start with the basics and determine if an identifiable event has a statistical edge in predicting future prices—before you even start to build a trading system.

M

by John F. Ehlers and Ric Way any trading systems begin with indicators, and because of that, the question you should be asking is, “What do indicators indicate?” The correct answer is that most of the time, they don’t indicate much. Indicators are just specialized filters.

Visible sieves

Some indicators, like the commodity channel index (CCI), relative strength index (RSI), and stochastic, are basically first-order high-pass filters that remove the longer wave components of the prices and display them as oscillators. Other indicators, like moving averages, are basically smoothing filters that remove the high-frequency components and 28 • March 2015 • Technical Analysis of Stocks & Commodities

aliasing noise. Of course, there are combinations of the two kinds of filters. The basic question still remains whether shaping the price data by filtering has any predictive power regarding future prices. Other trading systems involve setups, such as, “Buy when the current close is below the close nine days ago and the last four closes have been consecutively lower and the high 27 days ago is higher than the current high by at least the square root of 1.618.” Clearly, such a setup is heuristic and may or may not be true for future prices. Candlestick patterns and chart patterns also fall into the broad category of setups. The trick here, again, is to determine whether these setups have predictive power regarding future prices. Still other trading systems attempt to predict the direction of future prices by correlation with other leading indicators. For example, every trader has heard that volume leads price. Such correlations would be nice if they were correct for long enough to make a trading system profitable. The process of trading system design is very much like quan-

Peshkova, SHUTTERSTOCK/adaptation: NIKKI MORR

Trading System Design: A Statistical Approach

tum mechanics, in that an entity is described by a probability density, and a future state can only be estimated statistically. In this article, we will show you how to start with some basics to see if an identifiable event has the statistical edge in predicting future prices before you even start to build a trading system. Once you identify a predictive event, then it is a simple matter to move on to designing a robust trading system. We will illustrate the entire process with an example.

Price predictors

The process of designing a trading system starts with measuring prices into the future from any identifiable event. Our own bias is that we have noted a more or less monthly cycle in most market data, particularly in index futures. It is comforting to note that this cycle activity is consistent with the fundamental observation that most companies have to make their numbers on a monthly basis. A monthly cycle implies a movement consisting of 10 days up and then 10 days down. With this consideration, we start with the presumption that we want to predict the prices 10 days into the future. Since we are constrained to work with actual data, we shift the point of reference 10 days back in history as the point of occurrence of the event. In EasyLanguage, variables are stacked for reference in the code. For example, Close – Close[9] means the price increase over the last 10 days with reference to the closing prices. In sidebar “EasyLanguage Code To Test The Predictability Of An Event,” you see how we measure the prediction from the time of the event. The test code begins by expecting an event that happened 10 bars ago. This tester is general, and the event can be anything that is describable by computer code. The crossing of two moving averages is just one example. Given that an event has occurred, the percentage increase or decrease in prices over the next 10 bars is computed, ending with the current closing price. This percentage price, referenced to the closing price 10 bars back, is assigned to the variable FuturePrice. FuturePrice is limited to be between -10% and +10%. After limiting the range, FuturePrice is rescaled to vary from zero to 100 so that the FuturePrice can be contained in one of 100 bins. The plan is to accumulate the number of occurrences of a FuturePrice in each of the bins over the entire span of the price data series. We use 10 years of data to create a statistically meaningful sample size. At the end of the data, the number of occurrences in the bins creates a probability distribution function of the prices 10 bars into the future from the event. We also provide a quick measure of the average percentage future price by measuring the center of gravity (CG) of the probability distribution function. If the probability distribution function outline were cut out of a piece of paper, the CG would be the place along the horizontal axis where the outline would balance. The general procedure of a function in X and Y coordinates is to sum the XY products and also sum all the Y values. The ratio of these sums gives the CG. Since the X dimension is centered at 50, the 50 is removed so that plotting the CG gives a sense of the zero profit point. The CG and ebb & flow are plotted below the barchart as successive

EasyLanguage Code To Test The Predictability Of An Event Vars: Event(false), FuturePrice(0), I(0), CG(0), Denom(0); Arrays: PredictBin[100](0); {>>>>>>>>> Code for Event Goes Here <<<<<<<<<<} If Event Then Begin FuturePrice = 100*(Close - Close[9]) / Close[9]; //Future is referenced to 10 bars back If FuturePrice < -10 Then FuturePrice = -10; //Limits lower price to -10% If FuturePrice > 10 Then FuturePrice = 10; //Limits higher price to +10% FuturePrice = 5*(FuturePrice + 10); //scale -10% to +10% to be 0 - 100 End; //Place the FuturePrices into one of 100 bins If FuturePrice <> FuturePrice[1] Then Begin For I = 1 to 100 Begin If FuturePrice > I - 1 and FuturePrice <= I Then PredictBin[I] = PredictBin[I] + 1; End; End; //Measure center of gravity as a quick estimate CG = 0; Denom = 0; For I = 1 to 100 Begin CG = CG + I*PredictBin[I]; Denom = Denom + PredictBin[I]; End; CG = (CG/Denom-50)/5; Plot1(CG); If LastBarOnChart Then Begin For I = 0 to 100 Begin Print(File(“C:\PDFTest\PDF.CSV”), .2*I - 10, “,”, PredictBin[I]); End; End;

events are encountered. The probability distribution function can be viewed by charting it in Excel. We created a folder on our computer named C:\PDFTest. When the last bar on the chart is encountered, a text file named PDF.CSV is created in this folder. It is then a simple matter to view the probability distribution function by importing this file into Excel and plotting it as a vertical bar chart.

Example

A specific example of testing an event for predictability will undoubtedly make the process clearer. In a previous article titled “Predictive Indicators” published in the January 2014 issue of Technical Analysis of Stocks & Commodities magazine, we demonstrated that a stochastic indicator could March 2015

• Technical Analysis of Stocks & Commodities • 29

TRADING SYSTEMS

Predictability Test Of A Stochastic Trading System

A Simple Stochastic Trading System

Vars: Event(false), FuturePrice(0), I(0), CG(0), Denom(0);

Inputs: StocLength(8), Threshold(.3), TradeLength(14), PctLoss(3.8);

Arrays: PredictBin[100](0); //>>>>>>>>>> Start Event Code Inputs: StocLength(10); Vars: HiC(0), LoC(0), Stoc(0);

Vars: HiC(0), LoC(0), Stoc(0); HiC = Highest(Close, StocLength); LoC = Lowest(Close, StocLength); Stoc = (Close - LoC) / (HiC - LoC); If Stoc Crosses Under Threshold Then Buy Next Bar on Open; If Barssinceentry >= TradeLength Then Sell Next Bar on Open; If Low < EntryPrice*(1 - PctLoss /100) Then Sell Next Bar on Open;

HiC = Highest(Close, StocLength); LoC = Lowest(Close, StocLength); Stoc = (Close - LoC) / (HiC - LoC); If Stoc[9] Crosses Under 0.2 Then Event = true Else Event = false; //<<<<<<<<<<<< End Event Code If Event Then Begin FuturePrice = 100*(Close - Close[9]) / Close[9]; //Future is referenced to 10 bars back If FuturePrice < -10 Then FuturePrice = -10; //Limits lower price to -10% If FuturePrice > 10 Then FuturePrice = 10; //Limits higher price to +10% FuturePrice = 5*(FuturePrice + 10); //scale -10% to +10% to be 0 - 100 End; //Place the FuturePrices into one of 100 bins If FuturePrice <> FuturePrice[1] Then Begin For I = 1 to 100 Begin If FuturePrice > I - 1 and FuturePrice <= I Then PredictBin[I] = PredictBin[I] + 1; End; End; //Measure Center of Gravity as a quick estimate CG = 0; Denom = 0; For I = 1 to 100 Begin CG = CG + I*PredictBin[I]; Denom = Denom + PredictBin[I]; End; CG = (CG/Denom-50)/5; Plot1(CG); If LastBarOnChart Then Begin For I = 0 to 100 Begin Print(File(“C:\PDFTest\PDF.CSV”), .2*I - 10, “,”, PredictBin[I]); End; End;

be the kernel of a successful trading system if the turning points were anticipated rather than waiting for confirmation. We will reinforce that assertion in our example. Our example will create an event when the simple stochastic swings between zero and one. The turning point for a long entry 30 • March 2015 • Technical Analysis of Stocks & Commodities

Once you identify a predictive event, then it is a simple matter to move on to designing a robust trading system. occurs when the stochastic crosses under a threshold of 0.2, because crossing this threshold anticipates the price turning up. The complete code for the example is shown in the sidebar “Predictability Test Of A Stochastic Trading System.” The basic stochastic indicator is just the current closing price less the lowest closing price over the length of the indicator, normalized to the difference between the highest closing price and the lowest closing price over the length of the indicator. The event occurs when the stochastic 10 bars ago crosses under the 0.2 threshold. When we applied this indicator to 10 years of the S&P futures continuous contract using a 10-bar long stochastic indicator, we found that the CG plotted to be 1.09% at the end of the 10-year period. This relatively high 10-year average profit leads us to examine the probability distribution of predicted prices. This probability distribution function is shown in Figure 1. Since the event of the stochastic crossing under a threshold is shown to be substantially predictive, we can now proceed to write a trading system that trims the performance by adjusting the length of the stochastic and the precise threshold level that works best, and by limiting losing trades with a stop-loss.

Example trading system

In the sidebar “A Simple Stochastic Trading System” you will find the complete EasyLanguage code for our example stochastic trading system. When we optimize performance over 10 years of the S&P futures continuous contract, we find that the

Percent price gain after event Figure 1: probability distribution function. A stochastic indicator crossing under a 0.2 threshold is highly predictive of future prices.

Testing, testing

Equity ($)

We have outlined a procedure for the successful development of trading systems using a statistical approach. We have developed a code testbed that can assess whether the prices will statistically increase or decrease over 10 bars after an event. The event itself is completely general as long as it can be described in code. The event can show whether prices will go up (signaling long position trades) or whether prices will go down (signaling short position trades). Once a predictive event has been determined, it can then be written into a trading strategy, Trade number whose parameters can be trimmed to Figure 2: equity growth. Here you see the equity growth curve over 10 years for the stochastic system. optimize performance. The testbed can also be used to assess whether an event is robust across a number of stock or futures symbols. The testbed The code given in this article is available at the Subscriber Area at works on a basis of sample bars of data. Therefore, the testbed our website, www.traders.com, in the Article Code area. is equally applicable to any sample rate, including intraday See our Traders’ Tips section beginning on page 47 for commentary data or even equitick bars. and implementation of John Ehlers’ & Ric Way’s technique in variS&C Contributing Editor John Ehlers is a pioneer in the use of cycles and DSP techniques in technical analysis. He is president of MESA Software. MESASoftware.com offers the MESA Phasor Futures strategy. He is also the chief scientist for StockSpotter.com, which offers stock trading signals based on indicators and statistical techniques. Ric Way is an independent software developer specializing in programming algorithmic trading signals in C#. He may be reached at [email protected].

ous technical analysis programs. Accompanying program code can be found in the Traders’ Tips area at Traders.com.

Further reading

Ehlers, John [2014]. “Predictive Indicators,” Technical Analysis of Stocks & Commodities, Volume 32: January. ‡StockSpotter.com, MESASoftware.com †See Traders’ Glossary for definition ‡See Editorial Resource Index

March 2015

• Technical Analysis of Stocks & Commodities • 31

www.StockSpotter.com

Occurrences

best stochastic length is eight rather than 10. The threshold to be crossed is 0.3 rather than 0.2. The best length of trade is 14 rather than the 10 bars into the future used in the prediction test. We have also limited losing trades to be no more than 3.8%. The equity growth over 10 years of our stochastic system is shown in Figure 2. Pretty impressive for a really simple system! And we dare say it’s superior to most commercially available trading systems.

A New Frontier

News data, which has long been the province of institutional traders, is now making its way into the hands of retail traders. Here’s a look at how you can incorporate this data into your trading strategies.

We

by Stephen Massel

all know that news moves the markets, but what is less easy to determine is exactly how the market will react immediately after the news event as well as later, once market participants have had a chance to digest and analyze the news in more detail. The algorithmic interpretation of these news events and more detailed news stories has long been the province of the hedge funds, which

32 • March 2015 • Technical Analysis of Stocks & Commodities

have the resources to spend on research & development in this specialized area. However, as with most advanced technological developments, there comes a time when it becomes more widely available. The use of news analytics and news sentiment has reached this point, and more and more traders are now gaining an edge by using news data.

Quantifying news

The development of trading strategies based on traditional technical analysis using price action, volume, fundamental economic data, and derived indicators relies on backtesting for performance evaluation. The backtesting is based on historical data that, of course, has all the news known to the market at the time backed in. This is all well and good, but would it not

VICTOR MARCHAND KERLOW

News Sentiment

be better if news could be quantized and decoupled from the history? This would allow an additional dimension of detail (in the same way as trade volume is separate) affecting price action. This would also allow the strategy to react and adapt to real-world market events, rather than rely on a purely statistical representation of backed-in news events. In this article I will detail how traders can now access this news data and incorporate it into their trading strategies. The focus will not be on the high-speed receipt of news, as the advantage there lies with the high-frequency trading firms operating in time frames of micro and nano seconds, with whom the average trader cannot compete.

What is news sentiment?

The amount of news stories that are broadcast or published by multiple media outlets on the economy as a whole, on individual companies, and on global geopolitical events continues to rise. Making sense of all this data—filtering out what’s relevant and important, and to what extent—used to be the job of large investment houses’ research departments. However, with the advent of digitization of news content, advanced computing, and language interpretation techniques, this data can now be effectively and quickly analyzed. The programs that analyze this data are often referred to as news sentiment algorithms. They use advanced natural language heuristics and statistical techniques to quantize the news from various sources. This is a multistep process running in real time that involves: n

Inputting news from single or multiple sources (for example, broadcast TV channels, market data vendors’ newsfeeds, RSS web feeds, Internet blogs, etc.). These feeds can provide purely news headline and content (text) or additionally include metadata tags (for example, topic, company name, sentiment score, etc.)

n

Digitizing and formatting the data for processing

n

Parsing the data—looking for specific keywords, sentences, phrases, and so on

n

Applying weightings to the parsed data based on context, uniqueness, occurrences, extremeness of language, and so on, and generating a positive or negative value based on market impact, relevance, etc. (this step and the previous step are really the secret sauce, where the algorithm really earns its salt)

n

Consolidating all values and providing a news sentiment value for the specific news event. Results can be categorized as required (for example, macroeconomic, company/country/industry-specific, and so forth).

This sentiment data is provided throughout the day in close to real time, and often with additional metrics, such as: n

News sentiment (a negative, zero, or positive value representing news on a scale of bad to good)

Traders can now access news data and incorporate it into their trading strategies.

n

News flow (a zero or positive value, representing the number of news events or stories interpreted)

n

Z-score (a negative, zero, or positive value, representing statistical relevance of the sentiment value above or below the average)

n

A news link (a URL link to the underlying news story).

The key to success, of course, is the way the algorithm interprets the news text together with a strategy for managing duplication. The good news is that you do not need to create these algorithms yourself; the resultant news sentiment data is now becoming more widely available, and ultimately the best way to test its efficacy will be to create a strategy and analyze its effectiveness.

Applying it to your trading

News sentiment data can be of great assistance in various ways. A discretionary trader can use it as an additional indicator, the portfolio manager or investor can use it to keep track of news events affecting his holdings, and as I mentioned earlier, it can be incorporated into an automated strategy for backtesting. I’ll review each of these areas in some more detail.

Portfolio management

Any portfolio manager or investor will be interested in specific news pertaining to their holdings. Keeping up with all the news, especially for large portfolios, can be an overwhelming task. News sentiment can be of great benefit here, where a news sentiment feed can alert the manager to news events, on a per-company or industry basis. This can be achieved by simply having two or three additional metrics associated with each holding, namely news sentiment, flow, and z-score. The manager can then quickly get a high-level view of the news affecting his holdings, and can be alerted to any elevated activity. He can then dig down into the specific news articles from various sources to more fully understand the potential impact on his holdings. This automated method of highlighting relevant news saves a huge amount of time in manually scanning various news media, and it’s suitable to mobile devices for a manager on the move.

Strategy development

There are two main applications of sentiment data in strategy development. You can either use it as the primary driver and create a strategy around it directly, or use it as a filter for an existing strategy. In either case, when using this March 2015 • Technical Analysis of

Stocks & Commodities • 33

StockNewsSentiment.com

With the advent of digitization of news content, this data can now be effectively and quickly analyzed.

Figure 1: identifying support levels. The stock price finds itself at trendline support at the same time that the short-term news sentiment trend turns positive.

history for your purposes. As with any other data, news sentiment data can be used to drive a range of indicators available in today’s trading platforms. One of the most common ones is the basic moving average indicator, which can be used to gauge short-term news trends. For an existing strategy, this could be used as a filter to improve performance. Let’s say you have a short-term strategy that holds positions for a few days or weeks. You could decide to only enter a new position at the start of a positive news trend and avoid entering positions on bad news. The potential uses of this data, including flow and z-score, are literally limitless and can provide a significant edge in your strategies.

Discretionary trading

Figure 2: channel support. The price is approaching a channel support line with decreasing volume at the same time that the news sentiment trend reaches extreme negative levels.

data, one of the first considerations is to ensure the volume of data matches your expectations. News sentiment typically provides a single value per news story; this may be of great interest in itself, depending on the magnitude of the value. However, for a trading strategy you will want to make sure there is sufficient data for your time frame and style of trading. For example, when daytrading, if your news sentiment value starts the day off at zero and cumulatively builds during the day, you may not have sufficient data in the morning session to make a valid trade decision. Smaller stocks, including some within the S&P 500, will not have news every day, whereas macroeconomic or broader categories of news sentiment will have much greater flow. For strategy development and backtesting, you will also want to ensure there is sufficient 34 • March 2015 • Technical Analysis of Stocks & Commodities

As in strategy development, sentiment data can be effective as a decision support tool in discretionary trading. Like with any other indicator, there is no silver bullet, but any additional evidence to support a trade can sometimes prove very helpful. Here are some examples of its use.

Example 1: Below the Advanced Micro Devices Inc. (AMD) chart in Figure 1 is a plot of AMD daily news sentiment (white line) and the five-day moving average (bar chart). The stock finds itself at trendline support the same time as the short-term news sentiment trend turns positive. Here, news sentiment was useful in assisting the decision with regard to whether there might be a bounce at support. Example 2: In the chart in Figure 2, the stock price of Exxon Mobil Corporation (XOM) is approaching a channel support line with decreasing volume the same time as the news sentiment trend reaches extreme negative levels.

Example 3: In the chart of Coach Inc. (COH) in Figure 3 you see several examples of price approaching support & resistance levels at the same time that the short-term news trend changes direction. Example 4: In Figure 4 you see extreme positive news sentiment trend events for Duke Energy Corporation (DUK) highlight significant turning points.

Sources of news

sentiment data News sentiment data in various forms is available from several sources, and of course at various prices. Here are some specialist news sentiment data providers: n

Dragonfish (StockNewsSentiment.com, dragonfishgroup. com)

n

Opfine (opfine.com)

n

FinSents (finsents.com)

n

n

n

n

FIGURE 3: SUPPORT & RESISTANCE LEVELS. Price approaches support & resistance levels at the same time that the short-term news trend changes direction.

Ravenpack (sentimentnews. com) Dow Jones (http://new. dowjones.com/products/djnews/news-machine-analysis/) Thomson Reuters (http:// www.machinereadablenews. com/p-sentiment-indices.php) Bloomberg (bloomberg.com/ professional/news-research/ news/)

FIGURE 4: TURNING POINTS. Extreme positive news sentiment highlights significant turning points in the stock price.

Trading by news

With the increase of news sentiment data availability, the opportunities now exist for individual traders to utilize this data in their strategies and trading decisions and for investors to be quickly alerted to important news events affecting their holdings. Furthermore, this sentiment data can now be obtained at a fraction of the cost of paying for an expensive newsfeed from the traditional big vendors. This is one more example of technology that was once only available to the large trading firms, but is now becoming available to individuals to bring their trading up to a more sophisticated level.

and trading strategy development/testing company. He can be reached via his website at www.dragonfishgroup.com.

Further reading

Cameron, John [2013]. “Market Mobs,” Technical Analysis of Stocks & Commodities, Volume 31: August. ‡StockNewsSentiment.com (Dragonfish LLC) ‡See Editorial Resource Index

Stephen Massel has been developing strategies and indicators and trading futures & options for more than 18 years. He is cofounder of Dragonfish LLC, a news sentiment data provider March 2015 • Technical Analysis of

Stocks & Commodities • 35

INTERVIEW

Don’t Get Caught Unaware

Using ETF Momentum Strategies With Les Masonson Leslie N. Masonson is president of Cash Management Resources, a financial consulting firm that he founded in 1987. Masonson’s 44-year career has spanned trading, investing, financial advisory services, bank operations management, teaching, and corporate cash/treasury management consulting. He was a financial advisor for six years offering investment management services to retail clients of large financial institutions. Masonson has authored books on cash management, daytrading, market timing, and relative strength investing using ETFs. He also writes book reviews for Futures magazine and has written product reviews for this magazine. His website is www. buydonthold.com and he can be reached at [email protected]. Stocks & Commodities Editor Jayanthi Gopalakrishnan spoke with him on January 5, 2015 about trading and investing in exchange traded funds (ETFs) using momentum strategies. I expected to get into the investment management business after receiving my master’s degree in January 1970, but none of the brokerage houses or banks were hiring. So I ended up working for Irving Trust Company as a quality control analyst. I then managed a number of operational departments before departing to become a cash management consultant at the Bank of America. I then joined Citibank for seven years, where I focused on providing fee-based cash management consulting services to the banks’ large corporate clients. Thereafter, I started my own cash management consulting firm and worked in that specialty for 17 years. After that I decided to put my investment knowledge into practice by becoming a financial advisor for six years. After conferring with hundreds of people who were looking for financial advice, I learned that the vast majority of them had a very limited knowledge of the stock market and financial matters. You’re a big believer in the buy-don’thold strategy, which is contrary to what most advisors tell their clients to do, as far as long-term stock investments are

36 • March 2015 • Technical Analysis of Stocks & Commodities

Buying & holding is hazardous to your wealth because you have to sit through the bear markets, which can be emotionally and financially draining. concerned. Why the buy-don’t-hold approach? After spending thousands of hours researching the markets over decades, I’ve come to the conclusion that buying & holding individual stocks is too dangerous and too risky a strategy for investors. First of all, you have to be smart or lucky enough to buy a portfolio of the right stocks or your performance will not be good. Just look at what happened to the popular “nifty fifty” growth stocks such as Eastman Kodak, IBM, Polaroid, and Xerox of the 1960s and ’70s. Their prices exploded until they ran into the crushing 1973–74 bear market. Buying & holding is hazardous to your wealth because you have to sit through the bear markets, which can be emotionally

WORLD MAP: PILart/NYSE STOCK EXCHNAGE: LUCIANO MORTULO/SHUTTERSTOCK

Les, why don’t you start by telling us a little bit about yourself and how you got interested in the financial markets. I’ve been interested in the stock markets since 1957 when my grandmother gave me a few shares of PanAm Airways for my 13th birthday. From that point on I started reading about the markets, even though there were only a few books in my local library. I also traveled to Manhattan to visit the NYSE and AMEX visitor’s galleries during my summer breaks from junior high school. I opened a brokerage account for minors and I also attended a few stockholder annual meetings in the NYC area for companies that I owned. Those were both interesting learning experiences. After high school, I received my college degrees—a BBA in Finance and Investments from the City College of New York and an MBA in Operations Research from Bernard M. Baruch College. My master’s thesis title was “Statistical Evaluation of the Relative Strength Concept of Common Stock Selection.” After performing the research for my thesis, I was convinced that using a relative strength momentum strategy would be a viable investing approach.

and financially draining. We experienced this in the 2000–02 bear market when the S&P was down 49.1%, and then again during the 2007–09 crash when the S&P was down 56.7%. So we’ve had two devastating bear markets in a 10-year time frame, and we’ll have more down the road, just based on history. These bear markets will continue to crush people’s portfolios and they won’t be happy about it, and they may sell at the bottom, which is what many investors usually do. Many investors, especially those over 55, cannot afford to lose so much money when they most need it. If you have a 50- to 80-year time horizon, then perhaps buy & hold will work for you. But that is not realistic for most people. Defensive investing is the way to avoid the big bear markets. Second, the typical investor does not have the financial training or skill to evaluate the stock he/she is considering. Even CFPs, CFAs, and CPAs are not experts at assessing the risk and value of companies they cover. That is why over their careers they make costly mistakes or errors of judgment and recommend stocks they should not have. So how is the average person without the training going to do better? Third, I believe that using market timing or relative strength analysis with ETFs is a solid, risk-averse way to invest and trade. I’ve written a book on each of these subjects with complete information, aimed at self-directed investors who can consider the strategies I recommend. In my lastest book, Buy DON’T Hold, I provide a strategy with specific rules

for investing in a portfolio of ETFs that takes the emotion out of the equation. I also have a website, www.buydonthold. com, that supports the book and provides a weekly report on the strategy free of charge. I’m also a big user of charting and technical analysis. Because of these reasons, I feel that the most viable investing method is to use a mechanical, nonemotional approach. By using a specific time-tested strategy (as delineated in my books or one developed by the investor) with a handful of technical indicators, investors can limit their risk and protect their principal. The key to successful long-term investing is to protect your principal from devastating bear markets. That can be accomplished using any number of simple strategies. Whether I use market timing or relative strength analysis, I know that it will definitely not do as well as the market averages during bull markets because the strategy may have premature exits and late entries. The goal is to capture the majority of the uptrends and miss most of the downtrends. Over the long haul and during down markets, these strategies will save your nest egg. So that’s why I don’t believe in buying & holding in individual stocks. It’s just too risky. People don’t understand that buying & holding is not a strategy at all; it’s just hoping for the best. If they have individual securities and use buy & hold, I wish them luck. You mentioned that you use a controlled and systematic strategy for your trading. You follow a specific plan. One of the keys to that plan is to first determine your true risk tolerance. How does somebody go about doing that and does it affect how they trade? Determining your level of risk is critical to your investing and trading success. Without developing specific parameters to protect your principal, the odds are

38 • March 2015 • Technical Analysis of Stocks & Commodities

that you may go bankrupt. The majority of the risk tolerance questionnaires used by financial advisors typically ask five to 10 questions that tend to be very weak in determining an investor’s true risk level. I found that the website www. riskprofiling.com, which uses a questionnaire that people can fill out (at no cost, to determine their own risk) is one good source. It’s a psychometric test that is closer to reality in determining risk than those tests used by most advisory, bank, and brokerage firms. In addition to taking this test, one good way to determine your risk parameter is to look back at your actions and feelings during the last big market decline that you experienced. After carefully assessing how you reacted to this market meltdown, you should have a pretty good idea of your personal loss percentage that will be acceptable in the future, allowing you to sleep at night. It could be a 10% or 20% decline, for example. If investors say to themselves that they don’t want to risk more than 10 or 15%, that is fine, but they better use stop-loss or stop-limit orders, if at all possible, to take them out of the market and not second-guess it or change those percentages as the market declines further. Unfortunately, you can’t put stop-loss orders on mutual funds. You can place them on stocks and ETFs. So if you own mutual funds, then you or your advisor will have to watch them carefully. The minute the price hits your mental stop, sell it, because you’ll be surprised and unhappy if you don’t. Think of what would happen if the market crashes and you failed to act according to your own plan. Whether someone is a trader or investor, it is critical that an exit strategy always be in place to protect principal. Most of the top traders use stop orders since they know a high percentage of their trades may go against them. The key is to take small losses, which should be counteracted by large gains in positions going their way. What indicators do you use to determine when the market is in a trend? The indicators I use are laid out in Buy—Don’t Hold (BDH) and at my website www.buydonthold.com. My goal

is to be in tune with the trend. I use four indicators to determine when to be in or out of the market, which I refer to as the BDH Dashboard. When three or more of them are on buy signals, I go long the market using the five top-ranked ETFs based on their six-month relative strength out of universe of 52 predetermined ETFs. When one or none of the indicators are on buy signals, then I sell all five ETFs. It’s as simple as that. First of all, I use the daily Nasdaq Composite index to determine the market trend. That’s the most volatile of the big three indexes and the one that usually leads the market in both directions. The first indicator used on this index is the 100-day simple moving average (SMA). When the index’s price moves above the SMA, it triggers a buy signal and vice versa. As a second indicator, I use that index with the moving average convergence/divergence (MACD). When there is a positive crossover on the MACD, that is considered a buy signal on that indicator. But if the crossover is negative, it is a sell signal. My third indicator is the American Association of Individual Investor (AAII) weekly investor sentiment survey. I use the sentiment index and look for the extremes—more than 50% bulls or less than 25% bulls. A sell signal on this indicator occurs when it reaches a level of 50% or more bullish reading and then drops below that level in a subsequent week. A buy signal occurs when it falls below 25% and then rises above that level in a subsequent week. My last indicator is the Nasdaq Summation Index (NASI). I overlay a five-day exponential moving average (EMA) on the daily price chart of the index and plot the MACD indicator. A buy signal on this indicator is generated when there is a positive daily crossover of the fiveday EMA by the index coupled with a

positive MACD crossover. They must confirm each other to be considered a signal change. On December 8, 2014, there was a sell signal on the Dashboard. So I went into 2015 with a 100% cash position. In 2014 the BDH strategy earned 13.63% while the Nasdaq Composite gained 13.4%, the S&P 500 gained 11.4%, and the Dow Jones Industrial Average gained

7.5%. And during 2014, the Dashboard was out of the market for 178 days or 48.8% of the year, greatly reducing market risk. The beauty of my system is that the Dashboard can be out of the market between 25–50% of the time during the year and still post decent risk-adjusted performance. Remember, if you’re not in the market you have no risk at that time. But that means you

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• Technical Analysis of Stocks & Commodities • 39

By using a specific time-tested strategy with a handful of technical indicators, investors can limit their risk and protect their principal.

will miss some of the upside, but that’s part of risk management. During bull markets you’re not going to capture all of the upside as the indicators need time to reverse to the upside. The best part of the Dashboard strategy is that it pays off big time in a big bear market. You’ll be out of the market and stay out until the market reverses higher. That’s the key to building wealth. We’ve had a huge bull market since March 2009. It may have potentially peaked the last week of 2014. Looking ahead to 2015, no one knows where the market will end the year. The perennial forecasters are projecting an 8–10% market advance, as they do almost every year. One positive for 2015 is that it is the third year of the Presidential election cycle, which has had a positive historical track record. Another positive is that years ending in “5” have had a good track record as well. These positives are nice to keep in mind, but the question is whether they will kick in this year. And no one knows the answer to that at year-end 2014.

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You mentioned a few exchange traded funds. Why do you prefer trading them to individual stocks? Stocks are dangerous by themselves. If you pick a stock that is a winner, then that’s tremendous. But the odds are against you. For example, there was a study done on over 8,000 stocks from 1983–2006. They looked at the stocks on the Nasdaq Composite, the American Stock Exchange, and the New York Stock Exchange, including delisted stocks, and found that over the total life of that period, only 25% of the stocks provided all of the return, and 75% did not participate in the uptrend. Even in big bull markets there are many stocks that have negative performance. That’s why it’s difficult to pick stocks individually. Mutual funds really are not the way to go either because of their high internal expenses—about 1.23% for equity funds—and their endof-day-pricing. That’s why I love to use ETFs. They’re passive indexes, low cost, transparent, very liquid, and can be traded during the day. The nice thing is that you have a wide choice of ETFs in all asset classes. They don’t usually declare capital gains because they’re not actively trading. Another positive for ETFs is you can invest in an inverse fund. You can buy an inverse fund of an index and go long. There are over 1,700 ETFs to choose from, and the value of the total ETF world is $2 trillion, so they have really grown in the past couple of years. They’re going to knock out mutual funds at some point. It may take 10 or 15 years but I think it’ll happen. ETFs are a great product. They’re much better than mutual funds. In the past year 79% of the active managers didn’t even beat their own benchmarks, according to Morningstar, and interestingly, only 13% of those who were tracking

40 • March 2015 • Technical Analysis of Stocks & Commodities

large-cap stocks beat their benchmark this year. And anyone who holds them is paying those internal fees all the time. So I use ETFs with my strategies. Then of course with ETFs, you have the option of being able to rotate among sectors. Yes, my BDH strategy rotates into ETFs in different sectors. I use relative strength to identify the strongest sectors using a preselected universe of 52 ETFs, which are listed on my website and ranked each week. Each week they are ranked based on their six-month price performance, and the five strongest ones are purchased and held until the Dashboard has a sell signal, or their individual stop-limit order is hit, or they drop below rank 20, whichever criteria is met first. Each week I look at the four indicators for any signals—buy or sell. When there is a majority in one direction, then that results in a Dashboard buy or sell signal. Over time, I expected to only get three or four Dashboard signals a year, but in 2014 there were five buy and five sell signals because of the market choppiness. In a nice, trending market, you will have fewer signals. There really is no perfect indicator or trading system. Absolutely correct. The BDH Dashboard is not a perfect system, but it hopefully will capture most of the gains while minimizing the losses. There is no perfect system, and if you were talented enough to develop one, it will probably decay over time because the markets change. Speaking of changing markets, are there any significant changes that you have noticed in the markets of late compared to what they were a few decades ago? Yes, there have been many significant

changes in the last decade. These include lower trading commissions; availability of free, powerful trading platforms as well as charting and backtesting software; the global nature of the markets; the impact of the Federal Reserve and foreign central banks; and information explosion. Today, global political, economic, banking, and financial events filter their way back to the US instantly and impact our markets. This was certainly not the case 10 years ago. The social media explosion has also had its impact on certain stocks, as true and untrue stories circulate around the world in seconds. Another major change has been the commission structure reduction. More than a decade ago I was paying $45 to trade and a few hundred dollars a month for real-time data. Now I’m paying about half a cent in one of my brokerage accounts, and with another brokerage account I’m paying $5 to trade any amount of shares. Most of the large firms, such as E*Trade, Fidelity, and TD Ameritrade have advanced trading software and platforms coupled with real-time data for no charge with certain account minimums, and they keep updating and improving their offerings. The availability of powerful trading and backtesting software has given traders and investors the ability to analyze

their ideas and strategies in seconds. Ten years ago this capability was just in its infancy. You said you have 52 ETFs listed on your website. How did you select them? Anyone can see these ETFs by going to my website or to one of my links at www. etfscreen.com/buydonthold. They’re broad-based indexes representing seven categories: fixed income, commodities, international, sectors, styles, currencies, and inverse funds. Most have high daily volume and are liquid with low bid–ask spreads. I select five of the strongest ETFs and hold them until they have a sell signal based on a stop limit or a dashboard sell or if they drop below rank 20 out of 52. Any last thoughts? Investing successfully is all about protecting your principal from future devastating bear markets. The next few decades will most likely not match the performance of the 1950s, 1980s, and 1990s for many reasons. Therefore, investors need another way of investing to eliminate all the noise and not concentrate on what others are saying or what their opinions are about the future trend of the market. If you look at the forecasts of market participants, es-

pecially many financial advisors, pundits on Wall Street, or economists, you’ll find they’re usually completely wrong—their predictions will tend to head in the opposite direction. Take the forecasts from prominent prognosticators for 2014 as an example. Most economists thought that interest rates were going to go up, but that didn’t happen. They thought the price of oil would go up but that clearly didn’t happen. They thought the dollar was going to go down, but it went up. So why pay attention to someone’s forecast? It’s not going to help you make money. Thus, it is important to use a rulebased, logical approach such as relative strength to have the odds in your favor. Anyone who uses my website has free access to an ETF relative strength strategy. There’s no work for anyone to do to gather updated information, as I do all the work and provide the links. They can view the strategy and the weekly update of the Dashboard indicators and follow it if they want to. The reason I developed the blog was to back up my book, and provide self-directed investors with a conservative investing approach with proper risk safeguards. The question is, “When will the next bear market occur?” No one knows, but the Dashboard will be there to help determine when to sell—not at the top, but close to it. That’s worth its weight in gold.

Further reading

Masonson, Leslie N. [2010]. Buy, DON’T Hold—Investing with ETFs Using Relative Strength To Increase Returns With Less Risk, FT Press. _____ [2011]. All About MARKET TIMING: The Easy Way To Get Started, 2d ed., McGraw-Hill. _____ [2011]. Profiting From ETF Rotation Strategies In Turbulent Markets (Kindle edition only), FT Press. _____ [2014]. “StockCharts University,” Quick-Scan, Technical Analysis of Stocks & Commodities, Volume 32: April. • www.buydonthold.com, lesmasonson@ yahoo.com

“If elected, I promise to do my darndest to keep money in politics!” March 2015

• Technical Analysis of Stocks & Commodities • 41

Explore Your Options Got a question about options? Tom Gentile started his trading career on the floor of the American Stock Exchange in 1994. He has appeared on many financial TV and radio shows, as well as hosting a weekly talk show himself, and has co-authored many books on the markets. He can be found at www.tomgentile.com. To submit a question for Tom Gentile, post it to our website at http://Message-Boards.Traders. com. Answers will be posted there, and selected questions will appear in a future issue of S&C. Tom Gentile

PROTECTING YOUR SMALLER STOCK PORTFOLIO How do I hedge 10 shares of Google? Years ago, my answer would have been, “Get 90 more shares, then we can talk.” But as of last year, that all changed with the introduction of mini options. It has now been a year since this product was introduced, and I typically wait a year before trading anything new. Let’s visit this “small” section of options to see if it might be a good fit for the smaller trader. In March 2014, the CBOE launched a new product for the smaller investor looking to hedge odd-lot securities called mini options. What are they, how have they performed during the past year, and who is most likely to benefit from using these options? Each regular-sized equity option contract gives the buyer the right, but not the obligation, to buy 100 shares of the underlying asset at a set price for a set time. Regular options have many strike prices above and below the stock price. Regular options could have as little as one week to expiration, or as long as a few years. A mini option represents 1/10th of the value of a regular-sized option. Thus, a mini option contract is good for 10 shares of stock and is in many ways similar to the standardized options. Before you go out and analyze your odd-lot portfolio on every stock that you might own, mini options have most of their volume in Apple Inc. (AAPL), Amazon.com Inc. (AMZN), Google Inc.

(GOOG), SPDR Gold Shares (GLD), and SPDR S&P 500 ETF (SPY). These mini options, like the standardized ones, offer various strike prices and the same expiration dates. In this regard, they are similar to their bigger brother, but smaller. So right off the top of my head, who is the trader or investor that’s best suited to benefit from mini options? The odd-lot investor! This is the person like my motherin-law (let’s call her MIL) who buys 10 shares of GOOG, because that’s all she wants to buy in her portfolio. She likes to buy and hold GOOG a month before earnings and then sell after earnings. At today’s price, 10 shares of GOOG is valued at more than $5,000. That might not be much to you, but to her it represents a lot of money. With mini options, she now has several strategies to hedge this particular position if she intends on keeping it longer than a few days. These would include:

and simultaneously sell one mini option contract with one month to expiration on GOOG at $500, and collect premium for the sale, which at the time of this writing, was $30. She now has $30 of protection for her GOOG shares, and even if the stock were to stay at $500, she keeps the amount of money collected at expiration. Bad news is that she has capped the reward to the amount of premium collected, so if at earnings, GOOG jumps to $600 a share, she is obligated to sell the stock at $500. Keep in mind that the chart in Figure 1 shows 100 shares of GOOG and one

• Covered call options—MIL could purchase her 10 shares of GOOG at $500

Figure 1: Covered Call Options. This strategy gives you the protection but caps the reward to the amount of premium collected.

42 • March 2015 • Technical Analysis of Stocks & Commodities

Explore Your Options

full-size option contract; the mini is 1/10th the cost and risk. • Married put option—In this case, MIL could protect her 10 shares of GOOG with a mini option purchase of GOOG puts. If she bought one mini option with one month to expiration at a strike price of $500, she would end up paying a little less than 10 points of protection for her GOOG stock. This is to protect $5,000 of stock for 30 days. The good news is twofold: If GOOG has good earnings and the stock jumps to $600, she gains 100 points on the stock, and even though the put protection cost less than $10, she still nets out 90 points of profit. If the company’s earnings aren’t up to expectations and the stock falls by 100 points, the put she bought gives her the right to sell GOOG at $500. In this case, protection that cost 10 points saves her 100 points if the stock drops below $500. The drawback here would be if GOOG were to stay in a sideways range. This then costs her unneeded protection, but still gives

peace of mind. You can see the risk graphs with the full option contracts in Figure 2, so deduct 90% off the prices to get an idea of what your costs and risks are with 10 shares of stock and a mini option. • Collarstrategy— This involves a combination of the two strategies discussed— buying the stock, Figure 2: Married put options. This strategy gives you the protection and the buying a put, and possibility of higher rewards. The problem would be if the stock moved sideways. selling a call simultaneously. This strategy takes but you don’t hear about them much. If the positives and negatives of the two you’re a small trader, don’t let this disstrategies, and it protects the stock, courage you. Minis are a great way to but the rewards are minimal. start learning how to trade options. Good trading! Minis started out with a lot of fanfare,

FUTURES FOR YOU GARNER / FUTURES FOR YOU Continued from page 23

(selling long futures positions) due to a lack of conviction or funding, prices were forced lower in a dramatic nature. The panic was real, and it resonated

into the financial markets, causing junk bonds and energy stocks to plummet. Oftentimes, human emotion interferes with natural market fundamentals. In such times, prices can overshoot equilibrium, or even logical, levels. Eventually, the panic subsides and prices revert to a March 2015

more realistic level; in my view, this is a likely scenario in 2015. ‡QST Desktop (Quick Screen Trading)

• Technical Analysis of Stocks & Commodities • 43

product review

OptionStrategist.com Part 2 McMILLAN ANALYSIS CORP. PO Box 1323 Morristown, NJ 07962–1323 Phone: 800 724-1817 Fax: 973 328-1303 Email: [email protected] Website: www.optionstrategist.com Price: Various products and services are available. See website for details.

H

by S&C Staff ere in the second part of this twopart review, we’ll discuss The Option Strategist newsletter and other products and services offered by OptionStrategist.com.

Option strategist

newsletter The newsletter comes out biweekly and has an update called the hotline in between those weeks. It is typically 12 pages long and contains a wealth of information. It starts out with educational material such as an explanation of a specific strategy. There will often be examples to help explain the item under discussion. The newsletter has specific areas it covers in every publication. Following the educational/informative feature article is a table of follow-up actions as required for each open position. Next is a section titled sentiment indicators in which a stock market outlook is given based on various technical indicators, followed by sections on index options & volatility skewing, extremes in sentiment, and put–call ratios (Figure 1). Specific trading recommendations may or may not be given. Various relevant charts are included, followed by a discussion of the current state of the volatility in derivatives markets.

Software products

OptionStrategist.com offers five different software packages. We’ll look at two of them. The first one is The Expected Return Calculator. What it attempts to do is tell you, 44 • March 2015 • Technical Analysis of Stocks & Commodities

put–call ratio charts

Figure 1: put–call ratio charts. When new buy signals are generated from the put–call ratio extremes, a chart is provided in OptionStrtegist.com.

over a large number of trades, what your expected profit or loss might be for an option position. The key statement here is a large number of trades. Any one trade might be a profit or a loss. It is only after a number of trades that you can reasonably talk about average profit or loss. There are three inputs to the calculation. The first, and arguably the most important, is the historical volatility of the underlying. Volatility is free on a weekly basis from OptionStrategist.com. Follow the path Products→Analysis Tools→Free Analysis Tools→Data or go to http:// www.optionstrategist.com/calculators/ free-volatility-data. What is impressive about the data is that the table includes futures, indexes, and stocks. The use of percentage in conjunction with the composite implied volatility is the type of sophisticated approach typical of OptionStrategist.com because you want to know where implied volatility is relative to prior calculations of implied volatility. If you don’t want to wait a week for volatility calculations, you can subscribe to the Strategy Zone, which supplies the data on a daily basis, but it also includes much more, such as trading candidates for covered writes; naked put sales; straddle buys; and calendar spreads. A wide array of volatility data is also included, along with a daily midday market commentary; more than 200

put–call ratio charts; volatility charts; a probability calculator; and back issues of McMillan’s newsletters. The best thing is that all of this is in the Strategy Zone that goes for $195/year if you sign up for a yearly subscription with autorenewal. The expected return calculator has been set up to require manual inputs, and there are several sources of data that are free and readily available. There is no datafeed service you need to purchase. When you open the expected return calculator, you are presented with a screen

similar to what you see in Figure 2 that allows you to make inputs. Under the label securities are a couple of lines— one for the underlying and one for the option. The volatility on the line for the underlying is historical volatility. The next line below is for the option, and the volatility needed here is the implied volatility. The option line lets you specify a series of options so you can see what would happen with spreads. In this example, a -1 has been input for the quantity of options to identify selling the option. A dropdown menu lets

Figure 2: Expected Return Calculator. Here you see the editor tab. This screen is used to provide inputs for the option position you want evaluated. At the top are the points in time you want to determine your potential profit/loss. Below that is the securities information. You can input either put or call and add several more options so you can evaluate spreads. Historical volatility is used for the underlying line, and implied volatility is used for the option line. March 2015

• Technical Analysis of Stocks & Commodities • 45

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FIGURE 3: Expected Return Calculator Plot. This is a standard option profit/loss graph. Assuming a lognormal distribution of prices and using volatility, this screen lets the calculator estimate profit/loss. The black line corresponds to the option expiration date, while the blue and purple lines correspond to the two data points from your input.

Different option trading strategies are covered for novice and intermediate-level option traders. you input several options, thus allowing spreads to be created. After inputting the data, you can choose the plot tab from the upper left-hand corner. This will plot the familiar option profit/loss chart similar to what you see in Figure 3. In the upper left-hand corner is a legend that changes as you move your cursor to different underlying prices. If you are looking for another way to arrive at implied volatility other than through the newsletter, OptionStrategist. com also offers the Option Calculator 2.0 (Figure 4). The inputs are straightforward, with the primary ones being strike price, stock price, and stock price historical volatility. The calculator uses a BlackScholes model to calculate implied volatility. It will also show you the option greeks for a large combination of stock and strike prices.

Educational materials

One of the offerings by OptionStrategist. com is a home study video package that 46 • March 2015 • Technical Analysis of Stocks & Commodities

consists of 16 seminars by Lawrence McMillan. The seminars cover novice, intermediate, and advanced option trading. One of the approaches that McMillan uses is to give examples, and when possible he provides charts or diagrams to keep the material interesting while still being highly informative. Different option trading strategies are covered for novice and intermediate-level option traders.

Summary

OptionStrategist.com consists of a wealth of option-related information. Besides offering ongoing educational material through The Option Strategist newsletter, there is a wealth of educational material. There are over 10 different video packages and McMillan has also authored several books. Software is available that lets you input your own data so you can see the effect of changes. All in all, it’s an impressive set Continued on page 54

For this month’s Traders’ Tips, the focus is John Ehlers & Ric Way’s article in this issue, “Trading System Design: A Statistical Approach.” Here, we present the March 2015 Traders’ Tips code with possible implementations in various software. Code in EasyLanguage is already provided by Ehlers & Way in their article, which S&C subscribers will find in the Subscriber Area of our website:

• Traders.com  Home–S&C Magazine  S&C Article Code

The code for the Traders’ Tips section is posted here:

• Traders.com  Home–S&C Magazine  Traders’ Tips

(Or from Traders.com, scroll down to the current articles section and click on the Traders’ Tips tab.) The Traders’ Tips section is provided to help the reader implement a selected technique from an article in this issue or another recent issue. The entries here are contributed by software developers or programmers for software that is capable of customization.

F TRADESTATION: MARCH 2015 TRADERS’ TIPS CODE In “Trading System Design: A Statistical Approach” in this issue, authors John Ehlers & Ric Way outline a procedure for the development of trading systems using a statistical approach. In the article, they create a set of data that they analyze using Microsoft Excel spreadsheet software. They have provided TradeStation EasyLanguage code for an indicator to help create the data for analysis, as well as a simple test strategy to demonstrate the process. To download the EasyLanguage code, please visit our TradeStation and EasyLanguage support forum. The code for this article can be found here: http://www.tradestation.com/ TASC-2015. The ELD filename is “_TASC_StatisticalApproach.ELD.” For more information about EasyLanguage in general, please see http://www.tradestation.com/EL-FAQ. A sample chart is shown in Figure 1.

Figure 1: TRADESTATION. Here is an example of a simple stochastic system applied to a daily chart of the emini S&P 500 (ES), based on John Ehlers & Ric Way’s article in this issue.

The study contains formula parameters that may be configured through the edit chart window (right-click on the chart and select “edit chart”). A sample chart is shown in Figure 2. To discuss this study or download a complete copy of the formula code, please visit the EFS Library Discussion Board forum under the forums link from the support menu at www.esignal.com or visit our EFS KnowledgeBase at http://www.esignal.com/support/kb/efs/. The eSignal formula script (EFS) is also available for copying & pasting from the Stocks & Commodities website at www.traders.com in the Traders’ Tips area. —Eric Lippert eSignal, an Interactive Data company 800 779-6555, www.eSignal.com

This article is for informational purposes. No type of trading or investment recommendation, advice, or strategy is being made, given, or in any manner provided by TradeStation Securities or its affiliates. —Doug McCrary TradeStation Securities, Inc. www.TradeStation.com

F eSIGNAL: MARCH 2015 TRADERS’ TIPS CODE For this month’s Traders’ Tip, we’re providing the formula SimpleStocTrSystem.efs based on the formula described in John Ehlers & Ric Way’s article in this issue, “Trading System Design: A Statistical Approach.”

Figure 2: eSIGNAL. Here is an example of the simple stochastic system on a chart of the S&P 500 emini futures contract (ES). March 2015 • Technical Analysis of

Stocks & Commodities • 47

Highest HiC = Highest.Series(Close, StocLength); Lowest LoC = Lowest.Series(Close, StocLength); DataSeries Stoc = (Close - LoC) / (HiC - LoC); for(int bar = GetTradingLoopStartBar(1); bar < Bars. Count; bar++) { if (IsLastPositionActive) { Position p = LastPosition; if ( bar+1 - p.EntryBar >= TradeLength ) SellAtMarket( bar+1, p, “Timed” ); else if( Low[bar] < p.EntryPrice*(1.0 - PctLoss /100d) ) SellAtMarket(bar+1, p, “Stop”); Figure 3: WEALTH-LAB. This chart shows the US market bubble of the 2010s on a monthly chart of the S&P 500 index (^GSPC).

F WEALTH-LAB: MARCH 2015 TRADERS’ TIPS CODE In their article in this issue, “Trading System Design: A Statistical Approach,” authors John Ehlers & Ric Way outline a statistically valid procedure for the successful development of trading systems, providing a testbed for assessing whether the price will increase or decrease over n bars after an event. From our point of view, it might be optimal to prove the conclusion regarding the robustness of the example system by using a different subset of data that includes a bear market, given that the in-sample period of 10 years used to optimize the system on was a strong bull market (Figure 3). The code for Wealth-Lab based on Ehlers & Way's code follows: Wealth-Lab 6 strategy code (C#) using System; using System.Collections.Generic; using System.Text; using System.Drawing; using WealthLab; using WealthLab.Indicators; namespace WealthLab.Strategies { public class EhlersMar2015 : WealthScript { private StrategyParameter paramStoc; private StrategyParameter paramThresh; private StrategyParameter paramLength; private StrategyParameter paramLoss; public EhlersMar2015() { paramStoc = CreateParameter(“StocLength”, 8, 1, 100, 1); paramThresh = CreateParameter(“Threshold”, 0.3, 0.1, 0.9, 0.1); paramLength = CreateParameter(“TradeLength”, 14, 1, 50, 1); paramLoss = CreateParameter(“PctLoss”, 3.8, 0.5, 15.0, 0.5); } protected override void Execute() { int StocLength = paramStoc.ValueInt, TradeLength = paramStoc.ValueInt; double Threshold = paramThresh.Value, PctLoss = paramLoss.Value;

48 • March 2015 • Technical Analysis of Stocks & Commodities

} else { if( CrossOver( bar, Stoc, Threshold ) ) BuyAtMarket( bar+1 ); } } } } }

—Eugene, Wealth-Lab team MS123, LLC www.wealth-lab.com

F NEUROSHELL TRADER: MARCH 2015 TRADERS’ TIPS CODE The simple stochastic trading system described by John Ehlers & Ric Way in their article in this issue, “Trading System Design: A Statistical Approach,” can be easily implemented with a few of NeuroShell Trader’s 800+ indicators. Simply select “New Trading Strategy” from the insert menu and enter the following in the appropriate locations of the Trading Strategy Wizard: BUY LONG CONDITIONS: CrossBelow(Stoch%K(High,Low, Close,5),30) LONG TRAILING STOP:

PriceFloor%(Trading Strategy,3.8)

SELL LONG CONDITIONS: BarsSinceFill>=X(Trading Strategy,14)

If you have NeuroShell Trader Professional, you can also choose whether the parameters should be optimized. After backtesting the trading strategy, use the detailed analysis button to view the backtest and trade-by-trade statistics for the strategy. You can also create another trading strategy using the center of gravity indicator referenced in the article along with a one-period lag of the same indicator called the trigger. Both indicators are part of Ehlers’ Cybernetic Analysis add-on for NeuroShell Trader. BUY LONG CONDITIONS: Center of Gravity > Center of Gravity Trigger SELL LONG CONDITIONS: Center of Gravity < Center of Gravity Trigger

Figure 4: NEUROSHELL TRADER. This NeuroShell Trader chart displays the simple stochastic trading system as well as a trading system based on Ehlers’ center of gravity indicator.

Users of NeuroShell Trader can go to the Stocks & Comsection of the NeuroShell Trader free technical support website to download a copy of this or any previous Traders’ Tips. A sample chart is shown in Figure 4. modities

—Marge Sherald, Ward Systems Group, Inc. 301 662-7950, [email protected] www.neuroshell.com

F AIQ: MARCH 2015 TRADERS’ TIPS CODE The AIQ code based on John Ehlers & Ric Way’s article in this issue, “Trading System Design: A Statistical Approach,” is provided at: • www.TradersEdgeSystems.com/traderstips.htm !TRADING SYSTEM DESIGN: A STATISTICAL APPROACH !Author: John Ehlers, TASC March 2015 !Coded by: Richard Denning 1/12/2015 !www.TradersEdgeSystems.com !STOCHASTIC TRADING SYSTEM FROM ARTICLE: !INPUTS: StocLength is 8. Threshold is 0.3. TradeLength is 14. PctLoss is 3.8. !SYSTEM CODE: HiC is Highresult([Close], StocLength, 0). LoC is Lowresult([Close], StocLength, 0). Stoc is ([Close] - LoC) / (HiC - LoC). Buy if Stoc < Threshold and valrule(Stoc >= Threshold,1). PD is {position days}. PEP is {position entry price}. ExitLong if PD - 1 >= TradeLength or [Low] < PEP*(1-PctLoss/100).

Figure 5: AIQ. Here is the strategy’s EDS backtest summary for trading the NASDAQ 100 list of stocks over the period from 2009 through 1/13/2015.

Figure 5 shows the EDS backtest summary for trading the NASDAQ 100 list of stocks using the authors’ stochastic system over the period 2009 through 1/13/2015. —Richard Denning [email protected] for AIQ Systems

F TRADERSSTUDIO: MARCH 2015 TRADERS’ TIPS CODE The TradersStudio code for John Ehlers & Ric Way’s article in this issue, “Trading System Design: A Statistical Approach” can be found at: • www.TradersEdgeSystems.com/traderstips.htm • www.TradersStudio.com → Traders Resources → Traders Tips

The following code file is provided in the download: • System: EHLERS_SYSTEMS: A long-only system that uses daily data and the stochastic indicator for entries.

Figure 6 shows an equity curve for this stochastic system trading one contract per trade of the S&P 500 full-sized futures contract from 1982 to 2014 using data from Pinnacle Data Corp. Slippage & commission of $100 per round-turn trade were subtracted from each trade. 'TRADING SYSTEM DESIGN: A STATISTICAL APPROACH 'Author: John Ehlers, TASC March 2015 'Coded by: Richard Denning 1/12/2015 'www.TradersEdgeSystems.com 'Stochastic trading system from article: Sub EHLERS_SYSTEMS(StocLength, Threshold, TradeLength, PctLoss) Dim HiC As BarArray March 2015 • Technical Analysis of

Stocks & Commodities • 49

Figure 7: NINJATRADER. This screenshot shows the SimpleStochastic strategy applied to a daily emini S&P futures continuous chart in NinjaTrader. Figure 6: TRADERSSTUDIO. Here is a sample equity curve trading the stochastic system one contract per trade of the S&P 500 full-sized futures contract from 1982 to 2014. Dim LoC As BarArray Dim Stoc As BarArray If BarNumber=FirstBar Then 'StocLength = 8 'Threshold = .3 'TradeLength = 14 'PctLoss = 3.8 HiC = 0 LoC = 0 Stoc = 0 End If

menu Tools  Edit NinjaScript  Strategy from within the NinjaTrader Control Center window and selecting the SimpleStochastic file. NinjaScript uses compiled DLLs that run native, not interpreted, which provides you with the highest performance possible. A sample chart implementing the strategy is shown in Figure 7. —Raymond Deux and Dave Ingram NinjaTrader, LLC www.ninjatrader.com

HiC = Highest(Close, StocLength, 0) LoC = Lowest(Close, StocLength, 0) Stoc = (Close - LoC) / (HiC - LoC) If CrossesUnder(Stoc, Threshold) Then Buy(“LE”, 1, 0, Market, Day) End If If BarsSinceEntry -1>= TradeLength Then ExitLong(“LX_time”, “”, 1, 0, Market, Day) End If If Low < EntryPrice*(1 - PctLoss /100) Then ExitLong(“LX_loss”, “”, 1, 0, Market, Day) End If End Sub

—Richard Denning [email protected] for TradersStudio

F NINJATRADER: MARCH 2015 TRADERS’ TIPS CODE The SimpleStochastic strategy presented in John Ehlers & Ric Way’s article in this issue, “Trading System Design: A Statistical Approach,” has been made available for download at www.ninjatrader.com/SC/March2015SC.zip. Once it has been downloaded, from within the NinjaTrader Control Center window, select the menu File  Utilities  Import NinjaScript and select the downloaded file. This file is for NinjaTrader version 7 or greater. You can review the strategy source code by selecting the 50 • March 2015 • Technical Analysis of Stocks & Commodities

DETAIL FROM Figure 7

F UPDATA: MARCH 2015 TRADERS’ TIPS CODE Our Traders’ Tip for this month is based on the article by John Ehlers & Ric Way in this issue, “Trading System Design: A Statistical Approach.” In it, the authors develop a statistical methodology for the predictability of an event—in this case, the crossing of a stochastic threshold level. By offsetting entry times and measuring the effect this has on overall profitability in the intervening period given price direction, a probability distribution function can be created. The Updata code based on the article is in the Updata Library and may be downloaded by clicking the custom menu and system library. Those who cannot access the library due to firewall issues may paste the code shown here into the Updata custom editor and save it. A sample chart implementation is shown in Figure 8. 'AStochasticSystem DISPLAYSTYLE 2LINES INDICATORTYPE TOOL COLOUR RGB(0,0,200) COLOUR2 RGB(0,0,200) PARAMETER “Stochastic Period” #STOCHPERIOD=14 PARAMETER “Threshold” @THRESHOLD=0.3 PARAMETER “Hold Period” #HOLDPERIOD=14 PARAMETER “Stop Loss %” @STOP=3.8 NAME “STOCHASTIC SYSTEM [“ #STOCHPERIOD “|” @ THRESHOLD “|” #HOLDPERIOD “|” @STOP “]” “” @UPPER=0

FIGURE 8: UPDATA. Here is an example chart of the simple stochastic entry system as applied to the cash S&P 500 index.

@LOWER=0 @STOCH=0 @ENTRYPRICE=0 FOR #CURDATE=#STOCHPERIOD TO #LASTDATE @UPPER=PHIGH(CLOSE,#STOCHPERIOD) @LOWER=PLOW(CLOSE,#STOCHPERIOD) @STOCH=(CLOSE-@LOWER)/(@UPPER-@LOWER) 'STOCHASTIC ENTRY IF HIST(@STOCH<@THRESHOLD,1) AND ORDERISOPEN=0 BUY OPEN @ENTRYPRICE=OPEN ENDIF 'TIME EXIT IF ORDEROPENFOR>=#HOLDPERIOD SELL CLOSE ENDIF '% STOP EXIT IF HIST(LOW<@ENTRYPRICE*(1-(@STOP/100)),1) SELL OPEN ENDIF @PLOT=@UPPER @PLOT2=@LOWER NEXT

—Updata support team [email protected] www.updata.co.uk

F AMIBROKER: MARCH 2015 TRADERS’ TIPS CODE In “Trading System Design: A Statistical Approach” in this issue, authors John Ehlers & Ric Way present a way to find out whether signals generated by a given indicator have a statistical edge. Listing 1 presents AmiBroker Formula Language (AFL) code that produces a profitability distribution chart for a simple statistic crossover system. One can replace the event variable with any other system to test its statistical edge. When code is used in AmiBroker’s exploration mode, it produces an extra

Figure 9: AMIBROKER. Here is an AmiBroker exploration chart showing a sample profitability distribution for the stochastic indicator crossing under 0.2 using hourly SPY data. Note that hourly data and a significantly larger dataset produces a distribution that more closely resembles a classic bell curve than the chart that was shown in Ehlers & Way’s article.

tab(s) with a profitability distribution chart for each symbol separately. To use the formula, type the code into the formula editor and press send to analysis to perform an exploration. As you can see from Figure 9, using more data (in this case, hourly) produces a smoother chart than what was presented in the article. LISTING 1 Range = 10; HiC = HHV( Close, Range ); LoC = LLV( Close, Range ); Stoc = ( Close - LoC ) / ( HiC - LoC ); Lookback = Range - 1; Event = Ref( Cross( Stoc, 0.2 ), -Lookback ); PctGainRange = 3; // defines % gain range for X axis FuturePrice = ROC( Close, Lookback ); // keep values in range FuturePrice = Min( PctGainRange, Max( -PctGainRange, FuturePrice ) ); // map range to to 0..100 FuturePrice = Round( 100 * ( FuturePrice + PctGainRange )/ ( 2 * PctGainRange ) ); PredictBin = 0; for( i = 0; i < BarCount AND BarCount > 100; i++ ) { if( Event[ i ] ) PredictBin[ FuturePrice[ i ] ]++; } chartname = "Probability distribution " + Name(); XYChartSetAxis(chartname, "[%gain]", "[n]" ); for( i = 0; i < BarCount AND i <= 100; i++ ) { XYChartAddPoint( chartname, "", ( i * 2 * PctGainRange / 100 - PctGainRange ), PredictBin[ i ], colorGreen ); }

—Tomasz Janeczko, AmiBroker.com www.amibroker.com March 2015 • Technical Analysis of

Stocks & Commodities • 51

FIGURE 10: EXCEL, Event testing controls and trading controls. This shows the specification for one stochastic event definition on the left under the heading “predictive event testing controls.”

F MICROSOFT EXCEL: MARCH 2015 TRADERS’ TIPS CODE In their article in this issue, “Trading System Design: A Statistical Approach,” authors John Ehlers & Ric Way show us a statistical approach to determine if an event we can define to a computer has any value as a future price predictor. Once we have determined the size and shape of such an event, we can build trading rules around the event and construct a system to follow those rules. In the article, the authors use a simple stochastic crossunder as the event and look ahead a number of bars to determine a percentage change after the event. Run this logic against 10 or more years of historical data, accumulate the events you find as well as the percent change values associated with the events, and you can then use a center of gravity (weighted average) calculation to assess the predictive power of the event. The premise here is that the

more positive the CG value, the better your event is likely to be for trading long positions. Figure 10 shows the specification for one such stochastic event definition on the left under the heading “predictive event testing controls.” The corresponding “event count by price gains” chart with a marker for the calculated center of gravity is shown under the price chart. Controls specifying a slightly different size and shape of our event to be used in the simplified trading system appear under the heading “trading system controls.” A summary of the trading results for this control set can be found in the lower-left corner. Calculations for predictive event testing and center of gravity determination can be found in the columns to the right of the price chart, as shown in Figure 11. Figure 12 shows the calculations for the trading system. These are located in columns yet farther to the right of those

FIGURE 11: EXCEL, Predictive Event Computations. Calculations for predictive event testing and center of gravity determination can be found in the columns to the right of the price chart.

52 • March 2015 • Technical Analysis of Stocks & Commodities

shown in Figure 11. As described in the article, selecting the correct combination of specifications for our predictive event can be a trial & error process. In the spreadsheet I am providing, I have included a rudimentary mechanism to assist with the tedious business of evaluating an array of event parameter choices to find the combination that generates the most promising FIGURE 12: EXCEL, Trading decisions. This shows the calculations for the trading system. center of gravity value. Figure 13 shows this mechanism on the PredictiveEventScenarioTester tab of the workbook. Filling in the values in blue defines the envelope of events we want to look at. In this case, we are set up to look at all stochastic lookback lengths from eight to 18 bars; use threshold values from 0.1 to 0.35 in steps of 0.05; and try lookahead periods from five to 18 bars, inclusive. When you click the 13: EXCEL, Finding a “Good” Set of Event Parameters. On the PredictiveEventScenarioTester tab of the workrun button, the VBA code FIGURE book, I have included a rudimentary mechanism to assist with evaluating an array of event parameter choices to find the combination behind the button cycles that generates the most promising center of gravity value. through all possible combinations of these values one at a time. The results area keeps track of the looping process. The results are sorted from highest to lowest on the center of gravity value, and the three control values for this “best” setting are used to set the CalculationsAndCharts (Figure 10) predictive event controls. The TradingSystem­ Evaluator tab shown in Figure 14 serves the same FIGURE 14: EXCEL, Finding a “Good” Set of Event Parameters (Cont’d.). The TradingSystemEvaluator tab serves purpose for evaluating the same purpose for evaluating sets of trading system controls. Here, control values from the best equity value row are used to sets of trading system set the CalculationsAndCharts trading system controls. controls. Control values from the best equity value row are used to set the Calcula- fications as being their best choice. I think one of the reasons tionsAndCharts trading system controls. for this difference can be found in the trading summary in Trading results for a given scenario can be seen on the the bottom left of Figure 10: Not every event/entry signal transaction summary tab shown in Figure 15. participates in a trade. Many are ignored because a trade is You will find that the automated event evaluator and the already in progress. So while each of these “ignored” events trading evaluator usually come up with different event speci- contributed to a center of gravity computation, they do not March 2015 • Technical Analysis of

Stocks & Commodities • 53

contribute independently to the equity value. Moreover, stoploss processing of a trade may prevent an event entry from reaching the potential contribution that was recognized in the event evaluator CG calculation. The spreadsheet file for this Traders’ Tip (EventPredictabilityTester.xlsm) can be downloaded from www.traders. com in the Traders’ Tips area. To successfully download it, follow these steps:

• Right-click on the Excel file link (EventPredictabilityTester. xlsm), then • Select “save as” or “save target as” to place a copy of the spreadsheet file on your hard drive. —Ron McAllister Excel and VBA programmer [email protected]

FIGURE 15: EXCEL, Trade Details. Trading results for a given scenario can be seen on the transaction summary tab.

PRODuCT REvIEW / OPTIONSTRATEGIST.COM Continued from page 46

of information and tools to make you a better option trader.

FURTHER READiNg

Gopalakrishnan, Jayanthi [2002]. “Options Volatility With Lawrence McMillan,” interview, Technical Analysis of StockS & commoditieS, Volume 20: February. S&C Staff [2015]. “OptionStrategist. com (Part 1),” product review, Technical Analysis of StockS & commoditieS, Volume 33: February. ‡OptionStrategist (McMillan Analysis Corp.) ‡See Editorial Resource Index

FIGURE 4: OPTION CALCULATOR 2.0. Inputs are made to the top two lines, with the result being a matrix of premium prices for put & call strike prices and stock price combinations. If you click on any one cell of the matrix, the greeks shown below will change. The implied window (seen as the window overlaying the lower two thirds of this screen capture) is used to calculate implied volatilities. A series of six input rectangles are there for you to input premium prices for various strikes depending on whether you have chosen the call or put radial in the upper left. After making the inputs, the matrix is populated with implied volatilities and the greeks.

54 • March 2015 • Technical Analysis of Stocks & Commodities

NEW WEBSITE FOR MARKET DATA ANALYSIS John Ehlers, a Contributing Editor to this magazine, has announced the release of his new MesaSoftware.com website. MESA Software specializes in analyzing market data using advanced DSP techniques. He takes a scientific approach in developing filters, indicators, and trading systems and then uses statistics to verify performance. Ehlers’ stated mission is to provide cutting-edge scientific tools for traders. Among these tools are technical papers and seminars available for free download at the website. His MESA Phasor Futures trading strategy is described at his StockSpotter.com website. Editor’s note: Readers will find an article by John Ehlers & Ric Way in this issue, “Trading System Design: A Statistical Approach,” beginning on page 28.

MesaSoftware.com, StockSpotter.com Stock-Picking Service Adds Option TRADING With subscribers in 50 countries, Gorilla­ Trades is a global online subscriber service since 1999 providing news and professional insights into the stock market. Stock picks are listed regularly on a “menu” of both new and existing investments for consideration, based on subscribers’ individual investment objectives and risk tolerance. The service provides updated stop-loss levels and upside targets

weekly. Subscribers are directed to use the five-times-weekly subscriber portfolio named GorillaPicks as a guideline for investment decision-making. More than 6,000 stocks are sifted through daily to match each of the 14 technical indicators for potential growth. Recently, an “option idea of the week” feature was introduced for more aggressive investors. A 30-day free trial is available.

GorillaTrades.com NEW TREND SYSTEM Trading Alchemy has released its new Alchemy TrendCatcher System, which includes tools for entry triggers, bigger trend filters, and market reversal alerts. Alchemy TrendCatcher seeks to identify market trends and displays what it construes to be low-risk entry points. Its self-adaptive trailing stops seek to help minimize the initial risk while staying with the trend for longer moves. The built-in trend detector measures market strength. With its new trend filter, the trend-confirmation method seeks to help eliminate whipsaws while filtering out a significant amount of noise when the market is in a nontrending, consolidating phase. It attempts to capture a majority of big market moves. The system’s new market reversal alerts generate warning signals that tell the user when to tighten up stops as well as when to exit all positions. The added entry triggers confirm momentum changes, seeking to increase the probability of entering into the right direction of the market.

giving them access to more than one million ready-to-use strategies. Each of the strategies are complete systems with entry, exit, and management rules. Bloodhound allows the user to vet the strategies on 27 years of historical data and a set of historical metrics to ensure the strategy will be robust going forward. Users can choose to implement any of the strategies via direct integration with optionsXpress, a subsidiary of Charles Schwab & Co. Users are also able to modify any strategy or develop their own using a point & click interface. A free trial is available as well as a discount for the professional subscription level by using the promomotion code “bh2015.”

BloodhoundSystem.com PACKAGES of INDICATORS PivotHunter.com was formed by seven traders with more than 50 combined years of experience in chart analysis. The indicators offered by PivotHunter are designed to discern action between price velocity and order flow. Indicators are named after fictitious scenes with characters that represent the unfolding chart action (for example, three indicator packages include sheriffs, kings, or cavalry). Elements of analysis include money flow, velocity checks, and a heatmap. A live charting room is available.

TradingAlchemy.com collection of strategies Bloodhound Investment Research states its goal is to give users the tools to turn them into their own “hedge fund manager” by March 2015

PivotHunter.com

• Technical Analysis of Stocks & Commodities • 55

FUTURES LIQUIDITY

T

rading liquidity is often overlooked as a key technical measurement in the analysis and selection of commodity futures. The following explains how to read the futures liquidity chart published by Technical Analysis of Stocks & Commodities every month.

very high volumes. The greatest number of dots indicates the greatest activity; futures with one or no dots show little activity and are therefore less desirable for speculators. Courtesy of CBOT

Commodity futures

The futures liquidity chart shown below is intended to rank publicly traded futures contracts in order of liquidity. Relative contract liquidity is indicated by the number of dots on the right-hand side of the chart. This liquidity ranking is produced by multiplying contract point value times the maximum conceivable price motion (based on the past three years’ historical data) times the contract’s open interest times a factor (usually 1 to 4) for low or

three-year period. Thus, all numbers in this column have an equal dollar value. Columns indicating percent margin and effective percent margin provide a helpful comparison for traders who wish to place their margin money efficiently. The effective percent margin is determined by dividing the margin value ($) by the three-year price range of contract dollar value, and then multiplying by one hundred.

Stocks

All futures listed are weighted equally under “contracts to trade for equal dollar profit.” This is done by multiplying contract value times the maximum possible change in price observed in the last

Trading liquidity has a significant effect on the change in price of a security. Theoretically, trading activity can serve as a proxy for trading liquidity and equals the total volume for a given period expressed as a percentage of the total number of shares outstanding. This value can be thought of as the turnover rate of a firm’s shares outstanding.

Trading Liquidity: Futures

Commodity Futures Exchange % Margin Effective Contracts to Relative Contract Liquidity % Margin Trade for Equal Dollar Profit E-Mini S&P 500 GBLX 3.8 10.2 5 ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••>> 10-Year T-Note CBOT 1.1 20.8 26 ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••> T-Bond CBOT 2.3 15.3 9 ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• Ultra T-Bond CBOT 2.5 11 5 ••••••••••••••••••••••••••••••••••••••••••••••••••• Euro FX CME 1.7 8.1 6 ••••••••••••••••••••••••••••••••••••••••••• Japanese Yen CME 2.6 4.6 3 ••••••••••••••••••••••••••••••••••••••••••• E-Mini Nasdaq 100 GBLX 2.6 6.3 5 ••••••••••••••••••••••••••••••••••••••• Corn CBOT 13.8 11.9 8 •••••••••••••••••••••••••••••••••••••• Russell 2000 Mini ICEUS 3.8 10 4 ••••••••••••••••••••••••••••••••••• S&P 500 Index CME 3.8 10.2 1 •••••••••••••••••••••••••••••••••• 5-Year T-Note CBOT 0.6 17.4 44 ••••••••••••••••••••••••••••••• Gold COMEX 7 18.2 4 •••••••••••••••••••••••••••••• Soybeans CBOT 9.3 11.3 5 •••••••••••••••••••• Crude Oil WTI NYMEX 10.7 7.5 3 ••••••••••••••• Sugar #11 ICEUS 9 13 15 ••••••••••••• Gasoline RBOB NYMEX 11 6.8 2 ••••••••••• Natural Gas NYMEX 8.7 6.8 5 ••••••••••• Australian Dollar CME 2 6.1 7 ••••••••• DJIA mini-sized CBOTM 3.1 10 7 ••••••••• Heating Oil NYMEX 8.7 8.4 3 ••••••••• Wheat CBOT 12.1 15.8 9 ••••••••• E-Mini S&P Midcap GBLX 3.1 8.1 3 •••••••• British Pound CME 1.4 10.4 15 •••••• 2-Year T-Note CBOT 0.1 23.2 144 ••••• Canadian Dollar CME 1.3 5.2 9 ••••• Cotton #2 ICEUS 8.6 12.4 9 ••••• Soybean Meal CBOT 8.3 11.8 8 ••••• Soybean Oil CBOT 8.6 11.3 13 •••• Coffee ICEUS 8 20.8 8 ••• Nasdaq 100 CME 2.6 6.3 1 ••• Swiss Franc CME 1.5 10.7 9 ••• CBOT Chicago Board of Trade, Division of CME U.S. Dollar Index ICEUS 1.4 8.7 12 ••• CFE CBOE Futures Exchange CBOE S&P 500 VIX CFE 6.2 14.7 22 •• CME Chicago Mercantile Exchange Crude Oil Brent (F) NYMEX 10.3 6.2 2 •• COMEX Commodity Exchange, Inc. CME Group Eurodollar CME 0.1 53 296 •• GBLX Chicago Mercantile Exchange - Globex Hard Red Wheat KCBT 8.7 13.4 10 •• ICE-EU Intercontinental Exchange-Futures - Europe Lean Hogs CME 4.9 5.7 8 •• ICE-US Intercontinental Exchange-Futures - US Live Cattle CME 2.2 8.3 12 •• KCBT Kansas City Board of Trade Mexican Peso CME 6.5 28.4 24 •• MGEX Minneapolis Grain Exchange Cocoa ICEUS 6.4 20.8 21 • NYMEX New York Mercantile Exchange DJIA CBOT 3.1 10.2 3 • Palladium NYMEX 6.7 23.4 8 • Spring Wheat MGEX 11 14.5 8 • 30-Day Fed Funds CBOT 0 89.4 823 1503 Canola WCE 5.9 11.5 40 Trading Liquidity: Futures is a reference chart for speculators. It compares markets “Relative Contract Liquidity” places commodities in descending order according to according to their per-contract potential for profit and how easily contracts can be bought how easily all of their contracts can be traded. Commodities at the top of the list are easior sold (i.e., trading liquidity). Each is a proportional measure and is meaningful only est to buy and sell; commodities at the bottom of the list are the most difficult. “Relative Contract Liquidity” is the number of contracts to trade times total open interest times a when compared to others in the same column. The number in the “Contracts to Trade for Equal Dollar Profit” column shows how volume factor, which is the greater of: many contracts of one commodity must be traded to obtain the same potential return In volume 1 or exp –2 as another commodity. Contracts to Trade = (Tick $ value) x (3-year Maximum Price In 5000 Excursion).

56 • March 2015 • Technical Analysis of Stocks & Commodities

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Editorial Resource Index Microsoft Excel . . . . . . . . . . . . . . . . . 20

AIQ . . . . . . . . . . . . . . . . . . . . . . . . 49

QST Desktop (Quick Screen Trading) . . . . . . 23

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NinjaTrader . . . . . . . . . . . . . . . . . . . 50

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March 2015

• Technical Analysis of Stocks & Commodities • 57

The following selection of book descriptions represents a sampling of recent book releases in the investing field. Books described here may be from some of the major book publishers as well as some independent book publishers. These are not critical reviews or editorial evaluations, but rather a brief look at the book marketplace to help keep readers up to date on new or recent book offerings.

Doug Kass On The Market: A Life On TheStreet (44 pages, $29.95 hardcover, 2014, ISBN 9781-118-89298-5) by Douglas A. Kass with a foreword by James J. Cramer, published by Wiley. This book offers investment advice and guidance from this renowned trader. Kass distills his years of experience as a hedge fund manager and infamous short seller to share the theory, technique, and intuition that built his reputation and his portfolio. Anecdotes about interactions with Wall Street’s most famous names, including Warren Buffett, Jim Cramer, and Leon Cooperman, highlight tricks of the trade, value investing insight, and thoughts on shorting the market. Kass is a CNBC regular and was a 2013 Buffett Bear roundtable participant. In this book, Kass lists things to know when evaluating a possible long or short investment, and things you may not be doing to optimize your portfolio. He also describes how he thinks a stock should be properly shorted and discusses what fund managers don’t often discuss. www.wiley.com

No One Loves Your Money Like You Do: The Ultimate Retirement Planning Guide For Business Owners And Private Practitioners (256 pages, $25 softcover, 2014, 978-0-071-83936-5) by James Jackson, published by McGraw-Hill. This book provides retirement investing advice for high-networth professionals such as physicians, attorneys, and entrepreneurs, who may enjoy a good income and nest egg but who may have large, illiquid assets in the form of their practice as

well as possible partnership agreements to navigate. Jackson distills his decades of experience as a Certified Financial Planner (previously a practicing dentist) into practical, friendly advice for those who need a hand in planning their retirement. mhprofessional.com

The Intelligent Option Investor: Applying Value Investing To The World Of Options (304 pages, $45 hardcover, 2014, ISBN 9780071833653) by E r i k Ko b aya s h i Solomon, published by McGraw-Hill Professional. A company's worth is precisely the amount of wealth it will generate on behalf of its owners over its economic life. Using this principle as a touchstone, Kobayashi-Solomon shows that in the vast majority of cases, valuing a stock requires the answer to only three questions: How fast will revenues grow? How efficiently will the firm translate revenues into profits? What proportion of the profits needs to be reinvested in the short term, and how much will those investments help owners in the medium term? Kobayashi-Solomon is the founder and principal of IOI LLC and the director of research for YCharts Inc. Previously, he served as a market strategist for Morningstar and as co-editor of the Morningstar OptionInvestor newsletter. In addition to publishing sector and stock-specific reports for YCharts, he has expertise in corporate valuation, option investing strategies, and risk-control issues. mhprofessional.com

Dual Momentum Investing: An Innovative Strategy For Higher Returns With Lower Risk (216 pages, $50 hardcover, November 2014, ISBN 978-0071849449) by Gary Antonacci, published by McGraw-Hill Professional. Dual Momentum Investing details the author’s own momentum invest-

58 • March 2015 • Technical Analysis of Stocks & Commodities

ing method, which combines US stock, non-US stock, and aggregate bond indexes into a formula designed to increase profits and lower risk. The model he presents combines relative-strength momentum and absolute momentum to try to take advantage of intramarket trends while avoiding large drawdowns. His methodology, which he supports with research, is designed to pick up on major changes in relative strength and market trend. The book describes the various forms of price momentum and why they work. Antonacci has expertise in modern portfolio theory and optimization. In 1990, he founded Portfolio Management Consultants, which advises private and institutional investors on asset allocation, portfolio optimization, and advanced momentum strategies.

http://dualmomentum.net, http://mhprofessional.com

Mystifying Square, Divine Proportions: Nature’s Black Box (276 pages, $150 ebook, November 2015, ISBN 9781742984827) by Pauline NovakReich, published by Port Campbell Press. This volume traces W.D. Gann’s “ time factor” and “law of vibration” back to the Chaldeans of 3000 BCE Sumer, whose principal aspiration was to understand the motion of time. They divided time into years, months, weeks, days, hours, minutes, and seconds and devised calendars that helped them predict, and therefore survive, their two rivers’ ravaging floods. Inadvertently, their findings also solved the mystery behind the ups and downs of money markets. The square of 9 is a matrix embodying nature’s cosmic clock. Pauline Novak-Reich takes the reader through ancient math, sacred geometry, and lore, demonstrating the achievements of people who lived in tandem with nature. http://www.portcampbellpress.com.au/

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TOP 10 VIEWED ONLINE TRADING SERVICES You can find a wealth of information on the Internet for nearly any subject imaginable, including investing, trading, and the financial markets. You can even find a good amount on technical analysis. We contacted companies that offer services to traders over the Internet as well as financial website developers and asked them to fill out an online survey form to describe their Internet site. At our website in the Traders’ Resource area of Traders. com, you’ll find a database of the data we collected. The listed online services may offer charting, price quotes, and financial news and information; others offer a more specialized service that may be useful to investors and traders. Features may include stock

screening, articles, discussion forums, online support, and more. Traders’ Resource at traders.com In addition to the online trading services listing at Traders.com, you’ll also find listings of other trading-related products and services such as brokerages, data services, courses and seminars, software, publications, trading systems, and more. We hope this will help you learn about products to help in your trading endeavors. Just click on the Traders’ Resource link from Traders.com and follow the online trading services category link, or use the search feature to find products or services with specific attributes in this or other categories.

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7. Traders.com Advantage Technical Analysis, Inc. 8. eSignal Learning

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These are the 10 online trading services viewed most often on the Traders’ Resource website, where each company is listed in order of clicks received. This is not an editorial rating or ranking. For more information on specific products and services, try checking store.Traders.com for archived S&C product reviews.

The information in Traders’ Resource is the most accurate at the time of posting and is subject to change. Because the vendors posting to Traders’ Resource are responsible for their own listing, Technical Analysis, Inc. declines any and all liability for any representations made by the businesses and individuals listed. Nor can Technical Analysis, Inc. endorse any business or individual listed on Traders’ Resource. Technical Analysis, Inc. makes no warranties, express or implied, as to the accuracy and reliability of claims herein. You agree to release Technical Analysis, Inc., together with its respective employees, agents, officers, directors and shareholders, from any and all liability and obligations whatsoever in connection with or arising from your use of Traders’ Resource. If at any time you are not happy with the information posted to Traders’ Resource or object to any material within Traders’ Resource, your sole remedy is to cease using it. This list is updated frequently. If you are aware of a business that should be listed, please email us at [email protected].

March 2015

• Technical Analysis of Stocks & Commodities • 59

AT THE CLOSE overall direction of price movement and can be applied to charts of any time frame. Generally, when the tendency and pressure of a market is to the upside, the market will be higher than the SMA. The 90-period SMA is a great technical analysis tool when it comes to gauging the overall price movement. If the market moves above it on a daily chart, you would look for a strategic entry point that is in line with this type of price movement. Once you are confident of the direction of the FIGURE 1: GOING SHORT. A bearish candle opened above but closed below the SMA(30). The following market, you need to employ the proper entry tactic day, a short entry was made. to play the market. For part-time traders, it’s good to move to a higher time frame chart even though the higher time frame chart may generate fewer trading signals.

www.metaquotes.net

Continued from page 62

Steps in using the strategy

Step 1: Glance at your chart and identify the supply & demand zones. These are areas that price has tested and retested at least three times in the past. The “smart money” generally pays attention to these zones. They watch these levels and react to them. Step 2: Follow only the line of least resistance. This will stack the odds in your favor and will increase the probability of your survival. For example, in a bear FIGURE 2: BUYING THE BULLISH USDCAD. A trigger candle opened below the SMA(30) and later closed market, you would orient yourself with the bears, above it. On the following day, a long position was opened. You can see that a demand zone has been marked because that would be the line of least resistance. below the entry scene. The target was hit on the third day. Step 3: Be aware of the factors that contribute to reliable signals and how to take advantage of those signals. You also need to limit losses with stops, since trades can move against you. It is important that you not overcomplicate things when looking for entry signals. Since you’re trading part time, your objective should be to spend less time analyzing the markets.

Details of the strategy Strategy type: Trend-following Suitability: Part-time traders Time horizon: Daily charts Indicator 1: 30-period SMA Indicator 2: 90-period SMA

Interpretation of formation of indicators: A bull market is identified when the 30-period SMA is above the 90-period SMA. The logic is reversed for a bear market.

Long entry: In a bull market, when the price has gone below the 30-period SMA, you would need to wait for price. (I use candlestick charts, so I wait for a candle to close above the SMA before going long.) This candle must be of considerable length, but not too long. I look for a bullish engulfing candle without shadows, commonly referred to as marubozu. If it opens below the SMA (30) and closes above it, I’ll ignore the signal. But when a bullish candle with shadows opens below the shorter SMA and closes above it, I’ll pay attention to the signal. Short entry: In a bear market, when the price has moved above the SMA(30), you would need to wait for a candle to close below the SMA(30) before going short. Again, this candle must be of considerable length. For example, when a bearish marubozu candle opens above the shorter SMA and closes below it, I’ll ignore the 60 • March 2015 • Technical Analysis of Stocks & Commodities

signal. But when a bearish candle with shadows opens above the shorter SMA and closes below it, then I’ll pay attention to it.

Instruments: If you trade the currency markets, you can sift through 30 pairs and crosses to find reliable signals. I recommended trading pairs and crosses with a spread of 15 pips or less. Stop-loss: When going long, put a stop at the low of the trigger candle. Conversely, when going short, put a stop at the high of the trigger candle. Take profit: Set an initial target for each trade. If you’re trading forex, then set it at 300 pips. Since this is not a short-term trading system, you would not need to go for small profits. In some cases, some moves may be significant enough, giving you a nice gain. It is best to leave an open position until an exit condition is met. Exit rule: Make use of optimal breakeven and trailing stops. This exit rule takes you out of an unfavorable position. You can also adapt it to make you stay in a risk-free profitable trade while you run your gains.

Some recent trades

To help you better understand this trading method, I have provided some examples. The SMA(30) is the blue line and the SMA(90) is the green line. I have identified the supply & demand zones with the two horizontal lines. The red vertical line on the left shows where I took a signal, which is placed on the candle that serves as a trigger. The red vertical line on the right shows where I made an exit. I didn’t consider spreads in any of these examples.

AT THE CLOSE Example 1 On November 14, 2011, a bearish candle opened above but closed below the SMA(30) on the daily chart of the EURUSD (Figure 1). The following day, a short entry was made. The supply zone is marked above this candle by two parallel horizontal red lines. Some candles which preceded this trigger candle had repeatedly tested this area. Instrument: EURUSD Order: Sell Entry date: 11/15/2011 Entry price: 1.3600 Stop-loss: 1.3792 Trailing stop: 1.3450

Take profit: 1.3300 Exit date: 11/25/2011 Exit price: 1.3300 Status: Closed Profit/loss: 300 pips

FIGURE 3. CAPITALIZING ON THE BEARISH EURAUD. In early November 2011, the SMA(30) crossed below the SMA(90). About 10 days later, a bearish candle triggered a short signal and the EURAUD was sold short on the following day.

Example 2 On September 19, 2011, on the daily chart of the USDCAD, a trigger candle opened below the SMA(30) and later closed above it (Figure 2). On the following day, I opened a long position. I identified a demand zone below the entry point. The target was hit on the third day. Instrument: USDCAD Order: Buy Entry date: 9/20/2011 Entry price: 0.9900 Stop-loss: 0.9805 Trailing stop: 1.0050

Take profit: 1.0200 Exit date: 9/22/2011 Exit price: 1.0200 Status: Closed Profit/loss: 300 pips

FIGURE 4: TAKING A LOSS ON THE NZDUSD. A trigger candle was formed on May 20, 2011 and a long trade was opened on the following day. The market reversed and hit the stop-loss before it went in the expected direction.

Example 3 In early November 2011, the SMA(30) crossed below the SMA(90) on the daily chart of the EURAUD (Figure 3). More than 10 days later, a bearish candle triggered a short signal and I sold short the EURAUD on the following day. The supply zone is well above the entry point, and that suggested a strong short signal. Instrument: EURAUD Order: Sell Entry date: 11/30/2011 Entry price: 1.3250 Stop-loss: 1.3469 Trailing stop: 1.3100

Take profit: 1.2950 Exit date: 12/21/2011 Exit price: 1.0200 Status: Closed Profit/loss: 300 pips

Example 4 There are times when this strategy may not work, in which case you’ll have to honor the stop-loss and never run the loss beyond your initial stop. A trigger candle was formed on May 20, 2011 on the daily chart of NZDUSD (Figure 4), and I opened a long trade the following day. The market reversed and hit the stop-loss before it went in the expected direction. If the stop was wider I may not have been stopped out and instead would have profited handsomely. But as a matter of discipline, never widen your stop, because a reversal can be the beginning of a long-term move in the opposite direction. Instead, take your loss and look forward to the next trade. Instrument: NZDUSD Order: Buy Entry date: 5/23/2011 Entry price: 0.7930 Stop loss: 0.7904 Trailing stop: N/A

Take profit: 0.8230 Exit date: 5/23/2011 Exit price: 0.7904 Status: Closed Profit/loss: -26 pips

Conclusion

Trading involves making swift decisions. The minute you start hesitating, you overanalyze and are unable to place your trades at the right time. The sooner you see a good signal on your chart, the sooner you should be able to react and open a position. The more complicated you make a trading signal, the more analysis you would need to do before you can open a position. To emerge as a consistently surviving trader, you need to put your investments to good use. You need to constantly assess data, analyze it, and do something sensible out of that. In the end, you are responsible for your decisions, and the more time you spend doing this, the more competent you will become. The strategy I have described here is simple and worth trying. Azeez Mustapha is a professional forex trader, an analyst at instaforex, a blogger at ADVFN.com, and a freelance author. His articles have been published at itulglobalforex.blogspot. com, and in TRADERS’ magazine. He can be reached via email at [email protected].

Further reading

Mustapha, Azeez [2014]. “Beating The Currency Markets,” Technical Analysis of Stocks & Commodities, Volume 31: September. [2014]. “Recovering Your Fortune,” Technical Analysis of Stocks & Commodities, Volume 32: June. ‡Metaquotes.net March 2015

• Technical Analysis of Stocks & Commodities • 61

AT THE CLOSE The strategy and

Don’t Quit Just Yet

Play The Markets And Keep Your Day Job Not ready to be a full-time trader? Here’s a high-probability, part-time trading strategy that will help you master the markets before you commit to it full time.

To

be a winning trader, you need to master a discrete edge. But how do you gain that edge, especially if you are a part-time trader? Whenever you analyze the markets objectively, each trade you make will be of some benefit. Some of the most competent analysts are able to pinpoint winning signals constantly and control risk. Your ability to sight winning conditions is what will make a world of difference.

Can you trade and keep your day job?

Some traders — maybe you’re one of them — keep their jobs while using trading systems that allow them to trade on a part-time basis. Such traders would not use short-term strategies, since that would require that they stay glued to their screen most of the day. The trading systems that are well suited to part-time traders are usually longer term in nature. Even those who have transitioned to trading full time have realized that they do not necessarily have to spend more time trading than when they were trading part time. True, there are part-time traders who make as much money as full-time traders; in fact, some even make more than full-time traders. In addition, some traders’ mindsets prohibit them from watching their computer screen all day long since they may go livid watching their fortunes contract and expand.

by Azeez Mustapha 62 • March 2015 • Technical Analysis of Stocks & Commodities

The strategy I am going to discuss is one I have applied to the forex markets. It requires charts of a time frame higher than one or 30 minutes since it is designed for those who trade on a part-time basis. You’ll notice I use supply & demand zones in this system. The concept of supply & demand zones may be unfamiliar to you, but it’s not necessary to know it to make trading decisions. The zones are merely guidelines that you will be able to visually identify on a chart. Part-time traders should examine major moves and conscientiously anticipate high-probability trades so they can benefit from those moves. The various price zones may be used as a compass to assist you in locating high-probability signals and exit areas. Perceiving the overall direction of the market is invaluable. For example, in a northbound market, if you had entered a long position at the previous peak you would be ahead. Similarly, entering a short position at the previous trough of a southbound market will put you ahead. Whenever a consolidation zone materializes, it’s a good idea to stay out of the markets. This is also true when a countertrend move occurs. One of the earliest signals of a countertrend move is the violation of a crucial price zone. When that happens, it’s an indication that the market may reverse or it could result in a state of price equilibrium. Although this is nothing unusual, it is necessary for you to be confident about the general direction of price moves. Of course, not all positions would go in the forecasted direction, but having a system that requires you to spend a short period of time analyzing and making decisions is something well suited for the part-time trader.

Chaotic hullabaloo

The simple moving average (SMA) sometimes gets distorted because of erratic data. This would normally indicate that the sellers are dominant, but that could quickly change. You need to be aware of such erratic movements in data so as not to be caught unaware. The SMA is useful in gauging the Continued on page 60

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