Technical Analysis Of Stocks Commodities Tasc January 2021

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ETF MIDCAP GROWTH INVESTING Outperforming in the midcap space

INTERVIEW Kyle Crystal

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CONTENTS

JANUARY 2021, VOLUME 39 NUMBER 1

7 Algo Q&A The Traders’ MagazineTM EDITORIAL

[email protected] Editor in Chief Jack K. Hutson Production Manager Karen E. Wasserman Art Director Christine Morrison Graphic Designer Wayne Shaw Webmaster Han J. Kim Contributing Editors John Ehlers, Anthony W. Warren, PhD. Contributing Writers Thomas Bulkowski, Martin Pring, Barbara Star, Markos Katsanos, Leslie N. Masonson, Karl Montevirgen

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by Kevin J. Davey Got a question about system or algo trading?

FEATURE ARTICLE 8 A Fresh Look At Short-Term Patterns

TIPS

experience in formulating and implementing investment policy in various styles, including longshort, global macro and long-only for single managed accounts as well as fund structures. Stocks & Commodities Contributing Writer Karl Montevirgen spoke with him about his approach to analyzing the markets, an approach that includes multiple timeframe analysis, market geometry, Elliott wave theory, momentum oscillators, Gann analysis, cycles, and candlesticks.

by Perry J. Kaufman You may be familiar with some of the most popular short-term patterns, but do you know which work best? These test results may help you find out.

18 Semi-Annual Gold Momentum Strategy: International Evidence

by Massoud Metghalchi, PhD, with Ahsan Baig If you find an investing strategy with an edge, it’s worth looking to see if you can broaden the strategy for more opportunities. Here, we’ll revisit the gold momentum strategy to test it on some worldwide markets this time. We think you’ll like the results.

40 Explore Your Options

by Jay Kaeppel Got a question about options?

42 Futures For You

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

20 Managing Trading Fear And Stress by Stella Osoba Keeping emotion out of your trading decisions is always an important part of managing your trading. Understanding the biological processes behind our reactions to stimuli can help us find ways to counter unproductive emotions.

44 Buy Support, Sell Resistance

by Ken Calhoun Here’s what to look for if you want to trade within a price channel.

60 Trading Perspectives

by Rob Friesen Some perspectives on the equities world.

24 ETF Midcap Growth Investing

by Leslie N. Masonson One group of stocks with marketbeating performance over the past decade has been midcap growth stocks. ETFs provide a way to invest in a basket of stocks in this or other categories. Here’s a look at a handful of ETFs in this category to consider.

28 A Quick Look At Approaching Cryptocurrencies

by Azeez Mustapha Are candlestick patterns and basic technical analysis principles useful for trading cryptos? We take a look.

INTERVIEW 32 Technical And Market Analysis With Kyle Crystal

by Karl Montevirgen Kyle Crystal, CMT, CFTe, is a portfolio manager and technical/ quantitative market strategist with

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38 Target Rich Trades MetaStock Add-on.

DEPARTMENTS

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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

TREND DIRECTION AND PROBABILITY: THE BULL BEAR INDEX Editor, I thoroughly e nj oye d M i k e Siroky’s article on the “Bull Bear Index” in the November 2020 issue of Technical Analysis of Stocks & Commodities and I would like to use it in my own trading. However, I don’t understand how to set up the Excel formula for the t.dist function in Excel; perhaps you could persuade Dr. Siroky to provide the Excel code. Thank you. Tony Author Mike Siroky replies: Here is the Excel command for the cumulative t-distribution: You first need the difference between high and low probability normalized by the combined standard deviation, as described in the article. We can call this normalized value x. You also need the degrees of freedom (df) which is equal to n, your time window, minus 1. For a time window of 25 days, degrees of freedom is 24. Type into a blank box: =t.dist(x,df,true) to generate the cumulative probability, a value between 0 and 1. For example, if your difference x is 0, and your degrees of freedom is 24, you should generate a value of 0.5. Hope this helps.

MORE ON TREND DIRECTION AND PROBABILITY: THE BULL BEAR INDEX Editor, I’m writing about the article in the November 2020 issue, “Trend Direction And Probability: The Bull Bear Index,” by Mike Siroky. I would like to pursue using his technique. I was wondering if there is coding available for this indicator so I can use it on my trading platform? Thanks a lot for your help. Antonio Editor: We asked a platform developer about possible implementation on a trading platform, and they offered the following thought. One way to implement it could be for motivated readers to download and use a third-party library such AlgLib, MathNet, or MetaNumerics to implement the “student’s distribution” used in the calculation of the technique. Maybe someone reading this will also have some suggestions or thoughts to offer. VERIFYING READERS’ CHOICE AWARDS? Editor, I am interested in purchasing a particular product to use in my trading, but I first want to collect some feedback on the product from other users and try to verify it will do what it claims to be able to do. I know your magazine gives out Readers’ Choice Awards to products every year, and I often see product vendors citing these awards. I want to be able to verify the awards given. Many thanks if you are able to help. Thomas

6 • January 2021 • Technical Analysis of Stocks & Commodities

Editor: There is a new feature at our website where visitors can review past Readers’ Choice Awards given and browse a list of historical recipients. We are offering this information to help users verify the winners of the awards and to help users research products that may be of interest to them. We believe it’s helpful for readers to know what other readers of this magazine have found to be useful in their trading. This feature can be found on our homepage at www.traders.com under “Readers’ Choice Awards—Historical Winners.” We hope this helps.

On a related note, we’d like subscribers to this magazine to know that voting in our annual Readers’ Choice survey is now underway! Results of this survey are used to determine the next set of Readers’ Choice Award recipients. Recipients of the awards will be revealed in our Bonus Issue of Technical Analysis of Stocks & Commodities magazine, to be published in February. Voting ends December 31, 2020. Visit our website at www.traders.com to cast your vote! We want to hear from you.

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Algo Q&A ALGORITHMIC TRADING Have a question about system or algo trading? Kevin J. Davey has over 25 years of system trading experience. Davey is a full-time trader, and he also teaches and consults via his Strategy Factory online workshop (https://kjtradingsystems. com). He is the author of several bestselling trading books, including Building Winning Algorithmic Trading Systems and Introduction To Algo Trading. Send your questions or topic suggestions to Kevin Davey at kdavey@kjtradingsystems. com. Selected questions will appear in a future issue of S&C. Kevin J. Davey

Confused yet? Maybe an example will help. Here is how the data is presented in TradeStation:

after 5:00 pm—when the exchange determines the settlement price—the daily bar closing price will “jump” to reflect the settlement price.

XX minute bars: Closing price is always the last price traded. So, with a 1440-minute bar, the closing price will be the last price traded at 5:00 pm

For some markets (like the mini S&P), this difference is usually minor. But for markets like gold and crude oil, the difference can be huge. Figure 1 shows an example—the

Daily bars: Closing price during the day will be the last price traded. But,

Continued on page 17

TRADESTATION

CLOSING TIME(S) I have a gold algo, and I was calculating values today after the close at 5 pm and got an entry signal. But at 6 pm, the closing price had changed significantly, making my signal invalid. What went wrong? Based on your question, I would guess that you have fallen victim to the “last vs. settlement closing price” issue. Let me explain it, and I’ll give you some workarounds. Back in the old days, all futures and commodities were traded in pits, via open outcry. There was no electronic market, and there were limited trading hours—not the near 24-hour markets we enjoy today. To further confuse the issue, many markets closed at different times of the day. Gold, for example, closed at 1:30 pm. The exchange then determined the settlement (closing) price for the day based on the last minute or two of trading. That is the price you’d see on your daily equity brokerage statements. When markets transitioned away from pit trading, the market hours expanded (gold now closes at 5:00 pm), but the settlement price time fix did not. Gold still has a settlement price calculated at 1:30 pm, even though the market is open until 5:00 pm. For reference, you can find a list of settlement times for the CME futures exchange here: https://www. cmegroup.com/market-data/settlements/ settlements-details.html This means we have two possible closing prices: the last price traded at 5:00 pm, and the settlement price of around 1:30 pm. This creates an issue of how the data is presented to the user. Is the closing price shown the last price traded, or the settlement price? And does this even matter?

FIGURE 1: GOLD, LAST PRICE TRADED VS. DAILY SETTLEMENT PRICE. The 1440-minute bar close is the last price traded, while the daily bar close is the daily settlement price.

FIGURE 2: DIFFERENCE IN LAST PRICE TRADED VS. SETTLEMENT PRICE. The price of gold plummeted in the last few hours of the trading day, after the settlement time. This causes the 1440-minute and daily bars to be dramatically different. January 2021

• Technical Analysis of Stocks & Commodities • 7

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8 • January 2021 • Technical Analysis of Stocks & Commodities

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PRICE PATTERNS

With (And Without) A Trend Filter

A Fresh Look At Short-Term Patterns You may be familiar with some of the most popular short-term patterns, but do you know which work best? These test results may help you find out.

I

have always liked short-term price patterns. The simplest, such as an island reversal, seem intuitively correct. The best study of chart patterns I’ve seen is by Thomas Bulkowski, who ranked the three top bullish patterns as follows: 1. Upward breakout of a rectangular top (this is the same as a breakout above a horizontal resistance line) 2. Upward breakout from a falling wedge 3. Upward breakout from an ascending triangle and the three best bearish patterns as: 1. Descending scallop (a series of failed attempts at recovery) 2. Downward breakout of a symmetric triangle in a downtrend 3. Downward breakout of a broadening top

• Key reversals, a higher high followed by a lower close. We sell the lower close. The opposite for buy signals. • Island reversals, a gap higher followed by a lower close, but not filling the gap. We sell the lower close. The opposite for buy signals. • Outside days, a higher high and a lower low, but the close in the upper or lower 25% of the range. We buy if upper, sell if lower. • Wide-ranging days, the same as outside days, but the true range must exceed 1.5 × 20-day average true range. • Compression, the most recent 3 days must each have a true range smaller than the 4th previous day. We buy a breakout above the highest high of the last 3 days and sell a breakout below the lowest low of the past 3 days. • Gap openings, must be larger than 0.5 × 20-day ATR. We buy or sell the close of the gap day in the direction of the opening gap. All of these require no more than three days to identify and generate a trading signal. That fits my idea of instant gratification.

The test I will select a small set of ETFs and stocks that I think are a representative sample and of interest to investors: SPY (S&P 500), QQQ (Nasdaq), IWM (Russell small caps), AAPL (Apple), AMZN (Amazon), GE (General Electric), WMT (Walmart), and TSLA (Tesla). A selection of short-term patterns Hopefully, we can draw some valid conclusions. One Most of us are familiar with the popular short-term problem with testing a large number of stocks is that patterns, but not necessarily which are better and the averages hide many of the good results. which are worse. In this article, I’ll take a look at the I will test from January 2000 through July 2020, a following patterns: sample that includes a wide variety of trends, price

LISA HANEY

Patterns can range from simple to complex. The most complex one that I know of can take 22 days to produce a signal. But most traders, including myself, want something faster. The question is, “Are there short-term patterns that work?”

by Perry J. Kaufman January 2021 • Technical Analysis of

Stocks & Commodities • 9

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FIGURE 1: KEY REVERSAL PATTERN. In this example, cumulative returns following a key reversal day are shown. FIGURE 4: KEY REVERSAL BULL. Key reversal bull moves (top) and summary (bottom).

FIGURE 2: KEY REVERSAL PATTERN. The same data from Figure 1 is shown graphically here, cumulative returns following a key reversal day.

FIGURE 3: TREND FILTER. Cumulative returns using a key reversal plus a trend filter.

shocks, and market confusion. The position size is always $10,000 divided by the closing price. That will come close to making each trade equal risk so that a trade taken in 2020 at a high price will not overwhelm a trade taken in 2000 at a lower price. In addition to the results of these patterns, I will also apply an 80-day moving average trend filter, typical of a macrotrend system. We will buy only when the moving average is up and sell when it is down.

Example

Let’s look at the first pattern, a key reversal, applied to SPY and TSLA, two extremes. Because the SPY is the cap-weighted average of 500 stocks, it will always be less volatile than an individual active stock such as TSLA. The table in Figure 1 separates the upward reversals (“bull moves”) from the downward ones (“bear moves”). The numbers are the cumulative profits and losses from the entry on the close of the day of the reversal. Figure 2 shows the same returns on a chart. 10 • January 2021 • Technical Analysis of Stocks & Commodities

FIGURE 5: KEY REVERSAL BEAR. Key reversal bear moves (top) and summary (bottom).

Peak returns for TSLA occur on the second close after entering a key reversal upward. But then, TSLA has been in a strong uptrend, so we would expect the upside to be more profitable than the downside. SPY shows no gains at all, for either the upward (bull) or downward (bear) reversal. What if we filter these reversals with a trend, taking the reversal only in the direction of the trend? To avoid massive testing, we will only look at the 80-day moving average, which I consider representative of a macrotrend strategy. Figure 3 shows the results. While the trend does not seem to change the returns of TSLA except to make days 3, 4, and 5 similar, it drops the number of bull trades from 54 to 32, a reduction of 40%. That makes the profits per trade 40% larger, a significant benefit. The trend improved the downward reversals but not by enough to make them an interesting trade.

A broader view of the key reversal

When we look at our set of 3 ETFs and 5 stocks, we see a pattern that is different for ETFs and stocks. Because the ETFs are an index, the results are muted compared to stocks. QQQ and IWM are more volatile than SPY and show gains on days 3 and 4 for upward moves. Our selected stocks perform much better on those days. This can be seen in Figure 4 and in the averages in the lower section. The lower table clearly shows that the stock returns increase and peak on day 4. The equity index ETFs have small, positive returns on days 3 and 4. The bear market scenario is different, as seen in Figure 5. https://libta.org

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FIGURE 6: KEY REVERSAL. Key reversal results using an 80-day moving average trend filter.

FIGURE 8: 3-DAY COMPRESSION. (Top to bottom): Bull moves with and without a trend filter; bear moves with and without a trend filter.

FIGURE 7: ISLAND REVERSALS. (Top to bottom): Bull moves without and with a trend filter; bear moves without and with a trend filter.

Again, stocks outperform the index markets, but this time all but GE and TSLA are negative, with the least negative being day 1 and day 2. We can guess that the upward bias of the stock market makes it difficult to profit from moves to the downside.

Adding a trend filter

Normally, trading only in the direction of a macrotrend will improve returns. It will also reduce the number of trades. Continuing with the key reversal example, but only showing the summary, the results of the bull moves (up) are similar to the results without a trend filter, but using the trend filter (Figure 6) reduces the number of trades by about 37%, which makes the profits per trade that much bigger and reduces the time in the market. Less time in the market means less risk.

All of these require no more than three days to identify and generate a trading signal. That fits my idea of instant gratification. 12 • January 2021 • Technical Analysis of Stocks & Commodities

Island reversal The island reversal is more specific than the key reversal; therefore, it has only a few trades per year. That would be fine if it produces more consistent or more profitable returns. Figure 7 shows the summary of bull and bear island reversals, with and without the trend filter. Unlike the key reversal, this pattern shows profits for the index markets. For stocks, WMT and TSLA were profitable for upward moves without the trend, but the averages reflect large losses from AAPL. An island reversal in the index markets would indicate a broad economic event. Compression The 3-day compression represents a market that is consolidating, and the trading signal is a breakout of the high or low of those 3 days. The highs and lows of the 3 days do not have to be inside the larger range of the 4th day back, only the true ranges must be smaller. It is interesting because it seems to identify more frequent and more reliable moves to the upside when compared to the previous patterns. Toby Crabel referenced this as one of the best patterns for intraday trading. Results are shown in Figure 8. This formation does not work well with a trend filter. AAPL and TSLA had strong returns when taking upward breakouts. Outside day An outside day indicates volatility, a much more active day. In our test, we go long if the close is in the upper 25% of the range. We sell short if the close is in the lower 25% of the range. Figure 9 shows the four summary results. Bull moves, that is, upward breakouts, are profitable for both index ETFs and stocks, with all markets net positive after 4 days. Breakouts to the downside posted losses everywhere. Adding a trend filter gave results similar to the key reversal. The net returns were slightly lower but the reduction in the number of trades made the profits per trade higher. https://libta.org

FIGURE 9: OUTSIDE DAY BREAKOUT. Outside day (top to bottom) upward breakout with and without a trend filter; downward breakouts with and without a trend filter.

FIGURE 10: WIDE-RANGING DAY. Wide-ranging day (top to bottom) upward breakout with and without a trend filter; downward breakouts with and without a trend filter.

Wide-ranging day A wide-ranging day does not need to be an outside day, only a very volatile one, 50% bigger than the average range. We go long if the close is in the upper 25% of the range and sell short if the close is in the lower 25% of the range. Although individual stocks show a profitable average, all results are very small. Adding a trend improved results in some places and lowered results in others, as shown in Figure 10. Overall, this pattern is not working, or our breakout rule is wrong. Gap openings And now for our old friend, the gap opening. We want to believe that a gap opening, at least a large one, is important. We defined our minimum gap as 50% of the 20-day average true range, so that a stock trading at $100 with an ATR of $2.00 will need to

FIGURE 11: GAP OPENING. Gap opening (top to bottom) upward with and without a trend filter; downward with and without a trend filter.

open up or down $1.00 to qualify. That turns out to be about 125 cases over the past 20 years. Hopefully, these larger gaps will have a predictable pattern. Our rule is to go long or short on the close of the day with the gap, not on the opening gap, and take a position in the direction of the gap opening. We are looking for some continuation over the next 5 days, and this makes it easier to compare the gap opening with the other patterns. Figure 11 shows that an upward breakout is followed by upward moves, for both index ETFs and stocks, with the higher returns on day 5. The best performers were AAPL, TSLA, and AMZN, in that order. The only loss was in the SPY, a market dominated by noise. Gaps to the downside were also profitable, but only during the first two days, then those gains drifted away. The trend filter improved the stock returns everywhere but hurt the index returns. The upward bias of the stock market seems to be a better trend indicator. Applying the trend filter to the downward gaps did not improve returns.

Conclusions

Trading would be easy if all of these patterns were profitable. But the stock market is biased to the upside, so it is not surprising that upward breakouts (bull moves) are more successful.

In addition to the results of these patterns, I will also apply an 80-day moving average trend filter, typical of a macrotrend system. January 2021 • Technical Analysis of

Stocks & Commodities • 13

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UNITED STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF ILLINOIS EASTERN DIVISION HARRY PLOSS, as Trustee for the HARRY PLOSS TRUST DTD 8/16/1993, on behalf of himself and a proposed class, et al., v.

No. 1:15-cv-02937

Plaintiffs

Judge John F. Kness

KRAFT FOODS GROUP, INC. and MONDELĒZ GLOBAL LLC, Defendants

SUMMARY NOTICE OF PENDENCY OF CLASS ACTION TO: All persons and entities who purchased a Chicago Board of Trade (“CBT”) December 2011 soft red wheat futures contract or a CBT March 2012 soft red wheat futures contract after October 31, 2011, or sold a put option or purchased a call option on one or both of these contracts after October 31, 2011. The precise definition of the certified class appears below. If you are a clearing firm, futures commission merchant, brokerage firm or trustee through which CBT December 2011 soft red wheat futures contracts or CBT March 2012 soft red wheat futures contracts were traded after October 31, 2011, or through which put options were sold or call options were purchased on one or both of these futures contracts after October 31, 2011, please provide the name(s) and last known address(es) of such customers to the Notice Administrator, A.B. Data, Ltd. at the address listed below within one week of receiving this Notice. Alternatively, you may mail or email copies of this Notice to such persons or entities that are members of the Class within two weeks of receiving this Notice. Please preserve your clients’ transaction records in CBT December 2011 and CBT March 2012 soft red wheat futures contracts (and options on such futures contracts) traded after October 31, 2011. This Summary Notice seeks to alert you to a certified class action lawsuit called Ploss v. Kraft Foods Group, Inc. et al., Case No. 1:15-cv-02937, pending in the United States District Court for the Northern District of Illinois in Chicago before the Honorable John F. Kness. Plaintiffs Harry Ploss, Richard Dennis, Budicak Inc., Joseph Caprino, Kevin Brown, White Oak Fund LP, and Robert Wallace (collectively, “Plaintiffs”) brought a lawsuit on behalf of themselves and other similarly situated persons against Kraft Foods Group, Inc. and Mondelēz Global LLC (collectively, “Kraft”). The lawsuit alleges that Kraft manipulated the prices of the CBT December 2011 soft red wheat futures contract (“CBT December 2011 Contract”) and the CBT March 2012 soft red wheat futures contract (“CBT March 2012 Contract”) by buying and maintaining a 3,000 contract position (approximately 15 million bushels) in the CBT December 2011 Contract for the purpose of influencing prices, rather than because of any legitimate need for that quantity of wheat. Plaintiffs assert claims against Kraft under the Commodity Exchange Act, 7 U.S.C. §1 et seq. (“CEA”), the Sherman Antitrust Act, 15 U.S.C. § 2, et seq. (“Sherman Act”) and the common law regarding unjust enrichment. Kraft denies that it did anything wrong and asserts that Plaintiffs’ claims have no merit. Kraft asserts that its futures position was well within applicable limits, and did not impact any futures prices throughout November 2011 or thereafter. Kraft also asserts there was nothing improper about standing for delivery in the futures market given that cash market prices were high and Kraft had a real need for wheat. The Court has appointed the lawyers listed below to represent the Class in this lawsuit (“Class Counsel”). You may hire your own lawyer to appear in Court for you, but if you do, you are responsible for paying that lawyer. Christopher Lovell Christopher McGrath LOVELL STEWART HALEBIAN JACOBSON LLP 500 Fifth Avenue, Suite 2440 New York, New York 10110 Telephone: (212) 608-1900

Vincent Briganti Raymond Girnys LOWEY DANNENBERG, P.C. 44 South Broadway, Suite 1100 White Plains, New York 10601 Telephone: (914) 997-0500

WHO IS A MEMBER OF THE CLASS? The Class certified by the Court is defined as all persons or entities who either: a. purchased a CBT December 2011 Contract or a CBT March 2012 Contract after October 31, 2011 except that purchases of CBT March 2012 Contracts made after December 14, 2011 qualify for inclusion in the Class only to the extent they were made in liquidation of a short position in the CBT March 2012 Contract (whether an outright short position or as part of a spread position) which was sold between November 1 and December 14, 2011 inclusive; or b. sold put options or purchased call options on the CBT December 2011 Contract or on the CBT March 2012 Contract after October 31, 2011 except that sales of put options or purchases of call options on the CBT March 2012 Contracts made after December 14, 2011 qualify for inclusion in the Class only to the extent they were made in liquidation of a position in the CBT March 2012 Contract (whether an outright position or as part of a spread position) which was initiated between November 1 and December 14, 2011 inclusive. Excluded from the Class are Cargill, Inc., the Defendants and any parent, subsidiary, affiliate or agent of any Defendant.

YOUR LEGAL RIGHTS AND OPTIONS IN THIS LAWSUIT If you are a member of the Class, you will need to decide whether to (a) remain in the Class or (b) request to be excluded from the Class. To remain in the Class, you do not need to do anything at this time. If you remain in the Class, you will give up the right to file (or continue) Continued on Next Page https://libta.org

Continued from Previous Page

SUMMARY NOTICE OF PENDENCY OF CLASS ACTION your own lawsuit or seek any other form of resolution of claims you might have against Kraft concerning the claims in this lawsuit, and you will be legally bound by all court orders, judgements, or settlements approved by the Court. If money or benefits are obtained for the Class as a result of judgment or settlement, you may be entitled to share in a portion of such money or benefits. If money or benefits are obtained in this class action, the Class will be separately notified as to how to make a claim to participate and request a share of any money or benefits recovered for the Class. Class members may be required to produce trading records for all accounts in which they have a financial interest, showing all trades in the CBT December 2011 or March 2012 Contracts made after October 31, 2011. Class members should preserve records of their transactions in CBT December 2011 and CBT March 2012 Contracts (and options on such futures contracts) traded after October 31, 2011 (including any monthly statements for October 2011). Class members should also preserve records of any purchases and/or sales of physical wheat in the cash market between November 1, 2011 and March 14, 2012. If you do not want to participate in this lawsuit, you can opt out of the Class and request to exclude yourself. If you choose to exercise your right to opt out of the Class, you will not be bound by any court orders, judgments, jury verdicts, or settlements approved by the Court, but you keep your right to sue or otherwise resolve your potential claims against Kraft on your own. If you opt out, you cannot make a claim against any money or benefits that might be recovered by the Class from Kraft in a settlement or as a result of a judgment, if any. To opt out of the Class, you must mail, e-mail or submit through the case website a written statement to A.B. Data, Ltd. (mailing address, e-mail address and case website address referenced below) no later than February 11, 2021 stating: (1) you are a member of the Class in Ploss v. Kraft Foods Group, Inc. et al. and (2) you request to be excluded from the Class. Your written request for exclusion must also include your full name, address, telephone number, e-mail address (if any) and signature. A sample opt-out form is available on the case website address referenced below. The Court will exclude from the Class any member who submits a valid and timely request for exclusion. 2011 Wheat Futures Class Action Exclusions c/o A.B. Data, Ltd. P.O. Box 173001 Milwaukee, WI 53217 877-883-8949 [email protected]

HOW CAN I GET MORE INFORMATION? If you have questions related to this lawsuit, your rights or wish to review other documents related to this lawsuit, you may visit www.2011wheatfuturesclassaction.com or call 877-883-8949. You may also contact Class Counsel with any questions. PLEASE DO NOT CALL OR CONTACT THE COURT OR THE CLERK’S OFFICE REGARDING THIS NOTICE OR FOR ADDITIONAL INFORMATION. QUESTIONS? VISIT www.2011wheatfuturesclassaction.com or CALL 877-883-8949 TOLL FREE

Because the index ETFs include a large set of stocks, we would expect them to be less volatile, but when they gap open, have an island reversal, or break out of a compression formation, they tend to reflect a broader economic event. Island reversals, gaps, outside days, and key reversals are best with stocks because of their higher volatility. While the gains from any one of these patterns may be small, they are not likely to occur on the same day, so you can trade more than one pattern and add the returns together. Be sure to test these yourself. The more volatile stocks offer the best opportunities. Perry J. Kaufman is a trader and financial engineer. He is the author of many books on trading and market analysis, including the new sixth edition (2020) of Trading Systems and Methods (with the first edition published in 1978 as a seminal book in the field of technical analysis), and the newly released Kaufman Constructs Trading Systems (2020). For questions or comments, please go to www.kaufmansignals.com. The code given in this article is available in the Article Code section of our website, Traders.com. See our Traders’ Tips section beginning on page 46 for commentary and implementation of Perry Kaufman’s technique in various technical analysis programs. Accompanying program code can be found in the Traders’ Tips area at Traders.com.

Further reading

Bulkowski, Thomas N. [2005]. Encyclopedia Of Chart Patterns, 2nd. Edition, Wiley Trading. [2016]. Chart Patterns: After The Buy, Wiley Trading) Kaufman, Perry J. [2020]. Kaufman Constructs Trading Systems (print and ebook editions), Amazon. [2020]. Trading Systems and Methods, 6th Edition, Wiley. [2003]. A Short Course In Technical Trading, Wiley. [1995]. Smarter Trading, McGraw-Hill. ‡TradeStation

‡See Editorial Resource Index

EASYLANGUAGE CODE FOR PRICE PATTERNS WITH AND WITHOUT TREND FILTER // PJK Short-Term patterns // Look at reliability of short-term patterns with and without a // trend filter. // Look at using noise as a qualifier // Copyright 2020, P.J.Kaufman. All rights reserverd inputs: trendper(0), usekeyreversal(false), useislandreveral(false), usecompression(0), usegaps(0), useoutsideday(false), usewiderangingday(0), forecast(5), investment(10000); vars: trend(0), pattern(" "), bullcases(0), bearcases(0), keyreversal(false), islandreversal(false), January 2021 • Technical Analysis of

Stocks & Commodities • 15

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compression(false), gap(false), outsideday(false), widerangingday(false), bullpattern(false), bearpattern(false), bulltrend(false), beartrend(false), bulltrendcases(0), beartrendcases(0), cday(0), comphigh(0), complow(0), outsidebull(false), outsidebear(false), ratio(0), ndays(0), ix(0), lookahead(0), adate(" "), size(0), back1(0), back2(0), back3(0), back4(0); arrays: bullreturns[6](0), bearreturns[6](0), bulltrendreturns[6](0), beartrendreturns[6](0); // trend if trendper > 0 then begin trend = average(close,trendper); end; // 3-day compression if usecompression = 3 then begin cday = truerange[3]; compression = truerange < cday and truerange[1] < cday and truerange[2] < cday; end; // key reversals =================================== if usekeyreversal and ndays = 0 then begin keyreversal = true; pattern = "Key Reversal"; // without trend // key bearcases reversal if high > high[1] and low < low[1] and close < low[1] then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment/close; if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // key bullcases reversal else if high > high[1] and low < low[1] and close > high[1] then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; // island reversals ================================= if useislandreveral and ndays = 0 then begin keyreversal = true; pattern = "Island Reversal"; // without trend // bearcases island reversal if low > high[1] and close < open then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment/close; if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // bullcases island reversal else if high < low[1] and close > open then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment/close; if trend > trend[1] then begin

16 • January 2021 • Technical Analysis of Stocks & Commodities

bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; // compression ===================================== if usecompression > 0 and ndays = 0 then begin pattern = "3-Day compression"; back4 = truerange[4]; back3 = truerange[3]; back2 = truerange[2]; back1 = truerange[1]; compression = back4 > back3 and back4 > back2 and back4 > back1; if compression then begin comphigh = highest(high[1],usecompression); complow = lowest(low[1],usecompression); // bearcases compression if close < complow then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment/close; if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // bullcases island reversal else if close > comphigh then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment/close; if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; end; // Outside day (or wide ranging day) with close in upper/lower // 25% =========================================== if (useoutsideday or usewiderangingday <> 0) and ndays = 0 then begin if useoutsideday then pattern = "Outside Day" else pattern = "Wide Ranging Day"; outsidebull = high > high[1] and low < low[1] and close > 0.75*(high - low) + low; outsidebear = high > high[1] and low < low[1] and close < 0.25*(high - low) + low; ratio = 0; if usewiderangingday <> 0 then begin ratio = truerange/avgtruerange(20); end; // bearcases outside day if outsidebear and (ratio = 0 or ratio > usewiderangingday) then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment/close; if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // bullcases island reversal else if outsidebull and (ratio = 0 or ratio > usewiderangingday) then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment/close; https://libta.org

if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; // Gap opening with profits in the direction of the gap ====== if usegaps > 0 and ndays = 0 then begin pattern = "Gap Opening"; ratio = (open - close[1])/avgtruerange(20)[1]; // downward gap if ratio < 0 and -ratio >= usegaps then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment/close; if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // bullcases island reversal else if ratio >= usegaps then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment/close; if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; // accumulated profits over next 5 days ================== if ndays > 1 then begin if bullpattern then bullreturns[ndays] = bullreturns[ndays] + size*(close - close[ndays-1]); if bearpattern then bearreturns[ndays] = bearreturns[ndays] + size*(close[ndays-1] - close); if bulltrend then bulltrendreturns[ndays] = bulltrendreturns[ndays] + size*(close - close[ndays-1]); if beartrend then beartrendreturns[ndays] = beartrendreturns[ndays] + size*(close[ndays-1] - close); end;

Algo Q&A

DAVEY

Continued from page 7

1440-minute bar close is the last price traded, and the daily bar close is the daily settlement price. Some days the difference is small, other days it is huge. But, it is almost never exactly zero. Take August 19 as an example. The 1440-minute bar has a close of 1934.2, while the daily settlement price was 1970.3, a difference of 36.1, over $3,600 per contract! What happened here? As shown in Figure 2, the price of gold plummeted in the last few hours of the trading day, after the settlement time. So the 1440-minute and daily bars are dramatically different.

if ndays > 0 then begin ndays = ndays + 1; end; // summary if lastbaronchart then begin adate = ELdatetostring(date); print(file("c:\tradestation\Short-Term Patterns.csv"), "Date,Pattern,Cases,Bull Cases,BullPL1,BullPL2,BullPL 3,BullPL4,BullPL5,Bear Cases,", "BearPL1,BearPL2,BearPL3,BearPL4,BearPL5,,Trend Cases,", "Bull Trend Cases,BullTrPL1,BullTrPL2,BullTrPL3,BullTr PL4,BullTrPL5,", "Bear Trend Cases,BearTrPL1,BearTrPL2,BearTrPL3,B earTrPL4,BearTrPL5"); print(file("c:\tradestation\Short-Term Patterns.csv"),adate, ",", pattern, ",", bullcases+bearcases:8:0, ",", bullcases:8:0, ",", Bullreturns[2]:8:0, ",", Bullreturns[3]:8:0, ",", Bullreturns[4]:8:0, ",", Bullreturns[5]:8:0, ",", Bullreturns[6]:8:0, ",", bearcases:5:0, ",", Bearreturns[2]:8:0, ",", Bearreturns[3]:8:0, ",", Bearreturns[4]:8:0, ",", Bearreturns[5]:8:0, ",", Bearreturns[6]:8:0, ",,", bulltrendcases+beartrendcases:5:0, ",", bulltrendcases:5:0, ",", Bulltrendreturns[2]:8:0, ",", Bulltrendreturns[3]:8:0, ",", Bulltrendreturns[4]:8:0, ",", Bulltrendreturns[5]:8:0, ",", Bulltrendreturns[6]:8:0, ",", beartrendcases:5:0, ",", Beartrendreturns[2]:8:0, ",", Beartrendreturns[3]:8:0, ",", Beartrendreturns[4]:8:0, ",", Beartrendreturns[5]:8:0, ",", Beartrendreturns[6]:8:0); end; // end of trade if ndays > 6 then begin bullpattern = false; bearpattern = false; bulltrend = false; beartrend = false; ndays = 0; end;

To further confuse the issue, not all data vendors do what TradeStation does. Some vendors use last price traded for closing prices, and ignore the settlement prices. All this is a long way of explaining why you had a gold signal suddenly change on you. Now admittedly, for many traders, this issue might seem trivial. But for algo traders relying on accurate backtesting and real-time signal generation, it can be critical to understand the “last vs. settlement closing price” issue. The workaround for this issue is to make sure you understand what data you have before testing and trading. You can use either last price or settlement price and get correct calculations, as long as

For algo traders relying on accurate backtesting and real-time signal generation, it can be critical to understand the “last vs. settlement closing price” issue. you consistently use the same approach in your studies. A data issue like this is just one of the many tricks and pitfalls that algo traders can fall into. It definitely pays to understand your data before backtesting and trading.

January 2021 • Technical Analysis of

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Keeping The Momentum Going

Semi-Annual Gold Momentum Strategy: International Evidence by Massoud Metghalchi, PhD, with Ahsan Baig

In

the December 2019 issue of Technical Analysis of Stocks & Commodities, an article by Robert Tang proposed a yearly-based gold momentum strategy as follows: If the S&P 500 index performed better than gold in the current year, then in the next year, invest in the S&P 500; but if gold performed better, then the next year, invest in gold. (For his article, Tang used S&P 500 index data from Yahoo Finance and gold spot price from TheBalance.com. He further tested his strategy using SPY and GLD ETFs from 2006 to 2018, which showed similar results as for the index data.) Then, in the May 2020 issue of Technical Analysis of Stocks & Commodities, in my article “Variations On The Gold Momentum Strategy,” I applied Tang’s gold momentum

18 • January 2021 • Technical Analysis of Stocks & Commodities

strategy semi-annually, or every six months, as follows: • If the S&P 500 index performed better than gold in a six-month period, then in the next six-month period, invest in the S&P 500 • If gold performed better in a six-month period, for the next six-month period, invest in gold. This assumes that a trader can estimate the returns of the stock index and gold bullion a few minutes before the end of the six-month period, and that based on the performance of the stock index and gold bullion, the trader buys the best performer at the close of the last day of the sixth month. This process is repeated every six months.

Broadening the opportunities: An international look

For this article, we will apply the gold momentum strategy (GMS) semi-annually to several stock market indexes in industrialized countries, as well as to some well-known world indexes, in addition to the S&P 500 index. The stock indexes we will use are: Britain’s FTSE 100, France’s CAC 40, Germany’s DAX30, Switzerland’s SMI,

GOLD DRAGON: HELLORF ZCOOL/EURO CONTINENT: HARVEPINA COLLAGE: CHRISTINE MORRISON

If you find an investing strategy with an edge, it’s worth looking to see if you can broaden the strategy for more opportunities. Here, we’ll revisit the gold momentum strategy to test it on some worldwide markets this time. We think you’ll like the results.

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TRADING STRATEGIES

Individual industrialized countries results In the table in Figure 1, we present our results for individual industrialized countries. Note: For France, Germany, the Netherlands, and Spain, the country index and gold bullion index are in euro currency. For Japan, the Topix price index is in the local currency, yen; the gold bullion price index was converted to yen by using the Datastream exchange rate between the US dollar and yen. Similarly, for Switzerland, the SMI index is in local currency, the Swiss franc, and the gold bullion index price has been converted from USD to Swiss francs. Let’s discuss the French case. If a trader followed the efficient market hypothesis (EMH), the trader would buy and hold (B&H) the CAC 40 index; her average annual return would be 7.07 % over the 1992–2019 period with an annual standard deviation (risk) of 22.00%. If this trader only invested in gold, her annual average return would have been 7.49% with a risk factor of 13.52%. Over this period, the gold return has approximately the same return as the CAC 40 but has lower risk. However, if this trader followed the semi-annual GMS, this trader would have made an annual average return of 8.07% with an annual standard deviation of 14.08%. The risk-return trade-off for this trader using the semi-annual GMS would be better than that of the CAC 40, with higher return and lower risk. For Germany, we reach a similar conclusion: The B&H strategy has an annual average return of 10.60% with an annual standard deviation of 21.28%, all in local currency, the euro. Meanwhile, the semi-annual GMS for Germany has higher return (11.75%) and lower risk (17.24 %) than the B&H strategy for the DAX30 index. The conclusion is the same for the Netherlands, Spain, Switzerland, Japan, and the UK, in that a trader following the semi-annual GMS could beat the B&H strategy, all in local currency. The gain is very high for the Netherlands, Japan, and the UK. It should be noted that the annual average returns and the annual standard deviation of returns are estimated from semiannual returns. The estimations are as follows: Annual average = (1 + semi-annual average)2 - 1 Annual standard deviation = s emi-annual standard deviation * SQRT(2)

Annual Returns and Standard Deviation (%) 1992–2019 Index Gold GMS Return 7.06 7.49 8.07 France Stnd. Deviation 22.00 13.52 14.08 Return 10.60 7.49 11.75 Germany Stnd. Deviation 21.28 13.52 17.24 Return 2.80 5.60 6.86 Japan Stnd. Deviation 20.97 10.97 14.19 Return 6.79 6.93 13.85 Netherlands Stnd. Deviation 19.55 13.64 14.46 1994–2019 Return 9.12 7.49 12.87 Spain Stnd. Deviation 25.19 13.52 19.65 Return 7.59 5.38 7.76 Switzerland Stnd. Deviation 17.07 11.96 14.42 Return 4.62 7.70 9.19 UK Stnd. Deviation 13.43 13.71 12.61 FIGURE 1: GOLD MOMENTUM STRATEGY, RESULTS FOR INDIVIDUAL INDUSTRIALIZED COUNTRIES. Shown here is the risk-return trade-off for the test on individual countries and the semi-annual gold momentum strategy. Country

DATA FROM THOMSON REUTERS DATASTREAM

Spain’s IBEX, Netherland’s AEX, Japan’s TOPIX, and the S&P 500. The well-known indexes we will use are Dow Jones’s Euro Stoxx 50, MSCI’s Emerging Market, MSCI’s EAFE, and Dow Jones’ World Index. The index data are taken from Thomson Reuters’ DataStream from 1992 to 2019. The London gold bullion prices are taken from the Federal Reserve Bank of Saint Louis. Each country’s price index is in the local currency. The MSCI indexes and the DJ world index prices are in US dollar (USD) currency, and the Euro Stoxx 50 index is in euro currency. The Federal Reserve Bank of Saint Louis provides gold bullion prices in USD, euro, and pound sterling.

Annual Returns and Standard Deviation (%) 1992–2019 World Index Gold GMS 7.11 7.49 12.38 DJ Euro Stoxx Return Stnd. Deviation 18.80 13.52 15.16 50 Return 8.10 6.23 5.78 MSCI EM Stnd. Deviation 25.46 11.79 19.11 Return 5.29 6.23 6.66 MSCI EAFE Stnd. Deviation 17.02 11.79 11.42 Return 7.09 6.23 10.43 DJ World Index Stnd. Deviation 14.95 11.79 10.22 Return 8.72 6.23 14.47 S&P500 Index Stnd. Deviation 13.95 11.79 10.72 FIGURE 2: GOLD MOMENTUM STRATEGY, RESULTS FOR WORLDWIDE INDEXES. Shown here is the risk-return trade-off for various world indexes and the semi-annual gold momentum strategy.

Worldwide index results In the table in Figure 2, we present the risk-return trade-off for various world indexes and the semi-annual GMS. As we can see from Figure 2, if a trader follows the EMH and buys and holds the DJ Euro Stoxx 50 in euro currency, her average annual return over the 1992 to 2019 period would have been 7.11% with a measure of risk of 18.80%. Investing in gold in euros would have generated an annual average return of 7.49 % and a risk of 13.52%. However, if this trader switched every six months between the index and gold bullion index, this trader would have made an annual average of 12.38 % and a risk measure of 15.16%. The semi-annual Continued on page 37

Looking at the S&P 500 index test results, we see a very significant improvement in the risk-return trade-off. January 2021

• Technical Analysis of Stocks & Commodities • 19

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Have No Fear

Keeping emotion out of your trading decisions is always an important part of managing your trading. Understanding the biological processes behind our reactions to stimuli can help us find ways to counter unproductive emotions.

F

by Stella Osoba

ear is the one universal emotion that torpedoes many traders’ accounts. Unmanaged fear is the reason traders will often eventually quit trading. Fear is the underlying cause of many mistakes and countless unforced errors traders will make. Fear permeates our conscious and subconscious mind. All humans have an amygdala, which is thought to be the brain’s emotion center that governs our fear response. Thus, we may not be able to dispose of all fear, but we can learn to manage it intelligently so that it does not overwhelm us and thereby sink our trading accounts.

What is fear?

Fear can be defined as an unpleasant emotional feeling triggered by the perception of danger (in our case, trading 20 • January 2021 • Technical Analysis of Stocks & Commodities

losses). The danger can be real or imagined; the brain cannot distinguish between the two. Its close cousins, stress and anxiety, mimic fear in several ways. Stress is a reaction to excessive pressures or demands. Anxiety is the dread one feels when thinking about a potential threat; one which has not yet and may not materialize. It is the perception of and the belief in the imminence of the danger in all cases that is important. When it comes to trading, fear can arise as we debate whether to enter, stay in, or exit a position. The idea of trading losses is always very real, and for many of us it is often uppermost in our minds. We come to trading with the plan to make profits and to take money out of the market on a consistent basis. If we are very good at it and very lucky, the hope is that not only will we make money but also become rich in the process. For many, that plan never comes to fruition, and one reason for that is the handicap that fear exposes. It is therefore essential that if we are to not only stay in this trading game but also prosper, we must come to terms with the idea of fear and its role in our lives. We must learn to manage it and minimize its harmful expressions if we want to attain optimum trading results.

RYZHI/SHUTTERSTOCK

Managing Trading Fear And Stress

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TRADING PSYCHOLOGY

The biology of fear

Fear is an emotion that first appears as a thought in the thinking mind. We perceive something, and thinking gives it meaning. That meaning begins the process by which a series of chemical reactions interpret what had first appeared in our minds as a thought. Say for instance we are walking down a darkened street and see an object move in front of us. At first, we perceive it as possibly something that could be dangerous to us. The thoughts we ascribe to the situation before us causes us to feel fear. That feeling causes a series of chemical reactions to take place in the brain, weakening some network connections and strengthening others. The area in the front of the brain behind the cranium is called the prefrontal cortex. This area is thought to govern executive functions like short-term working memory, decision-making, and so on. When we feel fear, the chemical reactions in the brain cause the prefrontal cortex to shut down. Chemical messengers—neurotransmitters—send a message to the older regions at the back of the brain, such as the amygdala, that cause it to take over, triggering a panicked tide of emotion. Chemicals such as dopamine and norepinephrine switch off circuits in the prefrontal area required for higher cognition, while norepinephrine and cortisol cause the hypothalamus and other earlier evolved structures such as the amygdala to alert the rest of the nervous system to prepare for danger. This floods us with memories that are related to fear. The moment we realize that the object that moved in the darkness on the street was simply a barrel being rolled by the wind, we relax, and this causes enzymes to chew up those neurotransmitters, so that the shutdown does not persist. We then quickly return to our baseline, as the fear abates.

Thoughts are “ things”

The example just given is a simple illustration of why thoughts are, in a very real sense, things. They exist in a physical way. Thoughts control how our brains will react to outside stimuli. Thoughts control the creation and amount of particular chemicals created in our brains. Thoughts control how one region of the brain talks to another region of our brain. Thoughts control what region of the brain is currently in control or dominant and therefore how we are receiving and processing information from our environment. And what we perceive does not have to be true in order for the chemicals in our brains to trigger and react. We may in fact be perceiving information incorrectly and still end up with our amygdala on full alert, emotions taking control. Rational thought, which is handled by our prefrontal cortex, is shutting down. Researchers cannot know definitively why the brain evolved exactly the way it has. Why is it that our highest cognitive functions are weakened at the first signs of stress or fear? Why, during periods of stress or fear, does our orchestration of responses shift from the prefrontal cortex to the more primitive regions at the back of the brain? The more primitive areas near the brain stem can turn on a dime and set in motion the “fight-or-flight” response. This

Fear is an emotion that first appears as a thought. We perceive something, and thinking gives it meaning. might have developed as a mechanism to protect us from dangers seen in nature such as a snake about to bite or a bear about to attack. As we evolved, it was important for us to be able to perceive a threat quickly and react to it, in order to survive. This takes precedence over the deliberate, slowprocessing prefrontal cortex, which might make complex cognitive calculations about the likelihood of a snake bite killing us, or the best way to pacify a bear. This brings us to the next problem. In our highly developed present-day reality, we are far less likely to face the possibility that we may be eaten by a lion and far more likely to face problems that require higher-level cognitive abilities to resolve. The very same areas of the brain that tend to shut down during periods of stress or fear are the same areas of the brain that we need to solve many of the problems that confront us in our more highly evolved everyday realities. Our modern-day stresses most often involve situations that require us to make choices with thoughtful, deliberative analysis instead of with “fight-or-flight-or-freeze” reactions.

Stress: Chronic and acute

The effect of stress on the brain is much like that of fear. Stress can be acute or chronic. Both affect the functioning of our brain. Both acute stress and chronic stress lead to alterations in the brain’s architecture, although the effects of chronic stress are much more extensive and permanent than for acute stress. When we are unstressed, the circuitry in the brain connecting the prefrontal cortex and amygdala hum along contentedly. Our prefrontal cortex, or the executive center of the brain, allows us to keep our baser emotions and impulses in check. But studies have shown that keeping the circuitry of the brain functioning as it should is a fragile process. Even low levels of stress can create imbalances in the neurochemical environment in the brain. This imbalance weakens network connections, which in turn floods our brain with arousal chemicals that are released by neurons in the brain stem. As these signaling chemicals become elevated in the prefrontal cortex, they shut off neuron firing as the connection point between neurons is weakened. This causes network activity in the brain to decline. When this happens, the ability to regulate behavior is reduced. Oftentimes, our unforced trading errors can be linked to periods when we are under stress. Even small amounts of stress can affect our decision-making. Thus, when it comes to the myriad of factors we have to January 2021

• Technical Analysis of Stocks & Commodities • 21

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Oftentimes, our unforced trading errors can be linked to periods when we were under stress. observe and process in order to make trading decisions, to be able to handle them well and stay on task, we want to reduce stressors and control our sense of fear that can give rise to stress.

Cultivating a sense of control

Studies have shown that one of the best ways of countering the negative effects of fear and stress is to cultivate the belief that you have a sense of control over your immediate environment and over the choices available to you. In order to believe this, it is essential that you rehearse the very conditions that you fear happening, and rehearse what you will do in those situations. Training yourself to handle fearful situations can be habit-forming, and habits can change the circuitry of the brain. How does this work? Again, it is your thoughts that actually trigger signals in the brain. These signals are neurotransmitters in the prefrontal cortex communicating with the amygdala. And your thoughts are not what is actually happening in your environment; rather, your thoughts are your reaction to what is happening in your environment. Say for instance that you are in the market and get caught up in a nasty market reaction. You may panic and feel fear, and the brain will react by shutting down the prefrontal cortex as the amygdala floods the brain with chemicals such as catecholamine. That is the opposite of what you need to have happen to competently handle the situation that has arisen. You are no longer capable of rational thought. Instead, as fear grips you, you might recall past instances when you were fearful, and then you make highly emotional decisions. You wind up selling out of your positions in a panic, or you do nothing. Either way, you are not making calm, rational decisions. At this point, you may fail to see signals that could alert you as to the best course of action to take. Maybe there was buying late in the day, pointing to a market reaction as opposed to the start of a trend reversal. Because of the high levels of chemicals released during stress, the brain switches from the slower, more analytical regulation that is performed by the prefrontal cortex to the rapid-fire, reflexive response from the amygdala. Your emotions are now dictating your reactions.

Mindfulness

Mindfulness is focused attention. It is bringing our thoughts to the present and staying there without judgment. It means accepting what is happening in the present, moment by mo22 • January 2021 • Technical Analysis of Stocks & Commodities

ment, whether good or bad. It means cultivating the ability to stay present, with an open mind and no concern or judgement about how you are doing in the moment. Most of the time we are not in the present, we are not being mindful; we are either on autopilot or we are thinking about the past or the future. So for most people, the ability to stay mindful will take some work. But the ability to be mindful with some regularity allows you to begin to see the habitual pattern of negative thoughts and feelings that cause you to react in ways that hurt your trading and cause you to experience stress and/or fear. Being mindful of negative thought patterns can help you learn to avoid falling into these patterns. And this can help you to control your reactions.

Why you must sell to the sleeping point

It is much easier to practice mindfulness if we have prepared ourselves for market plunges by not carrying risk of ruin or almost-ruin positions in the first place. We must ensure that our position sizing is not too large for the size of our accounts so that whatever happens, we can weather the loss. Pioneer trader Jesse Livermore tells a story, which he attributes to Dickson G. Watts, that illustrates this point. The story was about a man who was very nervous. When his friend asked him what the matter was, he said: “I can’t sleep.” “Why not?” the friend asked. “I am carrying so much cotton that I can’t sleep thinking about it. It is wearing me out. What can I do?” “Sell down to the sleeping point,” replied the friend. The moral of the story is to avoid doing anything that can and will interfere with your sense of equanimity and that will keep you up at night. Trading is hard enough; don’t make it any harder by allowing the chemicals in your brain to join forces in the fight against your success.

The only thing to fear is fear itself?

The brain is a very powerful organ. It is made up of around 100 billion neurons. These neurons transmit messages to one another through a process resulting in the release of neurotransmitters. Neurotransmitters are chemical messengers that speak to the neurons, causing a specific response in the receiving neuron. The neuron is activated by the thoughts we produce to communicate through the neurotransmitter with other neurons. Sometimes neurotransmitters will stimulate neurons, making them more active, and other times the neurotransmitters will inhibit neurons, making them less active. What the neurons do depends on the signal that is received through your thoughts. Much is still unknown about how this complex organ called the human brain works, but research has shown that neurons control everything we do. It can therefore be liberating to know that we are in control. That is, we can choose to think the thoughts that will maximize our potential for right action when we trade. We can take control when we experience peContinued on page 56 https://libta.org

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Outperforming In The Midcap Space

ETF Midcap Growth Investing

L

by Leslie N. Masonson

ong-term and intermediate-term investors are always looking for areas of the market that offer consistent price performance with normal risk parameters. Market experts always try to pick next year’s winning category, but with limited success. One group of stocks that has seen market-beating performance over the past decade and intermediate periods has been midcap growth stocks. Here is a look at a handful of ETFs in that category to consider.

The midcap space

Investing in midcap stocks, as well as midcap equity ETFs and mutual funds, is often overlooked not only by the average investor, but also sometimes by the mainstream financial press. On the other hand, small-cap vehicles, and especially large-caps, have attracted most of the attention of retail and professional investors. Surprisingly, these “middle-of-theroad” midcaps have been very good performers among the 24 • January 2021 • Technical Analysis of Stocks & Commodities

three major investment categories over the past decade. Figure 1 shows the performance of the three capitalization (“cap”) sizes against market averages. Clearly, midcap and large-cap have run neck and neck, both way ahead of the S&P 500 and Dow Jones Industrials. Meanwhile, small-caps have underperformed.

Midcap ETF background

The midcap ETF arena contains stocks with a market cap of between $2 billion to $10 billion, but can be further divided into three types: basic or “plain-vanilla,” growth, and value. Interestingly, midcaps deliver the best characteristics of the capitalization sizes by offering higher growth rates than largecaps, coupled with less volatility than small-caps. SPDR S&P Midcap 400 (MDY) was the first midcap ETF offered on May 5, 1995, followed by iShares Core S&P Midcap’s birth on May 22, 2000. Next up were the triplets— iShares Russell IWP, IRS, and IWS on July 17, 2001. Based on their early start, these five ETFs have amassed the most AUM, in addition to Vanguard Midcap (VO) in second place with a later starting date of January 26, 2004. To gain a broad perspective on two midcap key data points, refer to Figure 2, which provides a list of the largest midcap ETFs based on assets under management (AUM). The top 10 midcap ETFs are listed in AUM order accompanied by their multiyear performance, and type. A first glance at the table

KENG MERRY DIGITAL CRAFT/SHUTTERSTOCK

One group of stocks with market-beating performance over the past decade has been midcap growth stocks. ETFs provide a way to invest in a basket of stocks in this or other categories. Here’s a look at a handful of ETFs in this category to consider.

https://libta.org

WHY TRADE ETFS?

indicates a wide variance in performance among these ETFs. But a closer look over the past one, five, and ten years shows that the worst performers have consistently been the value EFTs followed by the basic ETFs. However, the three growth-focused ETFs (that is, IWP, VOT, and IJK) have consistently excelled in price performance, even outpacing the S&P 500 and Dow Jones Industrials. ETF Report magazine lists 19 basic US ETFs, plus 9 growth and 7 value EFTs. Four of their growth ETFs are labeled as S&P 400 midcap growth (that is, RFG, IVOG, MDYG, and IJK), but they had inferior performance to the others in that category over five years, so they were excluded from my analysis in this article. Therefore, I retained JKH, NUMG, VOT, IWP, and FNY as the top growth performers. Figure 3 contains the names and tickers of the six reviewed ETFs. Note that I added Invesco S&P Midcap Momentum ETF (XMMO), a broad-based ETF, from the “basic” grouping to the mix because of its strong performance over three years. In summary, this article focuses on growth ETFs that are the “best” in their category over a decade.

Midcap growth ETFs For additional transparency purposes, I’ve provided a performance comparison of the top three ETFs in each midcap category in Figure 4. As you can observe, the best growth ETFs vastly outperform the others in the group. Data for the analysis of the ETFs in this column was provided by ETFAction. com, a platform that I reviewed in the May 2020 issue of this magazine. Previously, I used data from XTF.com for writ-

Total Return Ticker ETF Name 10 years iShares Morningstar Mid-Cap 308.30% JKH Growth ETF iShare Morningstar Small-Cap 255.90% JKK Growth ETF iShare Morningstar LargeCap 366.60% JKE Growth ETF 249.40%

SPY

SPDR S&P 500 ETF Trust

498.60%

QQQ

Invesco QQQ Trust

3 Years

5 Years

10 Years

28.51%

37.33%

20.73%

17.10%

15.07%

19.59%

27.90%

13.96%

14.05%

13.54%

26.90%

37.75%

22.16%

17.76%

16.65%

7.00%

14.74%

12.03%

12.59%

13.32%

32.62%

44.43%

25.03%

21.05%

19.56%

DIA

Name

Ticker

1 Year

5 years

10 years

AUM ($bill)

Type Basic

iShares Core S&P Mid-cap

IJH

-1.5%

7.5%

10.3%

$44.3

Vanguard Midcap

VO

6.5%

9.3%

1.6%

$35.3

Basic

iShares Russell Midcap

IWR

4.4%

8.9%

11.3%

$20.7

Basic

SPDR S&P Midcap 400 Trust

MDY

-1.6%

7.3%

10.1%

$14.9

Basic

iShares Russell Midcap Growth

IWP

22.8%

14.4%

14.1%

$13.3

Growth

iShares Russell Midcap Value

IWS

-7.3%

5.2%

9.2%

$9.8

Value

Vanguard Midcap Value

VOE

-8.1%

5.2%

9.8%

$9.3

Value

Vanguard Midcap Growth

VOT

21.9%

13.3%

13.3%

$8.5

Growth Growth

iShares S&P Mid-cap Growth

IJK

8.4%

9.3%

11.4%

$6.8

iShares S&P Mid-cap Value

IJJ

-12.4%

4.7%

8.9%

$4.4

S&P 500 ETF Trust

SPY

9.5%

11.6%

12.9%

$280.9

N.A.

SPDR DJ Ind, Average ETF Trust

DIA

-0.25%

11.0%

11.6%

$22.4

N.A.

Value

FIGURE 2: TOP 10 MIDCAP ETFS BY AUM. The growth category has clobbered not only the value ETFs and the plain-vanilla basic ETFs over multiple timeframes, but also the S&P 500 and Dow Jones Industrial Average. IWP, VOT, and IJK had the best performance. Ticker

iShares Morningstar Mid-Cap Growth ETF

JKH

Nuveen ESG Mid-Cap Growth ETF

NUMG

iShares Russell Mid-Cap Growth ETF

IWP

Vanguard Mid-Cap Growth ETF

VOT

Midcaps deliver the best characteristics of the capitalization sizes by offering higher growth rates than large-caps, coupled with less volatility than small-caps.

First Trust Mid Cap Growth AlphaFNY DEX Fund Invesco S&P MidCap Momentum XMMO ETF FIGURE 3: MIDCAP GROWTH ETFS. Six growth ETFs evaluated in this article are shown with their names and ticker symbols. JKH

1 Year

SPDR Dow Jones Industrial -1.12% 5.07% 8.14% 12.00% 12.09% Average ETF Trust FIGURE 1: ALL-CAP GROWTH ETFS VS. MARKET AVERAGES. Midcap and large-cap performance have exceeded that of small-caps, the S&P 500, and Dow Jones Industrial Average over multiple time periods. YTD midcap has been the leader. 218.81%

ETF Name

Performance Period

Y-T-D

NUMG

IWP

VOT

FNY

XMMO

VO

IWR

IWS

VOE

NUMV

Year-to-Date

28.51%

26.68%

18.78%

18.51%

16.49%

14.80%

4.10%

1.88%

-9.14%

-9.77%

-13.03%

1 Year

37.33%

33.78%

26.43%

25.27%

22.56%

20.69%

10.00%

7.85%

-4.12%

-4.74%

-8.36%

3 Year

20.73%

18.83%

16.70%

15.67%

14.14%

20.90%

8.87%

7.86%

1.85%

1.97%

1.33%

14.04%

18.63%

10.03%

9.62%

5.92%

5.96% N.A.

14.43%

12.00%

11.62%

9.54%

10.09% N.A.

5 Year

17.10%

15.04%

13.87%

10 Year

15.07%

14.44%

13.67%

Type of ETF

Growth

Growth

Growth

Growth

Growth

Basic

Basic

Basic

Value

Value

Value

FIGURE 4: MIDCAP PERFORMERS OF ALL TYPES. Here, the best performers among the basic, value, and growth ETFs are compared. Clearly, there is no contest that growth performance has been exceptional. January 2021

• Technical Analysis of Stocks & Commodities • 25

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340,000 shares, but inexplicably has the worst net asset flows at a Efficiency Score - FactSet 96 94 91 96 83 91 negative $57 million for the past Tradability Score - FactSet 98 91 84 98 94 95 year, the only ETF in the group Fit Score - FactSet 85 86 86 87 71 70 with a negative number. Its oneAUM ($MM) $8,884 $1,220 $206 $13,872 $436 $755 year and three-year performance Expense Ratio 0.07% 0.30% 0.40% 0.24% 0.70% 0.34% of 26.4% and 16.7% place it third Annual Yield 0.73% 0.51% 0.36% 0.85% 0.66% 0.49% in the group. And a low expense ratio of 0.24% places it second Avg. Daily Share Volume 135,569 26,892 24,777 339,808 63,014 85,534 behind VOT. Avg. Number of Holdings 157 161 58 342 225 77 IWP also has the highest Inception Date 08/17/2006 06/28/2004 12/13/2016 07/17/2001 04/18/2011 03/03/2005 FactSet scores on efficiency Performance 1 Year 25.3% 37.3% 33.8% 26.4% 22.6% 20.7% (96), tradability (98), and fit (87). Performance 3 Years 15.7% 20.7% 18.8% 16.7% 14.1% 20.9% These scores are explained on $-57 $73 $72 Net Asset Flows ($MM) - 1 Year $461 $355 $102 the FactSet website, but briefly, Net Asset Flows($MM) - 3 Years $980 $623 $112 $573 $231 $482 efficiency focuses on whether Std. Deviation 30-day annualized 20.0% 19.5% 20.9% 20.5% 22.5% 21.5% the ETF delivers on its promises FIGURE 5: COMPARISON OF MIDCAP GROWTH ETFS. JKH and XMMO are the preferred ETFs in this category, as without undue risk or cost, tradexplained in the conclusion of this article. ability means ability to obtain a fair market price, and fit assesses ing this column, but they ceased operations in early September how the portfolio measure ups to its stated objective. 2020. Figure 5 provides comparative data on the critical variables Vanguard Midcap Growth ETF (VOT) for the six ETFs. Common characteristics of all these ETFs VOT came in second with $8.8 billion AUM with an August include: open-ended investment company; 100% US equities; 2006 starting date, as well as with its 0.73% annual yield, and passively managed; offer quarterly dividends; benchmarked to a decent 136,000 daily trading volume. VOT tracks a marketS&P 500 Midcap, Russell 1000 Midcap Index or custom index; cap-weighted index of midcap growth companies selected by listed on NYSE Arca (except for FNY listed on Nasdaq and the Center for Research in Security Prices (CRSP). Moreover, NUMG listed on Cboe BZX US Equities Exchange); and not it came in first with its one- and three-year inflows of $461 part of the top 10 AUM grouping for all midcap ETFs (excep- million and $980 million, respectively. The low 0.07% expense ratio is the best of all. VOT also compiled almost identical tion for IWP, which is the fifth largest in total category). Blackrock is the issuer for IWP and JKH while Invesco FactSet scores as IWP, which is a big positive. However, its Capital handles XMMO. TIAA offers NUMG, First Trust one-year performance of 25.3% was only fourth best, while is the issuer for FNY. Lastly, Vanguard issued VOT. Each of its three-year performance of 15.7% was next to last. these ETFs offers a slightly different focus. iShares Morningstar MidCap Growth (JKH) JKH is third in AUM at $1.2 billion with a June 2004 birthdate. iShares Russell Midcap Growth (IWP) Let’s first review IWP, which was the first midcap growth It tracks a market-cap-weighted index of midcap companies ETF available and the behemoth of the group with a solid selected by Morningstar based on their growth characteristics. $13.8 billion in AUM gained over 19 years since its July 2001 Its 37% one-year performance places it first in this category, inception. This ETF is clearly a powerful asset gatherer. IWP as does its three-year 21% annual return. The daily trading tracks a market-cap-weighted index of growth companies from is low at 27,000 shares and its standard deviation of 19.5% is a swath of the 800 smallest Russell 1000 companies using in line with its brethren. JKH joins IWP and VOT as the biggest players in the arena two growth factors. Moreover, it sports the highest annual yield of the group and account for 69% of the midcap growth assets. VOT and at 0.85%, coupled with the highest daily trading volume of JKH have captured 81% of the one-year cash flows out of all six ETFs discussed, while IWP actually went negative for one year with outflows of $57 million. Category

VOT

JKH

NUMG

All six of these ETFs had their largest sector percentage positions in information technology. 26 • January 2021 • Technical Analysis of Stocks & Commodities

IWP

FNY

XMMO

Nuveen ESG Midcap Growth (NUMG) NUMG has the lowest AUM in the category at $206 million, as it is not a pure midcap growth play. NUMG tracks an index composed of midcap US companies with growth characteristics that meet specific “environmental, social, and governance” (ESG) criteria (which is a set of standards used as metrics in the socially conscious investing arena). Its 0.40% https://libta.org

expense ratio is second highest, while its 0.36% yield is the lowest along with its 25,000 daily trading volume, none of which are very impressive numbers. Its limited 58 portfolio holdings constitute a concentrated portfolio compared to the 342 holdings of IWP and about 160 for VOT and JKH. Performance-wise it is in third place with the third-highest cash inflows. iShares ESG Screened S&P Midcap ETF (XJH) is the latest midcap launch on September 22, 2020 and will compete directly with NUMG.

followed by industrials (12–17%). The fourth most invested sector was consumer discretionary (10–11%) with FNY at 14.6% and NUMG at 5.6% as the two outliers in either direction. For XMMO, the top 10 of its 77 holdings consisted of 29.5% of its portfolio. FNY had the lowest concentration in its top 10 at 8.4% with 225 holdings. NUMG had 27.8% of its 59 holdings in its top 10. IWP, VOT, and JKH had 12.3%, 14.3%, and 18.2% of their portfolios in their top-10 holdings. Figure 6 provides the top 10 tickers in each of the six ETFs evaluated. Notice that Twilo, Inc. (TWTO) was represented in four portfolios, while Lulelemon Athletica Inc. (LULU) and Veeva Systems Inc. (VEEV) were purchased in three. VOT invested about 1.4% in each of its top 10. IWP had about 1.2% in its top 10. JKH had 3% in Zoom Video Communications, Inc. (ZM), 2.3% in Square, Inc. (SQ), and about 1.5% in each of the other eight positions. NUMH had 3.4% in Twilio, Inc. (TWLO); 3% in Splunk, Inc. (SPLK); and 2.6% in Copart, Inc. (CPRT), Mettier-Toledo International Inc. (MTD), ANSYS, Inc. (ANSS), and Paycom Software, Inc. (PAYC); and 2.3% in Xylem Inc. (XYL) and Zebra Technologies Corporation (ZBRA). FNY had about 0.90% to 0.77% in its top 10 from high to low. Lastly, XMMO had 4% to 3% in its top four ETFs— GNRC, MPWR, SEDG, and QDEL—and about 2.45% in the remaining six holdings.

VOT JKH NUMG IWP FNY XMMO DLR ZM SNAP IDXX ENPH GNRC DXCM SQ TWLO DOCU DAR MPWR LULU MELI SPLK LULU INSP SEDG VEEV TWLO CPRT VEEV CHWY QDEL DOCU LULU MTD ALGN GNRC SAM SBAC DOCU SNSS CSGP SAM ENPH CMG IDXX PAYC CMG FRPT MASI TWLO SNAP CBRE ORLY WMS CRL CNC VEEV XYL KLAC TXG CGNX IDXX WDAY ZBRA TWLO SAIL MOH FIGURE 6: TOP 10 HOLDINGS FOR MIDCAP GROWTH ETFS. Shown here are the top 10 symbols in each of the six ETFs evaluated. In general, the largest sector holding is in information technology, followed by healthcare, industrials, and then consumer discretionary.

First Trust Mid Cap Growth AlphaDEX (FNY) FNY entered the category on April 18, 2011 gathering $436 million in assets. It tracks a tiered, enhanced, equal-weighted index of midcap growth stocks selected from the Nasdaq US MidCap Growth Index. This index is reconstituted and rebalanced quarterly. Eligible stocks are ranked on growth factors including three-, six- and 12-month price appreciation, salesto-price and one-year sales growth, and additionally on value factors including book value to price, cash flow to price and return on assets. All stocks are ranked on the sum of ranks for the growth factors and, separately, all stocks are ranked on the sum of ranks for the value factors. A stock must have data for all growth and/or value factors to receive a rank for that style. It has the second-lowest FactSet scores and the highest expense ratio at 0.70%. Annual yield of 0.66% is third highest and its 63,000 daily volume is low, but reasonable. Performancewise it came in dead last for three years at 14.1%, and next to last for one year at 22.6%. Its portfolio size of 225 places it midrange. Its alpha is 5.00 and beta is 1.05. Invesco S&P Midcap Momentum ETF (XMMO) XMMO, born in March 2005, was included from the plain vanilla category because of its top three-year performance record of 20.9%, beating all the others in the growth category. Unfortunately, its more recent one-year performance of 20.7% was the weakest of the six. Its FactSet efficiency and tradability scores are strong at 91 and 95%, respectively, but its fit score was the lowest at 70. XMMO tracks an index of S&P 400 midcap stocks based on momentum and weighted by market cap and momentum. Its expense ratio of 0.34% and 85,000 trading volume places it midrange while its annual yield of 0.49% places it in the bottom quartile. The portfolio is fairly concentrated with 77 issues.

Sector breakdowns and holdings

All six of these ETFs had their largest sector percentage positions in information technology (most in the 25% area) with JKH the outlier at 42%, followed by healthcare (20–24%), and

Conclusion

Based on a review of the key characteristics of the six midcap growth ETFs evaluated here, I’ve concluded that for investors, JKH just edges out XMMO on the basis of higher FactSet scores, better long-term performance (March 2, 2005 through Continued on page 39

The “efficiency” [rating] focuses on whether the ETF delivers on its promises without undue risk or cost, “tradability” means ability to obtain a fair market price, and “fit” assesses how the portfolio measures up to its stated objective. January 2021

• Technical Analysis of Stocks & Commodities • 27

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Candlesticks And Cryptos

A Quick Look At Approaching Cryptocurrencies

T

by Azeez Mustapha

wo of the most important success factors for a trader are their ability to assess and recognize risks, and their ability to evaluate and control their impulses. Both require separate types of skills, but there are some matches. In the trading process, you will encounter many opportunities to take risks. Of course, most of them are not worth considering, but from time to time you will find in the market something that you want to become a part of. If you are new to the world of cryptography, it is best to start your portfolio with the purchase of bitcoin (BTC). This is a common way to get your feet wet, as well as a great way to understand how cryptocurrencies are moving. Almost 28 • January 2021 • Technical Analysis of Stocks & Commodities

always, when bitcoin rises, all the other coins do the same. When bitcoin falls, the other coins also tend to fall. The point of this article will not be to discuss specific tools or strategies. Rather, it will seek only to introduce you to some of the structures relating to cryptocurrencies—a still new and developing field of investing.

Buy low, sell high

It sounds simple, but you will be surprised. Note that “buying at a low price” doesn’t mean buying really bad coins. You should only buy low prices in coins that have a proven history of good results but that were perhaps hit by a falling market. That way, you can know that not only is your coin falling but most likely, all the coins and tokens are falling. When the market recovers, your coin will also recover (most likely). Selling high is also a struggle. Most people tend to want to wait “just a little longer” to see how far the top goes. Bad idea. If you made a satisfactory return on your investment, pull it out and convert it into fiat. Do not be too greedy.

WIT OLSZEWSKI/SHUTTERSTOCK

Are candlestick patterns and basic technical analysis principles useful for trading cryptos? We take a look.

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CRYPTOCURRENCIES

Before we get into the technical analysis of it, I would just like to first make sure you understand how to read basic candlestick charts. So this will be just a brief reminder rather than a full review. Candlestick charts are made up of multiple bands of green or red (or any two different colors, but using green and red is usually the default setting). Green indicates that the price of a coin has risen since the last period the bar represents. The red bars represent the price which has declined since the last period. In trading terms, the main body of the candle is called the real body. On green candles, the base of the real body is sometimes called the opening price (the price at the beginning of the reference for this period) and the top of the real body is called the closing price (price at the end of the period). For red candles, this process is the opposite: The upper part is the opening price, and the lower part is the closing price. Any lines emerging from real bodies are called shadows or wicks. The upper part of the wick represents the highest price that the coin was bought during this period, and the lower part of the real body represents the lowest price that the coin was bought during this period. Wicks are rarely taken seriously, as they are often considered anomalies.

Technical analysis

TRADINGVIEW

Reading charts

FIGURE 1: CUP WITH HANDLE. In this pattern, the candles drop significantly for a long time, only to start a quick climb up immediately after the second ascent. This means a possible continued increase in value.

FIGURE 2: MEASURED UPWARD MOVEMENT. Candles begin to rise, stop to rest (where they move sideways), and then continue to rise upward. The fact that the asset has been moving sideways for a considerable time makes it more optimistic than the average upward pattern.

There are many technical analysis tools to help you become a successful trader on your journey. Technical analysis allows people to make informed forecasts regarding the future market based on its history. Many traders and investors argue that it is technical analysis that separates traders from standard players because technical analysis allows people to make knowledgebased decisions rather than impulse-based decisions. Several different types of technical analysis can be used to facilitate your transactions, and although more advanced methods are not needed, some basic information should not be ignored. People will think that technical analysis is about observing patterns in charts. And that’s certainly a big part of it, since technical analysts were, after all, the original chartists. But the term technical analysis also covers a lot more. One of the most basic things you can do that involves technical analysis is to look at the market capitalization of the coins and tokens

that interest you. Market capitalization is the price of asset X, the number of existing assets. The greater the market capitalization, the more effort will be required for the asset to grow in value. This is a more important factor to check than just the price of a coin. For example, newcomers could think that Ripple has many opportunities for growth as they looked at its price on July 13, 2018 of just $0.40, but the market capitalization is $17,291,808,853, which is huge. This means that price fluctuations in Ripple are slower than for coins and tokens with lower market capitalization. Thanks to this characteristic, traders love to find coins with low market capitalization. A market cap shows the rarity of coins. This is why some developers prefer to regularly “burn” their coins to increase the price.

Bullish chart patterns

It is well known that applying technical analysis patterns to cryptocurrencies is extremely difficult and temperamental, but January 2021

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Bearish chart patterns

The following patterns, as a rule, are the exact opposite of the bullish patterns: Inverted cup with handle: Candles rise significantly, then begin to fall, and in the end there’s an even steeper fall.

FIGURE 3: THREE POINTS OF RISING. Candles rise, then lower, rise again, lower, and finally rise for the last time (this time higher than the previous times). During each lift, candles move higher than the previous lift.

this does not mean that we should completely ignore patterns. Although I found that these types of patterns are not executable, this does not mean that they are unreliable. Here are some bullish charts you will encounter. With most exchanges you will be able to notice these patterns quickly, given that their interface is simple and intuitive: Cup with handle: This is the place where the candles on the chart drop significantly for a long time, only to start a quick climb up, immediately after the second ascent. This means a possible continued increase in value. Measured upward movement: Candles begin to rise, stop to rest (where they move sideways), and then continue to rise. The fact that the asset has been moving sideways for a considerable time makes it more optimistic than the average upward pattern. If an asset grows without interruption, it could be a sign of market manipulation or crowds. The fact that investors stopped for a moment and continued to invest is a sign of a high-quality coin or token. Three points of rising: This is when candles rise, then lower, rise again, lower, and finally rise for the last time (this time higher than the previous times). During each lift, candles move higher than the previous lift. Even though each accompanying fall is usually regarded as bad behavior, subsequent ascents continue to rise higher.

One of the most basic things you can do is to look at the market capitalization of the coins and tokens that interest you. 30 • January 2021 • Technical Analysis of Stocks & Commodities

Measured downward movement: Candles begin to fall, pause, and push sideways, then continue to fall. Traders see this as a terrible sign since a pause and a side push make the fall seem calculated and thorough (and not accidental).

Three downward points: In this pattern, candles rise, fall, rise again, lower again, perform one last rise, and then fall further than previously.

Finally

If you’ve come this far with building your theoretical knowledge of the markets, congratulate yourself. It’s not easy, and it’s even more difficult to follow and apply to live trading than it is in textbooks. My goal for this article has been to simply point out a little of what’s involved and to offer a few things you can apply to your trading in cryptocurrencies. Also, developing the right thought processes that go into trading is important to anyone’s dream of making a career out of cryptocurrency trading. Trading can be a difficult process, but it becomes easier the more you do it. Azeez Mustapha is an analyst at Instaforex Companies Group and a blogger at Advfn.com, and as well as a freelance author for trading magazines. He is a trading signals provider at some websites. He can be reached via email at azeez. mustapha@ analytics.instaforex.com.

Further reading

Mustapha, Azeez [2020]. “A Nondirectional Trading Strategy For Cryptocurrencies, Part 1,” Technical Analysis of Stocks & Commodities, Volume 38: February. [2020]. “A Nondirectional Trading Strategy For Cryptocurrencies, Part 2,” Technical Analysis of Stocks & Commodities, Volume 38: April. [2019]. “Spotting Imbalances In Novel Markets,” Technical Analysis of Stocks & Commodities, Volume 37: September.

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INTERVIEW

Portfolio Manager, Chartered Market Technician

Technical And Market Analysis With Kyle Crystal Kyle Crystal, CMT, CFTe, is a portfolio manager and technical/quantitative market strategist with over 15 years of experience formulating and implementing investment policy in various styles including long-short, global macro and long-only for single managed accounts as well as fund structures. A contributor to the CMT Association 2019 curricula, he has expertise in defining price objectives, support/resistance, and cycles. His skillset includes multiple timeframe analysis, market geometry, Elliott wave theory, momentum oscillators, Gann analysis, cycles, and candlesticks. His firm, Lakeshore Technical Analysis, LLC, provides technical and quantitative forecasting to institutional clients including portfolio managers, risk managers and wealth managers. Technical education is also offered to traders and analysts. Crystal is a Bloomberg research contributor and holds Series 65 and Series 3 licenses. More information on these services can be found at his website, www. lakeshoretechnicalanalysis.com. In addition to offering forecasting services, his related companies, Crystal Capital Advisors, LLC and Eastborough Capital, LLC, offer portfolio and money management services for both equity and futures markets. Stocks & Commodities Contributing Writer Karl Montevirgen interviewed Kyle Crystal in October 2020 to discuss his approach to analyzing the markets. Kyle, tell us a bit about your background. When did you first encounter the markets, and what set you on your current path as a technical analyst? I grew up around markets. My dad was a successful portfolio manager and I remember him bringing copies of his Daily Graphs chartbooks on our annual family vacation as a kid. I was lucky because I came right out of grad school and was able to work alongside him and learn the business. I am still lucky enough to be working with him today. After going through the 2009 bear market in equities I decided that I needed a skillset to make sure that I could not only avoid another disaster, but see it coming and profit from it. Initially, I started down the CFA (Chartered Financial Analyst) path but I decided the material was too removed from the dayto-day actions of the market. I called on someone who ended up becoming a real friend, Tim Brackett, now of The Mar-

ket’s Compass, who described himself as an “Elliottician” and he encouraged me to go through the Chartered Market Technician (CMT) program offered by the CMT Association (formerly known as the Market Technicians Association). It was a great recommendation. I first developed a base skillset and then I read day and night for about seven years (much to my wife’s chagrin!), and I studied with some brilliant people all while applying theory to the reality of managing capital. And now you operate a firm whose services are primarily focused on technical analysis. Not an easy task, considering that most research firms are fundamentally oriented. And your firm specializes in Elliott wave analysis, something that most mainstream financial institutions would find unfamiliar. How did you do it? It really came about after years of managing capital. Lakeshore Technical Analysis, LLC is a trade name of Crystal

32 • January 2021 • Technical Analysis of Stocks & Commodities

After the 2009 bear market in equities, I decided I needed a skillset to not only avoid disaster but to see it coming and profit from it. Capital Advisors, LLC, a Registered Investment Advisory (RIA) firm. So, Lakeshore was a natural extension of the skillset I developed managing money. My first client was a portfolio manager at a mutual fund who asked if I had a side service for analysis of commodity markets. Since then, I have grown through referral and cold calls, believe it or not. I love introducing myself to firms and seeing where the conversation leads. I also have a good sense of humor and that is required for cold calls! I’m curious—what is it like advising various types of institutional investment firms, many of whom are probably fundamentally based? Out of all the businesses I am involved https://libta.org

in, advising Lakeshore clients feels the least like work! I truly enjoy it. I think the key is 100% transparency and honesty. I work very early in the relationship to make sure clients understand the basic technical concepts that will be utilized in real-time. From that point forward, everything I bring into the analysis builds on the basics. As they see consistency and watch movements unfold, they gain trust in the methods. I’m bringing noncorrelated information to the table that cannot be generated from fundamental analysis. For instance, specific price targets, support/resistance, specific dates, and real-time action signals. This information is then used as a complement as well as a checksand-balance system against their own fundamentally based view. How do you view the relationship between fundamental and technical strategies? Fundamental strategies tend to be discretionary or have a discretionary component. Technical strategies may or may not have discretionary components. In my opinion, fundamentals provide the answer to the question why. Fundamentals are responsible for the long-term secular movement within markets and therefore fundamental analysis excels at helping one see through some of the noise found in the near-term market movements. Unfortunately, fundamental analysis offers little to no market timing or risk-management methods. Therefore, fundamentally based strategies can improve their timing and risk management through the addition of a technical overlay to help answer the question of when or even which (as in which market, which stock, which commodity market, etc.). Let’s talk about Elliott wave. Years ago I read the well-known Frost & Prechter 1978 book on Elliott wave analysis. Yes, it’s considered the “bible” of Elliott wave theory, serving as both an introduction to the approach as well as a documentation of how the technique is applied.

I enjoyed it but found it a little complicated when I studied with some brilliant it came to application. Given the complexities people, all while applying and potential variations theory to the reality of involved in the theory, managing capital. might this form of analysis present be a bit risky in the hands of less experienced technicians? think that’s what your question eludes When I first learned about Elliott wave, to. When you get into those situations I thought it was amazing and interest- where you are seeing more than two ing. And then about six months later, I possible scenarios, it’s best to put it all decided it was worthless. I probably went aside for the time being. Again, it is a back and forth on that several times over subjective tool open to interpretation, so a couple of years. I finally came around some situations will lack clarity. to finding it useful. But I think when trying to implement this approach, you So you find that Elliott wave analysis really have to work with somebody who has its usefulness but it shouldn’t be understands it. It’s hard to implement it treated as the holy grail, which lessjust by reading about it. experienced traders might uncritically assume. I can see how working with someone Right. Some people will think, “If I would be helpful. Elliott wave analysis can just go back and understand market is as subjective as an art but it’s as movements over the last 10 years, then I complex as a science, which makes it should be able to predict market movedifficult to work with. ment going forward.” But I think it’s Yes, that’s why it helps to sit alongside dangerous to think that. If you start trying someone and watch how they develop to predict large-degree market movetheir count. It is through this kind of ments, what this does to your thinking osmosis that you can start to really is it glues your brain into expectations understand how Elliott wave works. So that may not happen. in my opinion, it’s a valid approach and The reality is, there is no holy grail. can be very useful. But there’s no doubt You are going to make mistakes, and that it’s the most subjective tool in the no tool is perfect. When it comes to aptoolbox. plying Elliott wave analysis, I find it’s Because of that subjectiveness, it’s better not to start from the big picture, the first tool I will put aside if there is as is the general custom when analyzany ambiguity within price structure. ing the markets, but rather, start small However, here are two underlying ten- and work up. That way, the distance to dencies to understand about the market whatever negates your count is as small and why I think Elliott wave analysis as possible. This helps to minimize any can be useful: Basically, it’s helpful misinterpretation. to understand that market chop is esSo, to use Elliott wave effectively, sentially corrective, and that aggressive I’d say that first, you have to go from movement is essentially impulsive. And the small picture to the big picture. the more you get into it and study it, the And second, since it’s a subjective tool, more you can pick up on all those wave you must use confirming analyses. You variations. Basically, you will know what should be thinking, how can I confirm your preferred wave count is, and the my counts? What tools would be second-highest probability will be the complementary to this analysis? There alternative wave count. are some technicals that can help to But there will be periods in the market confirm whether we’re in a third wave, a where you will see conflicting scenarios, fifth wave, and so on. Using confirming and you may think to yourself, well, it tools can raise the probabilities of getting could be this, or it could be that. And I a good wave count. January 2021

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That’s interesting because people would typically approach this theory scaling the general down to the particular. But what you’re saying is to go the other way around, to go from the particular to the general. And also, you’re saying that if you come across too many variations that may conflict, you have to know when to toss out the count and put the analysis aside. That’s right, and then you have to lean on your other tools.

Let’s talk about cycles. If you put a bunch of cycles together,  I can imagine that a few of them might converge, or not. They can agree or disagree. How often do you come across conditions wherein cycles don’t really agree or are not compatible? And what do you do when that happens? To me, cycles are the least important

piece of the puzzle. The reason for that is because they can invert, as you’ve described. So in general, it’s the least important piece of information that I tend to care about. Generally, cycles produce a window of time where something may happen, meaning a change of trend. But whenever you create or identify a window for a change in trend, the market doesn’t have to turn there. So you need other non-correlated tools to add to your analysis to help indicate when the market may turn. So cycles can’t be used as an action signal. They are really just an additional layer of information to be aware of. There are different types of cycles, but they all function essentially the same way. And an example of a natural cycle such as seasonality would be, say, planting and harvest seasons? Yes, seasonality is the most common natural cycle. Something to be aware of is that seasonality charts are essentially an overlay of many years, including the outliers. If there’s an extreme outlier in a given year, it’s going to disproportionately influence the seasonality chart. So you have to

OPTUMA

I’m thinking about the chaotic events of this year and the markets. A lot has been going on that affects the markets, from quantitative easing (QE), to trade tensions with China, to the pandemic. I can imagine someone trying to plot a wave count amid the uncertainty. How do you work with so many unprecedented events? And does that tend to throw off the basic Elliott wave structure? It’s a great question but compliance restrictions prevent me from discussing current markets with any specificity and advising what I think. However, a lot of what I do at Lakeshore is to consult with people about current markets. I share

my thoughts, my read on the market, and where technicals suggest we are heading. I do that through conference calls and screen sharing to graphically demonstrate and annotate my interpretation of the market. That way, I can walk the client through what I am seeing and share my thoughts. By the way, it’s easy to go off into the weeds with wave counting. So I created a simple Elliott wave course for people who want to learn the technique. I offer it through my firm, Lakeshore Technical Analysis. In the course I provide examples using real market charts. I provide the basic guidelines, I provide the logic, I translate the line drawings to real market charts (Figure 1), and I provide a way to quiz yourself with example charts (Figures 2 and 3).

FIGURE 1: EXAMPLE OF THREE CORRECTIVE STRUCTURES. This chart displays the three simple corrective structures found within Elliott wave theory: the zigzag, flat, and triangle. The bar charts below each line chart above offer some real-life examples of the patterns.

34 • January 2021 • Technical Analysis of Stocks & Commodities

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break it down by different intervals of time, by plotting one year over another year, and then again over another year. Then we’ll look for correlation between the different years to identify which pieces of seasonality actually repeat. You can think you see a seasonal pattern if you look at a chart over a single period of time. But you have to compare year over year. If there’s variation at a point during the year that repeats over many years, it’s meaningful. So there are pieces of seasonality that are correlated and have high probability, and there are pieces of seasonality that are noncorrelated and have low probability. So if I understand you, you’re saying that you have to overlay many cycles to see what’s really correlated versus what’s not? To discern between more reliable patterns versus randomness?

FIGURE 2: THE EXPANDED FLAT. This chart illustrates an expanded flat. This is a common variation of the flat pattern where the “B wave” and “C wave” expand to new extremes before reversing.

FIGURE 3: THE CONTRACTING TRIANGLE. This illustrates the most common variation of the triangle pattern: a contracting triangle.

Yes, particularly for natural cycles. Each type of cycle has its own quirks that you have to work with.

The higher timeframe is essentially the trend. The movements and the smaller timeframe are the push and the pull within the trend.

Can you explain the different quantitative measures you employ in your approach (and services)? I use quantitative measures primarily within cyclical analysis. I work to identify three independent types of cycles on each market: fixed cycles (Hurst analysis), natural cycles (seasonality, etc.) and periodicity (sequencing). Fixed cycles and natural cycles can and should be verified through quantitative analysis (spectrograms, composite diagrams, correlation, etc.). I write about some of these methods and tools in the CMT level I and II curriculum that I authored.

Is there any software available to assist traders with either Elliott wave analysis or cycle analysis? Is it possible for software to help with these types of analyses? And if so, do you use such software yourself, or do you perform your analysis just by observation and your own study? Yes. I use Optuma software. It formerly was called Market Analyst, but now it’s called Optuma. They have a wonderful product and graphics. The graphic display is very important to me so that I can screen-share with clients to show them more clearly what I am seeing. You can customize the charts to your liking. It also uses an opensource coding language that allows you to go in and work with data in a custom way. The software can also label Elliott waves, although in order to interpret these labels, you still need an understanding of Elliott wave theory. Cycle-wise, it offers a spectrogram, and it also has some Hurst tools. These functions help you to look for cycles and seasonality that may be taking place in the market. You mentioned Hurst cycles. Yes, JM Hurst was the first to document fixed cycles with the aid of a computerized spectrogram and he created a January 2021

full technical system for trading fixed cycles. Sometimes people will refer to fixed cycles as Hurst cycles. While exceedingly rare, his correspondence course is very cool and required reading for serious market students. Can you talk about multi-timeframe analysis, which is one of the mainstays of your approach? As a broad statement, I use multiple timeframe analysis to provide clients with actionable information that is specific to the timeframe of their business. For instance, if a client is interested in buying soybean meal every two weeks to feed their hogs, they need to focus on the daily timeframe because buy/sell signals tend to last 1 to 2 weeks. However, a client who is interested in buying soybean meal every three months will be interested in technical signals originating from the weekly timeframe, as these signals tend to last 1.5 to 6 months. So the client dictates the timeframe. I generate the analysis from three independent noncorrelated perspectives: structure, momentum, and cycles. These methods of analysis are always employed in order of priority as mentioned above. I am also a fan of using Commitment Of Traders (COT) data when available. While I use the exact same approach on every market, I do tweak the tools to match the volatility characteristics of the market. I think multiple timeframe analysis is the most important piece of the puzzle. You need multiple timeframes in order to understand what’s happening in the markets, because the reality is that price is a fractal. Every movement is a piece of a trend that’s one timeframe higher. For Hurst cycles, for example, if you’re dealing with a 20-day-cycle, it’s heavily

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to keep it simple, although it could be more). It’s the push and the pull that tells It’s helpful to understand us what to do with the nearthat market chop is term movements. Do we essentially corrective, and want to ignore them? Or do aggressive movement is we want to take advantage of the situation and do the essentially impulsive. opposite of what the near term is doing? This is why I find multiple affected by the 40-day-cycle. Meaning timeframe analysis so useful. that the higher timeframe is essentially the trend. And the movements and the You wrote part of the CMT (Chartered smaller timeframe are the push and the Market Technicians) curricula? pull within the trend. Yes, that’s right. For an example, and keeping it simple, let’s consider a weekly chart and a daily Do you have anything available for chart. When it comes to commodities, readers to read of yours who are not I generally refer to the weekly time- necessarily taking the CMT course? frame as the trend. That is what most If you truly want to learn then I would people feel is the trend. When you get encourage you to reach out and drop a signal in a weekly timeframe, it tends me an email. I work with people of all to last between one-and-a-half months skill levels. to six months. Meanwhile, the daily As for published material, I’ve written timeframe is like the near-term push the cycle curriculum for Level I and II and pull of the next one or two weeks. technicians within the CMT program. So you really need two timeframes There’s a total of four chapters that disto understand the bigger picture. As cuss cycles. The first two chapters discuss an example, let’s say we’re in a bull the basics of cycle theory and principles trend, meaning the weekly timeframe as per the work of the late J.M. Hurst as is bullish, and the market is creating well as seasonality and detrending. The higher highs and higher lows. Let’s say second two chapters focus on tools used it’s midway up in its range, it’s healthy, to phase cycles as well as application and there are no issues. And then we through case studies. get a sell signal on the daily timeframe. As for other available writings, you What does that mean? It suggests “buy can read two articles that I co-wrote on the dip.” It suggests that in the near the Andrews pitchfork in issues 84 and term, the market is likely to go down, 85 (March 2018 and September 2018) possibly for one or two weeks. But in of The Journal of The Society of Techthe higher timeframe, the trend is up. So nical Analysis, which is the publication in a case like this, we might be looking from The Society of Technical Analysis to buy the dip. (STA), the UK’s professional body for Now think about a different scenario technical analysts. where the weekly timeframe has been Pitchforks are an amazing tool. And going up. But now, say it has a sell sig- most people don’t really focus on them, nal. Say your daily timeframe also has so I think they’re underappreciated. a sell signal. Well, that situation does There is no better tool for the diagonal not suggest “buy the dip.” It suggests we axis. I would suggest that people read may have a major high and so we need those articles and really try to think to react accordingly. about what the pitchfork formations are So it’s all about the context. The near- actually showing. term signals are all about the context of the trend, what is happening within the Isn’t there a lot more complexity to trend, and the push and pull of at least pitchforks than it seems at first? two timeframes (two timeframes in order It does involve degrees. You can think 36 • January 2021 • Technical Analysis of Stocks & Commodities

of this like Elliott wave—it’s fractal. Price structure is fractal. So we need tools that address fractals. Elliott wave analysis does that. Multiple timeframe analysis does that. Pitchforks do that. Elliott wave was designed for equity markets. After all, the developer of Elliott wave theory, R.N. Elliott, was sitting in a hospital bed studying stock charts, and what he discovered was essentially the fractal nature of it. He started to document the fractals he saw in the stock charts, which became the waves. The pitchfork was designed for commodity markets, in particular, the grain markets. It has a fractal concept to it. Let’s say the pitchfork is bullish—price is moving up within the pitchfork— and then all of a sudden it breaks the lower parallel and now price is out of the pitchfork. That’s the same concept of degree. So it essentially means that upward movement is completed and we could be in a new structure. So it could mean the impulse up is done and we’re now in a correction. So pitchforks are a great noncorrelated complementary tool to Elliott wave analysis. Anything else you’d like to mention? We know we are in the Wild West right now from a macroeconomic standpoint. Technical and quantitative analysis is likely to become more and more important to “getting it right” as time progresses. I would argue the current environment requires technical input and, from what I see, most firms agree with this view. I am involved in a lot of businesses: Lakeshore Technical Analysis (market forecasting/risk management), Crystal Capital Advisors (active equity management), Round Rock Advisors (comprehensive financial planning/wealth management), and Eastborough Capital (systematic commodity pool). All of them, while different, have a common theme: They use technicals as an input for decision-making. Working with markets is one of the most challenging jobs on earth, but if you decide you want to drive the bus, I would encourage you to study technicals and specifically to go through the CMT https://libta.org

program offered by the CMT Association. It offers good preparation. And I would just encourage anybody who wants to learn more about some of these technical analysis tools, or who feels they are overexposed to the volatility in the markets and they need help with this, to contact me. Finally, and perhaps most important, I’d like to mention a quick word of thanks here to my wife for her years of support and encouragement. What I do is not easy and it’s quite time-consuming. She has a level of patience that deserves acknowledgement and gratitude. Thanks, Meg! How can someone contact you? Anyone can make an inquiry through my website at http://www.lakeshoretechnicalanalysis.com. Thanks for speaking with us and for sharing examples of what you use to

analyze the markets. Good to hear about them. Karl Montevirgen is a content writer specializing in financial markets as well as the arts. His website is www.kontenthammer. com.

I’m bringing noncorrelated information to the table that cannot be generated from fundamental analysis.

Further reading

Crystal, Kyle, and Brackett, Timothy [2018]. “A Brief History Of The Development Of Median Line Analysis,” The Journal Of The Society Of Technical Analysts, March 2018 issue 84, The Society of Technical Analysts, https://www.technicalanalysts.com. [2018]. “Further Analytical Methods Using Median Line Analysis,” The Journal Of The Society Of Technical Analysts, September 2018 issue 85, The Society of Technical Analysts,

https://www.technicalanalysts.com. Hurst, J.M. [1970]. The Profit Magic of Stock Transaction Timing. Prechter, Robert, and A.J. Frost [1978]. Elliott Wave Principle, Elliott Wave International.

‡Optuma

‡See Editorial Resource Index

METGHALCHI & BAIG/GOLD Continued from page 19

GMS for the Euro Stoxx 50 has higher return and lower risk than investing in the Euro Stoxx 50. The same conclusion can be made for all the other indexes tested except the MSCI Emerging Market Index. For example, looking at the DJ World Index, with an average annual return of 7.09% in US currency, a trader could follow the semi-annual GMS and increase the return to 10.43% and at the same time lowering her risk from 14.95% to 10.22%. You can see from Figure 2 that the semi-annual GMS works for all major world indexes tested except the EM. S&P 500 index results Looking at the S&P 500 index test results in Figure 2, we see a very significant improvement in the risk-return trade-off. The semi-annual GMS applied to the S&P 500 index would enhance the S&P 500 return from 8.72% average annual return to 14.47 % average annual return, while the risk is reduced from 13.95% to 10.72%.

SuMMarY

In summary, we applied the semi-annual gold momentum strategy to various individual industrialized countries and a few well-known world indexes. Our results strongly support applying the semi-annual GMS for all the individual industrialized countries tested and all the world indexes tested except the MSCI Emerging Market Index.

We will apply the gold momentum strategy semiannually to several stock market indexes in industrialized countries, to some well-known world indexes, and to the S&P 500 index. Massoud Metghalchi, PhD, is a professor of fi nance at the University of Houston-Victoria. He may be reached at [email protected]. Ahsan Baig is a student at University of Houston-Victoria pursuing an MBA degree.

Further reading

Tang, Robert [2019]. “A Gold Momentum Strategy,” Technical Analysis of StockS & commoditieS, Volume 37: December. Metghalchi, Massoud [2020]. “Variations On The Gold Momentum Strategy,” Technical Analysis of StockS & commoditieS, Volume 38: May.

January 2021

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TARGET RICH TRADES MetaStock Add-on

4548 Atherton Drive, Ste 200 Salt Lake City, UT 84123 Phone: 800 882-3040 Web: www.MetaStock.com/ saleschat Requirements: MetaStock version 13 or higher, Windows XP or higher Product: MetaStock add-on for a trading system by Anne-Marie Baiynd Price: $499 one-time fee with 30day money-back guarantee by Barbara Star, PhD Target Rich Trades incorporates a trading system used by Anne-Marie Baiynd, the originator and CEO of The Trading Book.com. This MetaStock add-on combines her use of trend, support/resistance, and momentum within bullish and bearish price cycles to produce real-time buy and sell signals in all timeframes. A “target-rich trade” is an area on the chart that identifies the beginning of a potential price move that leads to new trading targets. Sometimes these are areas where price might reverse and sometimes they are areas where price continuation moves could be expected. The Target Rich Trades add-on issues signals for long and short reversal trades

as well as for long and short re-entry trades. Whenever a buy or sell signal triggers, an alert pops up on the screen that labels the type and direction of the signal. But more than merely signaling those trades, the algorithm automatically recognizes and labels support and resistance levels as well as the buy and sell zones.

Program components

The program opens with a price and volume chart template that displays a special moving average to represent the overall general trend. The chart springs to life when an expert advisor is added. It populates the chart with signals and text labels, along with colored price bars that show buying and selling strength.

Target Rich Trades incorporates a trading system used by AnneMarie Baiynd. A color ribbon under the chart identifies the current shorter-term trend (see Figure 1). Diamond shapes mark support and resistance levels. When the algorithm detects a buy or sell zone that follows

a diamond shape and all the underlying conditions for a trade have been met, a text label, a directional arrow, and an initial stop-loss sign appear on the chart. Trade re-entries also display the buy or sell label and arrow but occur after a failed entry, one that initially had been stopped out, or after a failed pullback. The support and resistance diamonds provide the initial trading targets but also could form part of an additional trading strategy in which the diamonds themselves serve as both entries and exits. For example, traders looking for long entries in an uptrending market could use the green diamonds as entry or re-entry signals and red diamonds as places to take profit. Commentaries A commentary feature located within the expert advisor provides the trader with information about the current trend, the price level of both the last support and the last resistance areas, and whether a new or open trade currently exits. Once a trade is triggered, the commentary conveys information about how to proceed, with suggestions for exits or profit-taking. Trade-management suggestions are also given for open trades, those that are currently in progress. An initial stop-loss price, which adjusts

FIGURE 1: TARGET RICH TRADES FOR EASTMAN CHEMICAL. As seen on the daily chart of Eastman Chemical, Target Rich Trades automatically displays both longer-term and current price trends, support and resistance levels, and buy and sell zones.

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automatically as the trade progresses, is added to the commentary. Trade preparation Even though a buy or sell signal flashes, traders are advised to avoid blindly entering a trade. Trade preparation is so important to Baiynd that she outlines a procedure to follow prior to entering a trade. Price slope, relation to moving averages, and support/resistance location are among the subjects she discusses to assess the probability of a successful trade outcome.

Scanning and backtesting

The program includes scans for long entry signals, short entry signals, and recent inflections. The scan lists those symbols that have signaled either a buy or re-entry buy and a sell or re-entry sell, as well as price levels where stops, confirmations, and closes occur. The recent inflection scan is unique because its function is not to filter for buy or sell signals. Instead, it includes every symbol on the chosen list and tells how

many bars have passed since posting the last support or resistance diamond and also the price when that happened. The backtester can test one symbol or multiple symbols. It can display a bar graph to show winning and losing trades as well as a report summarizing performance activity for each symbol

A “target-rich trade” is an area on the chart that identifies the beginning of a potential price move that leads to new trading targets. which includes profit or loss, reward to risk ratio, and the dates when orders were considered, placed or canceled. It can even plot an equity line on the price chart of any symbol tested.

In tune with the basics

stray from the path of sound technical chart analysis and rely on guesswork or media attention for selecting and entering a trade. Target Rich Trades replaces guesswork with the key technical analysis components, scanning, and trading signals necessary for a solid, real-time trading method that works in all timeframes for both beginning and experienced traders. Barbara Star, PhD, is a Contributing Writer to Technical Analysis of Stocks & Commodities magazine. She can be reached at 818 224-4070 or by email at [email protected].

Resources

Gibby, Jeff [2018]. “Anne-Marie’s Target Rich Trades for MetaStock,” video, https://www.youtube.com/ watch?v=vvXs9cumuWc ‡MetaStock ‡TheTradingBook.com ‡See Editorial Resource Index

Too often, traders are tempted to

MASONSON/WHY TRADE ETFS? Continued from page 27

November 4, 2020) with a total return of 445% vs. 408%, 2020 current-year performance (through November 4) of 31% vs. 17%, 1.6 times the AUM, lower standard deviation, higher cash inflows, and a more diversified portfolio with 161 positions. XMMO had a higher daily trading volume of 85,000 vs. 27,000 and more concentrated holdings with 77 positions, though neither is a very significant factor. Although Vanguard’s VOT had the lowest expense ratio, highest cash inflows, significantly more AUM, and five times VOT’s daily trading volume, it severely lagged on long-term performance from August 2, 2006 to November 4, 2020 of 309% vs. 378% for VOT, and short-term 2020 YTD performance of 20% vs. 31% for JKH. iShares Russell Midcap Growth (IWP), the AUM leader of the group, with a number of leading factors such as highest annual yield and largest number of portfolio positions, also had negative cash inflows of $57 million compared to VOT’s massive inflows of $461 million. Moreover, on a long-term basis from July 2, 2004 through November 4, 2020, IWP gained 457% compared to 526% for JKH, and since the beginning of 2020 was underperforming JKH by 10 percentage points. NUMG also underperformed JKH since December 15, 2016 by 17 percentage points and in 2020 by 1.5 percentage points.

For investors, JKH just edges out XMMO. Are you interested in learning more about using exchange traded funds (ETFs) in your trading? Leslie N. Masonson, an active ETF trader, is president of Cash Management Resources, a financial consulting firm that focuses on ETF relative strength and sector strategies. He is the author of Buy—DON’T Hold: Investing with ETFs Using Relative Strength To Increase Returns With Less Risk, and All About Market Timing, as well as Day Trading on the Edge. His website is buydonthold.com, where he writes a monthly blog. To submit topics for future columns, reach him at [email protected].

resources

www.blackrock.com • vanguard.com • ftportfolios.com • www.invesco.com • www.nuveen.com

January 2021 • Technical Analysis of

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Explore Your Options GOT A QUESTION ABOUT OPTIONS? Jay Kaeppel has over three decades of experience in the options markets. He was a head trader for a CTA firm, an options trading software developer, and is a portfolio manager for an investment management firm. He also spent several years writing a weekly column titled “Kaeppel’s Corner” and now publishes a blog, “Jay On The Markets” (http://jayonthemarkets.com). He is the author of several books, including The Four Biggest Mistakes In Option Trading; The Option Trader’s Guide To Probability, Volatility, And Timing; and Seasonal Stock Market Trends. Send your questions or topic suggestions to Jay Kaeppel at jaykaeppel@ gmail.com. Selected questions will appear in a future issue of S&C.

• The trade will make money if the underlying stock price remains within the breakeven prices through expiration. If price moves significantly outside of this range, then losses can occur. So you should have some reason to believe that price will remain within a given range before entering the trade. • You are trading two options and you may decide to exit the trade prior to option expiration. As a result, it is important to consider the width of bid/ask spreads on the options you

are trading. Ideally, you will want to focus on heavily traded, highly liquid options with tight bid/ask spreads. • Changes in implied volatility can have a profound impact on a calendar spread once the trade is entered. A rise in volatility will typically help a calendar spread and a decline in volatility will typically hurt a calendar spread. As a result, it is typically preferable—though certainly not

A calendar spread can offer a trader the opportunity to make money even when a stock “goes nowhere.” required—to enter a calendar spread when implied volatility is on the low end of the historical range.

Example trade

For our example trade we will use ticker UBER. Figure 1 displays an UBER

price chart along with implied volatility (black line). Note that the stock price has support around $28.42 and resistance around $38.50. Figure 2 displays the history of implied volatility (IV) for 90+ day options on UBER. Current IV is not necessarily “high” nor “low” compared to its historical range. In recent years it has been as low as low the 40s and spiked to 140% during the COVID-19 selloff in early 2020. It currently stands in the mid 50s. Our example trade involves: • Buying 1 Jan15 2021 put @ $3.33 (with 112 days left until expiration) • Selling 1 Nov06 2020 put @ $2.25 (with 42 days left until expiration) The particulars appear in Figure 3 and the risk curves in Figure 4. Some key things to note: • This trade costs $108 to enter on a 1-lot. This is the maximum risk on the trade.

PROFITSOURCE BY HUBB

SIDEWAYS STOCKS: AN OPPORTUNITY TO USE CALENDAR SPREADS? A number of stocks that I am following seem to spend a lot of time going sideways and trading in a range. Is there a low-risk way to profit from that scenario using options? A calendar spread can offer a trader the opportunity to make money even when a stock “goes nowhere.” Likewise, if properly positioned, it can offer a significant rate of return and a relatively low dollar risk. As with most option strategies, the key is to understand what “makes it tick.” A standard at or near-the-money put calendar spread involves buying a put option with a strike price near the current price of the underlying stock in a furtherout expiration month and simultaneously selling another put option at the same strike price in a closer expiration month. The basic premise of a calendar spread is that the shorter-term option will experience time decay and lose time value at a much faster rate than the longer-dated option. But there are a few important things to consider before entering an at-the-money calendar spread:

Jay Kaeppel

FIGURE 1: UBER PRICE CHART. In this example price chart of UBER, you can see identifiable support & resistance levels.

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• The approximate maximum profit is $197. • The breakeven points for this trade are $28.38 on the downside and $39.42 on the upside. Note that these breakeven prices are beyond the support and resistance levels we identified earlier. The hope is that the support and/or resistance levels will serve as a “brake” to halt any advance or decline before price moves beyond our breakeven points. • The theta for this trade is $1.94. This implies that this trade will gain $1.94 in value each day due solely to the passage of time—that is, each day, the shorter-term option will lose roughly $3.60 in value and the longer-term option will lose only roughly $1.70 in value. Since we are short the former and long the latter, we will gain $3.60 on the shorterterm option and lose only $1.70 on the longer-term option. • The vega for this trade is $2.82. This implies that if implied volatility rises by 1 full percentage point, then the position will gain $2.82 in value and vice versa. If volatility rises, the call we hold long will gain more time value than the call we are short and if volatility declines, the call we hold long will lose more time value than the call we are short.

OPTIONSANALYSIS.COM

Explore Your Options

FIGURE 2: IMPLIED VOLATILITY. Shown here is an example of implied volatility on 90+-day UBER options.

FIGURE 3: PUT CALENDAR SPREAD. This shows the particulars for the example put calendar spread on UBER stock.

Note that greek values are not static and will change as time goes by and price and volatility levels change. But for now, these are the values we have to work with in assessing the viability of this particular position.

Position management

From a risk standpoint, the key consideration is what to do if price exceeds the breakeven points. There is no correct answer. The choices are: • Exit as soon as a breakeven price is violated • Exit as soon as a support or resistance price is violated • Establish a wider “uncle” point in order to give price some opportunity to work its way back into the profit range if it only temporarily pierces support/

FIGURE 4: RISK CURVES. This graph shows the risk curves for the example put calendar spread on UBER stock.

resistance or breakeven points • One other technical—but important—consideration is to remember that if the short put is in-the-money at expiration, you will be required to buy 100 shares of stock at the strike January 2021

price. You could simply exercise your long call to offset, but more typically a trader will want to exit the position prior to getting involved in exercise. Continued on page 45

• Technical Analysis of Stocks & Commodities • 41

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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, where she also works as a broker. She has written five books on futures and options trading, with the latest being Trading Commodity Options...With Creativity (July 2020), as well as A Trader’s First Book On Commodities (third edition, October 2017) and Higher Probability Commodity Trading (July 2016). Garner also authors widely distributed e-newsletters; for a free subscription, visit www.DeCarleyTrading.com. To submit a question, email her at [email protected] or via www.DeCarleyTrading.com. Selected questions will appear in a future issue of S&C.

THE QUALITY OF FILLS Does the commodity brokerage make a difference in the quality of the fill? Also, why aren’t orders always filled as expected? The biggest lesson new traders learn is there are no free lunches. Moreso, the commodity markets are not charities. Orders will only be filled if there is a willing and able market participant to take the other side of the trade at the desired price. The market does not owe any of us anything, not even liquidity or fair pricing. Additionally, in the United States, brokerage firms do not play a role in making markets. Instead, they merely connect retail traders to a centralized exchange via trading platforms, a trading desk, or an individual full-service broker. Trades are sent for execution through the proper chain directly to the exchange’s trade-matching software (or open outcry pit in rare cases). Accordingly, aside from minimal differences in software and connection speeds, there is no difference in fill quality when entering an order into a trading platform at one brokerage versus another. In other words, a trader who experienced slippage on a stop-loss order, or who wasn’t filled on a limit order they believed should have been, would have had the same experience if they were using any other brokerage. Thus, switching shops isn’t going to make the difference they are hoping for. For futures traders, fill quality is less of an issue. For instance, technically, a limit order is one that buys or sells a futures contract at a better price than the current market price. An order is only owed a fill if the futures price trades through it, but on many occasions, the markets are

amply liquid to enable a trader to get filled if the market merely reaches the noted price. For example, if a corn trader works an order to sell a March contract at $4.10 (a dime higher than the current price of $4.00), the trader desires to go short corn at $4.10 or higher if the market rallies to the noted price. It is unlikely she will receive a fill higher than a price of $4.10 but she is only owed a fill if the price prints one tick above $4.10. If the futures market reaches precisely $4.10

Orders will only be filled if there is a willing and able market participant to take the other side of the trade at the desired price. and drops, the trader might or might not receive a fill on the order. Whether or not the order was filled would depend on the number of orders from buyers at that price and time. This makes sense, since the exchange cannot force another trader to accept the trade at the price you desire; the transaction can only take place if both traders are inclined to execute at that price and time. Something to be aware of regarding stop orders (which is an order to buy or sell a futures contract if the price gets worse): The CME Group exchanges have a system referred to as “protection functionality for market and stop orders.” This program defines protection points representing prices the exchange deems to be unacceptable slippage for a stop order (or market order). If the market

42 • January 2021 • Technical Analysis of Stocks & Commodities

Carley Garner

is volatile, thinly traded, or both, it is possible a working stop order cannot be filled at a reasonable price (as determined by the protection points). In this situation, stop orders go unfilled and become limit orders. While this sounds like a luxury because it can reduce slippage on most occasions, it can also go the opposite way. In late October, the S&P 500 gapped lower by 20.00 points from a Friday close to the Sunday night reopen. One of our brokerage clients had a sell stop working at a price on the lower end of the gap. Sadly, the CME exchange’s protection functionality resulted in that order not being filled; instead, it became a limit order to sell at the previous stop price, which was never filled at all. This was particularly painful because the S&P 500 futures proceeded to collapse 100 points ($5,000 per contract) in the session. Luckily, this was a stop order to enter a short trade, not one to protect a long trade. It is a little easier to stomach missing out on a big profit than it is dealing with a failed stop-loss order and sitting on a large loss. For options traders, the issue of getting orders filled at an agreeable price is more of a challenge. This is because options are not traded as fluidly as futures contracts are. Thus, the lighter liquidity means fewer parties to take the other side of trades resulting in wider bid/ask spreads and the necessity to accept price slippage to get an order filled. In normal market conditions and in a reasonably liquid commodity market, the slippage from the price needed to execute and one that a trader might deem fair is minimal. But on occasion, volatility arises, causing Continued on page 45 https://libta.org

LAUNCH OF WEBSITE TO OFFER COURSES, EDUCATION, DATA FOR HEDGED TRADING The new www.hedgedtrading.com website from StockOdds (mystockodds. com) offers courses on advanced hedged trading and basket trading. HedgedTrading.com is a data and education service for equities and CFD traders. It seeks to offer insights for long and short basket traders. Basket trading is an approach that seeks to offer a way to cover rising and falling industries without having to be perfectly right on one stock selection. The courses are designed to encourage the development of a probability mindset and a probability-based trading approach through the use of statistical odds to achieve relative performance yield. The courses instruct on ways to combine long and short positions as a way to increase the chances of success over the long sample. Hedges are used to help insulate the trader from market moves and adverse events. The courses offer advanced strategies, money management techniques, dealing with outliers, balancing positions based on dollars, beta, volatility, and more. Students can learn to design baskets that may be right for their skill set, account size, and timeframe.

StockOdds Predictive Analytics & Probability Data is offered as a service to provide predictive analytics data as a source of trading ideas for students and hedge traders. Its indicators provide signals as well as probabilities of what may arise after the signals, based on the strategies used and trade duration. www.hedgedtrading.com

RISK AND DECISION-ANALYSIS PLATFORM FOR ASSET ALLOCATION Since extreme, black-swan events are by definition unexpected, ironically, these types of events should be expected to happen over the course of decades, according to many advisors. Probability simulations can be helpful when preparing to address unexpected market fluctuations, and asset allocation is known to be a primary factor in longterm portfolio outcomes. To provide insights to help manage long-term investment portfolios in ways that conventional static models cannot address, Palisade Company provides a risk and decision-analysis software platform. It offers a suite of analytics tools including: @RISK for Monte Carlo simulation; PrecisionTree for decision trees; TopRank for “what-if” sensitivity analysis; NeuralTools for predictive neural networks; StatTools for statistical analysis & forecasting; Evolver for sophisticated optimization; and RISKOptimizer for Monte Carlo simulation & optimization. @RISK Monte Carlo simulations examine a range of possible outcomes and how likely each is to occur. The program supports probabilistic, or stochastic, asset allocation models by incorporating longer-time horizons and realistic probability distributions associated with asset classes. @RISK provides a method to forecast risk and prepare portfolios for the unexpected, helping investors to turn risks into opportunities. The company is offering an on-demand webinar (https://www.brighttalk.com/ webcast/18521/450696) titled “Asset Allocation Modeling with Black Swans Using Monte Carlo Simulation” that demonstrates how @RISK can be used to create financial models that give investors a more realistic view of the

risks in their portfolios by incorporating simulated distributions that more closely resemble reality and allow for “fat tails.” This is in contrast to a traditional approach to asset allocation that uses efficient frontier models to try to find the optimal portfolio mix with the lowest possible level of risk (standard deviation) for its level of return (mean). Headquartered in Ithaca, NY, Palisade Company seeks to help companies optimize their decision-making in many industries ranging from finance to oil and mineral exploration, real estate to heavy manufacturing, pharmaceuticals to aerospace, as well as for business schools around the world.

www.palisade.com, https://www.brighttalk.com/ webcast/18521/450696

IN-DEPTH GUIDES FROM IG MARKETS IG is an online forex trading provider and forex brokerage, offering a trading platform and customizable apps, as well educational and other services. In 2019 IG expanded into the US with its forex services, offering access to over 80 currency pairs. IG has compiled several in-depth guides, available from www.ig.com/ uk, including the following topics: top trading books; the future of trading; psychology in trading; politics and the markets; the impact on coronavirus on the stock market; the economic impact of coronavirus; and paychecks of world leaders. www.ig.com, www.ig.com/uk

January 2021

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TRADING ON MOMENTUM

Sideways Markets

Buy Support, Sell Resistance Here’s what to look for if you want to trade within a price channel.

In

by Ken Calhoun

nontrending markets, it can be frustrating to get stopped out when trends do not continue in your favor. The S&P 500 index has been in a sideways consolidation from September through November 2020, as seen in Figure 1 (SPY). In this situation, you may find it more successful to buy pivots off of support levels and sell into resistance.

When price action cycles

This strategy gives you clarity on exactly where to enter and where to exit, without the guesswork. the middle of the trading range, as seen by the blue and red 50 and 100 SMA (simple moving average) lines, illustrated in Figure 1. Developing a trading plan designed to capitalize on price action in

this situation requires the use of trailing stops. We want to buy once price has pivoted off the prior day’s low for at least one day, and sell once price action has pulled back off of resistance for at least a day.

Step-by-step action plan

Here’s how you can start using this strategy: Step 1: After a sustained downtrend of at least 10 days, look for a technical pivot signal, such as the hammer seen on September 21 in Figure 1, and enter your position. Step 2: Set your exit target at just beneath the prior high; which is $360 in this example.

eSIGNAL

up and down Sideways markets are always difficult to trade. From a technical analysis perspec-

tive, the most important factor to keep in mind is the trading range: The larger the range, the better. It is also important to note that standard moving averages won’t be nearly as useful in this type of market as they are in trending markets, since moving averages will appear in

FIGURE 1: BUYING SUPPORT, SELLING RESISTANCE (SPY). This shows an example of buying off of obvious support levels within the channel.

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Step 3: Either close the entire position or scale out of it once price action has gotten close to the prior high. Step 4: Repeat this for as long as price action cycles up and down in a defined channel.

Insights: Why this

technique works As with most trading strategies, support & resistance levels are obvious and traded by the majority of professional traders. The most important thing to keep in mind is exiting on time. In working with many traders over two decades, I’ve consistently found this to be the single biggest error that traders make. They don’t sell into resistance and instead

wait far too long to exit their trades to book a profit. Another reason why this strategy is valuable is it gives you clarity on exactly where to enter and where to exit, without the guesswork that causes missed trade opportunities.

Trade management tips

Because the duration of the trades is relatively brief, it is important to manage both your entries and exits with a bit more precision compared to trading trending instruments. From a size perspective, you do not have the luxury of time to scale in and build larger positions. So you need to initiate your trade with full size from the beginning once it has pivoted off of support. If you do scale in and out, limit

You need to initiate your trade with full size from the beginning once it has pivoted off of support. it to a single additional trade while price action is still in the trading channel. Ken Calhoun moderates a live trading room for active traders. He is the founder of TradeMastery.com, an interactive webinar site for active traders, and is a UCLA alumnus.

Explore Your Options

KAEPPEL

Continued from page 41

On the flip side, in terms of profittaking, a trader will likely need to exhibit some patience since most of the profits will accumulate as the short option nears expiration. One final wild card to consider: If IV declines after the trade is entered, our long option—because it has a higher

the two breakeven points. Conversely, if IV increases, the net effect would be to widen the range between the two breakeven points as our long call would gain more time premium than our short call.

If properly positioned, it can offer a significant rate of return and a relatively low dollar risk. vega—would be more adversely affected than our short option. The net effect would be to narrow the range between

‡ProfitSource (HUBB); ‡Optionsanalysis.com

‡See Editorial Resource Index

FUTURES FOR YOU GARNER

Continued from page 42

wider spreads between the bid and ask price of an option. As a result, another trader might not be willing to take the other side of a trader’s order at the expected fair price. This can be frustrating, but it shouldn’t be; as mentioned before, the markets are not a charity. In fact, they are closer to the opposite. Markets don’t volunteer to help those in need; they forcefully accept donations of the

unsuspecting. Let’s consider an example: A trader wishing to execute a butterfly option spread in silver might estimate a fair price of the spread to be 26 cents. Yet, the bid price of the spread might be 24 cents and the ask 28 cents. Unless the trader is willing to buy the ask price (28 cents), he should not expect a fill, nor get upset and feel victimized when one doesn’t occur. This is because at least one other trader is willing to take the other side of the trade at 28 cents, but there are currently no traders willing to January 2021

do it at 26 cents. Just like the buyer of this spread wouldn’t appreciate being forced to pay 28 cents, the seller of the spread cannot be required to accept a lower price than they desire. Again, for a transaction to occur, both parties must be willing and able. A trader should never assume they can buy or sell an instrument at the price their software claims is fair; market participation at any given price is voluntary, not obligatory.

• Technical Analysis of Stocks & Commodities • 45

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The focus of Traders’ Tips this month is Perry Kaufman’s article in this issue, “A Fresh Look At Short-Term Patterns.” Here, we present the January 2021 Traders’ Tips code with possible implementations in vari-

ous software. The code for the following Traders’ Tips selections is posted here:

F TRADESTATION: JANUARY 2021 TRADERS’ TIPS CODE In his article in this issue, “A Fresh Look At Short-Term Patterns,” author Perry Kaufman introduces some test methods to analyze various short-term price patterns to determine how they work with various stocks and ETFs. The analysis includes results with and without a trend filter. The trend filter used is an 80-period simple moving average and the article also provided the criteria for the various patterns used to determine if an entry is triggered. Shown here is the indicator code based on the author’s work. A simple Plot statement was added to indicate that the code was running, but the code is designed to export the results to a text file. Indicator: TASC JAN 2021

• Traders.com → S&C Magazine → Traders’ Tips At Traders.com you can also right-click on any chart to open it in a new tab or window and view the chart at a much larger size. The Traders’ Tips section is provided to help readers 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.

bulltrendcases( 0 ), beartrendcases( 0 ), cday( 0 ), comphigh( 0 ), complow( 0 ), outsidebull( false ), outsidebear( false ), ratio( 0 ), ndays( 0 ), adate( " " ), size( 0 ), back1( 0 ), back2( 0 ), back3( 0 ), back4( 0 ); arrays: bullreturns[6]( 0 ), bearreturns[6]( 0 ), bulltrendreturns[6]( 0 ), beartrendreturns[6]( 0 );

// TASC JAN 2021 // PJK Short-Term patterns // Look at reliability of short-term patterns with // and without a trend filter. // Look at using noise as a qualifier // Copyright 2020, P.J.Kaufman. All rights reserved inputs: trendper( 0 ), usekeyreversal( false ), useislandreversal( false ), usecompression( 0 ), usegaps( 0 ), useoutsideday( false ), usewiderangingday( 0 ), forecast( 5 ), investment( 10000 ); variables: trend( 0 ), pattern( " " ), bullcases( 0 ), bearcases( 0 ), compression( false ), gap( false ), outsideday( false ), widerangingday( false ), bullpattern( false ), bearpattern( false ), bulltrend( false ), beartrend( false ),

FIGURE 1: TRADESTATION. Shown here is a TradeStation daily chart of SPY with the indicator applied. The plot is used to indicate that the code is running and does not plot a significant number in terms of the article content. The code is designed to export information to a file.

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// trend if trendper > 0 then begin trend = average( close, trendper ); end; //============================================ // 3-day compression //============================================ if usecompression = 3 then begin cday = truerange[3]; compression = truerange < cday and truerange[1] < cday and truerange[2] < cday; end; //============================================== // key reversals //============================================== if usekeyreversal and ndays = 0 then begin pattern = "Key Reversal"; // key bearcases reversal if high > high[1] and low < low[1] and close < low[1] then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment / close; if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // key bullcases reversal else if high > high[1] and low < low[1] and close > high[1] then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment / close; if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; //=============================================== // island reversals //=============================================== if useislandreversal and ndays = 0 then begin pattern = "Island Reversal"; // bearcases island reversal if low > high[1] and close < open then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment / close;

if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // bullcases island reversal else if high < low[1] and close > open then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment / close; if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; //=============================================== // compression //============================================== if usecompression > 0 and ndays = 0 then begin pattern = "3-Day compression"; back4 = truerange[4]; back3 = truerange[3]; back2 = truerange[2]; back1 = truerange[1]; compression = back4 > back3 and back4 > back2 and back4 > back1; if compression then begin comphigh = Highest( High[1], usecompression ); complow = Lowest( Low[1], usecompression ); // bearcases compression if close < complow then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment / close; if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // bullcases compression else if close > comphigh then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment / close; if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; end; //================================================ // Outside day (or wide ranging day) with close in // upper/lower 25% January 2021

• Technical Analysis of Stocks & Commodities • 47

https://libta.org

//================================================ if (useoutsideday or usewiderangingday <> 0) and ndays = 0 then begin if useoutsideday then pattern = "Outside Day" else pattern = "Wide Ranging Day"; outsidebull = high > high[1] and low < low[1] and close > 0.75 * ( high - low ) + low; outsidebear = high > high[1] and low < low[1] and close < 0.25 * (high - low ) + low; ratio = 0; if usewiderangingday <> 0 then begin ratio = truerange / avgtruerange( 20 ); end; // bearcases outside day if outsidebear and ( ratio = 0 or ratio > usewiderangingday ) then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment / close; if trend < trend[1] then begin beartrend = true; beartrendcases = beartrendcases + 1; end; end // bullcases outside day else if outsidebull and (ratio = 0 or ratio > usewiderangingday) then begin ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment / close; if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; //================================================ // Gap opening with profits in direction of the gap //================================================ if usegaps > 0 and ndays = 0 then begin pattern = "Gap Opening"; ratio = ( open - close[1] )/avgtruerange( 20 )[1]; // downward gap if ratio < 0 and -ratio >= usegaps then begin ndays = 1; bearcases = bearcases + 1; bearpattern = true; size = investment / close; if trend < trend[1] then begin

48 • January 2021 • Technical Analysis of Stocks & Commodities

beartrend = true; beartrendcases = beartrendcases + 1; end; end else if ratio >= usegaps then begin // bullcases gap ndays = 1; bullcases = bullcases + 1; bullpattern = true; size = investment / close; if trend > trend[1] then begin bulltrend = true; bulltrendcases = bulltrendcases + 1; end; end; end; //================================================ // accumulated profits over next 5 days //================================================ if ndays > 1 then begin if bullpattern then begin bullreturns[ndays] = bullreturns[ndays] + size * ( close - close[ndays-1] ); end; if bearpattern then begin bearreturns[ndays] = bearreturns[ndays] + size * ( close[ndays-1] - close ); end; if bulltrend then begin bulltrendreturns[ndays] = bulltrendreturns[ndays] + size * ( close - close[ndays-1] ); end; if beartrend then begin beartrendreturns[ndays] = beartrendreturns[ndays] + size * ( close[ndays-1] - close ); end; end; if ndays > 0 then begin ndays = ndays + 1; end; //================================================ // summary //================================================ if lastbaronchartex then begin adate = ELdatetostring( Date ); // print headers to file print( file( "c:\tradestation\Short-Term Patterns.csv"), "Date,Pattern,Cases,Bull Cases,BullPL1,BullPL2," + "BullPL3,BullPL4,BullPL5,Bear Cases,", "BearPL1,BearPL2,BearPL3,BearPL4,BearPL5,," + "TrendCases,", "Bull Trend Cases,BullTrPL1,BullTrPL2,BullTrPL3" + ",BullTrPL4,BullTrPL5,", "Bear Trend Cases,BearTrPL1,BearTrPL2,BearTrPL3," https://libta.org

+ "BearTrPL4,BearTrPL5" ); // print the data to file print( file( "c:\tradestation\ Short-Term Patterns. csv"), adate, ",", pattern, ",", bullcases+bearcases:8:0, ",", bullcases:8:0, ",", Bullreturns[2]:8:0, ",", Bullreturns[3]:8:0, ",", Bullreturns[4]:8:0, ",", Bullreturns[5]:8:0, ",", Bullreturns[6]:8:0, ",", bearcases:5:0, ",", Bearreturns[2]:8:0, ",", Bearreturns[3]:8:0, ",", Bearreturns[4]:8:0, ",", Bearreturns[5]:8:0, ",", Bearreturns[6]:8:0, ",,", FIGURE 2: THINKORSWIM. Here is an example of the study. The returns calculation from 1 to 5 days for bullish key reversals is shown bulltrendcases+beartr in the upper pane with bearish key reversal returns in the lower pane. Log scale is enabled for the price pane to view the price moves endcases:5:0, ",", bulltrendcases:5:0, ",", more distinctly. Bulltrendreturns[2]:8:0, ",", Bulltrendreturns[3]:8:0, ",", Bulltrendreturns[4]:8:0, ",", Bulltrendreturns[5]:8:0, ",", Bulltrendreturns[6]:8:0, ",", beartrendcases:5:0, ",", F THINKORSWIM: JANUARY 2021 TRADERS’ TIPS CODE Beartrendreturns[2]:8:0, ",", We have put together a study based on the article in this issue Beartrendreturns[3]:8:0, ",", “A Fresh Look At Short-Term Patterns (With And Without A Beartrendreturns[4]:8:0, ",", Beartrendreturns[5]:8:0, ",", Trend Filter)” by Perry Kaufman. Beartrendreturns[6]:8:0 ); We built the study referenced by using our proprietary end; //================================================ // end of trade //================================================ if ndays > 6 then begin bullpattern = false; bearpattern = false; bulltrend = false; beartrend = false; ndays = 0; end; Plot1( Close ); // dummy plot to show code is running

To download the EasyLanguage code for TradeStation 10, please visit our TradeStation and EasyLanguage support forum. The files for this article can be found here: https:// community.tradestation.com/discussions/Topic.aspx?Topic_ ID=190289. A sample chart is shown in Figure 1. 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. —Chris Imhof TradeStation Securities, Inc. www.TradeStation.com

scripting language, thinkscript. To ease the loading process, simply click on http://tos.mx/pnEzI0G or enter it into the address into setup → open shared item from within thinkorswim, then choose view thinkScript study and name it “ReturnsCalculationForPricePatterns” or whatever you like so you can identify it. You can then add the study to your charts from the edit studies menu from within the charts tab. The example chart shown in Figure 2 is the returns calculation from 1 to 5 days for bullish key reversals (upper pane) and bearish key reversals (lower pane). Also, log scale is enabled for the price pane to see the price moves more distinctly. The price pattern to be used, its direction, whether or not to apply the trend filter, and investment size are all configurable via inputs. Please see Perry Kaufman’s article for more information on how to read the study. —thinkorswim A division of TD Ameritrade, Inc. www.thinkorswim.com

F WEALTH-LAB: JANUARY 2021 TRADERS’ TIPS CODE The Wealth-Lab strategy code for the short-term pattern scanner described by Perry Kaufman in his article in this January 2021

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https://libta.org

issue, “A Fresh Look At Short-Term Patterns,” is presented here. With parameter sliders at the bottom left of your Wealth-Lab workspace, the included strategy demonstrates how to switch between the patterns interactively when viewing a chart. Dragging the pattern slider to the left or to the right will change between the six choices and make the chart update with backtested trades. For example, Figure FIGURE 3: WEALTH-LAB. Sample entries are shown on a daily chart of QLD. Data provided by Yahoo! Finance. 3 illustrates one bearish and two bullish key re /* key reversal */ versal trades created on the next open following the pattern bool keyRevBear = High[bar] > High[bar - 1] && Low[bar] < Low[bar - 1] && Close[bar] < Low[bar - 1]; and exiting 3 days after. Through another parameter slider, bool keyRevBull = High[bar] > High[bar - 1] && you can control exits after N bars in a trade. Low[bar] < Low[bar - 1] && Close[bar] > High[bar - 1]; To avoid copy/paste, hitting Ctrl-O and choosing down /* island reversal */ load in Wealth-Lab gets you the downloadable strategy un bool islRevBear = Low[bar] > High[bar - 1] && der the “Chart patterns” folder. Close[bar] < Open[bar]; WEALTH-LAB CODE using System; using System.Collections.Generic; using System.Text; using System.Drawing; using WealthLab; using WealthLab.Indicators; /* Requires Community Components installed */ using Community.Components; namespace WealthLab.Strategies { public class TASCJan2021 : WealthScript { private StrategyParameter paramPattern; private StrategyParameter paramExitDays; public TASCJan2021() { paramPattern = CreateParameter("Pattern", 1, 1, 6, 1); paramExitDays = CreateParameter("Exit after", 3, 1, 10, 1); } protected override void Execute() { var _pattern = paramPattern.ValueInt; var _exitAfter = paramExitDays.ValueInt; int atrPeriod = 20, maPeriod = 80; double tick = Bars.SymbolInfo.Tick; var atr = ATR.Series(Bars, atrPeriod); var trendFilter = SMA.Series(Close, maPeriod); for(int bar = GetTradingLoopStartBar( Math. Max(atrPeriod,maPeriod)); bar < Bars.Count; bar++) {

50 • January 2021 • Technical Analysis of Stocks & Commodities

bool islRevBull = High[bar] < Low[bar - 1] && Close[bar] > Open[bar];

/* outside day */ bool outsideBull = this.isOutsideBar(bar) && Close[bar] > Low[bar] + ( 0.75 * (High[bar] - Low[bar])); bool outsideBear = this.isOutsideBar(bar) && Close[bar] < Low[bar] + ( 0.25 * (High[bar] - Low[bar])); /* wide range day */ var ratio = TrueRange.Series(Bars)[bar] / atr[bar]; bool isWRBBull = outsideBull && (ratio > 1.5); bool isWRBBear = outsideBear && (ratio > 1.5); /* 3-day compression */ bool compression = CumDown.Series(TrueRange. Series(Bars), 1)[bar] >= 3; /* gap open */ bool isGapUp = (this.isGap(bar) == CommonSignalsEx. GapType.FullUp) && (Open[bar] > Close[bar] + 0.5 * atr[bar]); bool isGapDown = (this.isGap(bar) == CommonSignalsEx.GapType.FullDown) && (Open[bar] < Close[bar] + 0.5 * atr[bar]); /* trend filter */ bool isBullish = Close[bar] > trendFilter[bar]; bool isBearish = Close[bar] < trendFilter[bar]; if (IsLastPositionActive) { /* Exit after N days */ Position p = LastPosition; if (bar + 1 - p.EntryBar >= _exitAfter) ExitAtMarket( bar + 1, p, string.Format("After {0}", _exitAfter)); } else https://libta.org

{ switch (_pattern) { case 1: if( keyRevBear && isBearish) ShortAtMarket( bar + 1, "KeyRevBear"); if( keyRevBull && isBullish) BuyAtMarket( bar + 1, "KeyRevBull"); break; case 2: if (islRevBear && isBearish) ShortAtMarket( bar + 1, "IslRevBear"); if (islRevBull && isBullish) BuyAtMarket( bar + 1, "IslRevBull"); break; FIGURE 4: NINJATRADER. The PJKShortTermPatterns indicator is displayed on a daily MSFT chart from November 2019 to Novem case 3: ber 2020 with TrendPer = 2 and Use Key Reversal = true. if (outsideBear && isBearish) ShortAtMarket( bar + 1, Patterns,” is available for download at the following links for "OutsideBear"); NinjaTrader 8 and for NinjaTrader 7: if (outsideBull && isBullish) BuyAtMarket( bar + 1, "OutsideBull"); NinjaTrader 8: www.ninjatrader.com/SC/January2021SCNT8.zip break; NinjaTrader 7: www.ninjatrader.com/SC/January2021SCNT7.zip case 4: if (isWRBBear && isBearish) ShortAtMarket( bar + 1, "WRBBear"); if (isWRBBull && isBullish) BuyAtMarket( bar + 1, "WRBBull"); break; case 5: if (compression) { if(BuyAtStop(bar+1, Highest.Series(High,3) [bar], "CompressionBull") ==null) ShortAtStop( bar + 1, Lowest. Series(Low, 3)[bar], "CompressionBear"); } break; case 6: if (isGapUp && isBullish) BuyAtClose( bar, "GapUp"); if (isGapDown && isBearish) ShortAtClose( bar, "GapDown"); break; default: break; } } } } } }

Once the file is downloaded, you can import the indicator into NinjaTader 8 from within the control center by selecting Tools → Import → NinjaScript Add-On and then selecting the downloaded file for NinjaTrader 8. To import in NinjaTrader 7 from within the control center window, select the menu File → Utilities → Import NinjaScript and select the downloaded file. You can review the indicator’s source code in NinjaTrader 8 by selecting the menu New → NinjaScript Editor → Indicators from within the control center window and selecting the PJKShortTermPatterns file. You can review the indicator’s source code in NinjaTrader 7 by selecting the menu Tools → Edit NinjaScript → Indicator from within the control center window and selecting the PJKShortTermPatterns file. NinjaScript uses compiled DLLs that run native, not interpreted, which provides you with the highest performance possible. A sample chart displaying the indicator is shown in Figure 4. —Chris Lauber NinjaTrader, LLC www.ninjatrader.com

—Gene Geren (Eugene) Wealth-Lab team www.wealth-lab.com

F NINJATRADER: JANUARY 2021 TRADERS’ TIPS CODE The PJKShortTermPatterns indicator, as presented in the article by Perry Kaufman in this issue, “A Fresh Look at Short-Term

F NEUROSHELL TRADER: JANUARY 2021 TRADERS’ TIPS CODE A short-term pattern trading system such as the one discussed by Perry Kaufman in his article in this issue can be easily implemented in NeuroShell Trader by combining a few of NeuroShell Trader’s 800+ indicators. January 2021

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For this example, we’ve used the island reversal pattern, but you can choose from any of the 90 candlestick and traditional trading patterns included in NeuroShell Trader. To create the trading system, 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: [All of which must be true] Key Reversal: Bullish Flag(High,Low,Close) A>B(Momentum(Avg( Close,80),1),0)

FIGURE 5: NEUROSHELL TRADER. This NeuroShell Trader chart shows the key reversal pattern applied to Walmart. SELL LONG CONDITIONS: [All of which must be true] the article “A Fresh Look At Short-Term Patterns” BarsSinceFill>=X(Trading Strategy,3) SELL SHORT CONDITIONS: [All of which must be true] Key Reversal: Bearish Flag(High,Low,Close) A=X(Trading Strategy,3) POSITION SIZING METHOD: Fixed Dollar 10,000.00 Dollars

After entering the system conditions, you can also choose whether the parameters should be genetically optimized. After backtesting the trading strategy, use the detailed analysis button to view the backtest and trade-by-trade statistics for the system. NeuroShell Trader users can go to the Stocks & Commodities section of the NeuroShell Trader free technical support website to download a copy of this or any previous Traders’ Tips. —Marge Sherald, Ward Systems Group, Inc. 301 662-7950, [email protected] www.neuroshell.com

F THE ZORRO PROJECT: JANUARY 2021 TRADERS’ TIPS CODE Japanese traders developed candlestick charts and candlestick patterns in the 17th century. Some traders believe that those patterns are still valid today. But since the 21stcentury financial markets are quite different from the Kyoto rice market of 300 years ago, new patterns were invented. In 52 • January 2021 • Technical Analysis of Stocks & Commodities

in this issue, Perry Kaufman tests several new patterns with major US stocks and indexes, and with an additional trend filter. The 6 patterns tested were key reversal, island reversal, outside days, wide-ranging days, 3-day compression, and gap opening. All are calculated from the previous 3 or 4 candles and give a buy or sell signal. Here’s how they look coded as indicators in C: var cdlKeyReversal() { if(priceHigh(0) > priceHigh(1) && priceLow(0) < priceLow(1)) { if(priceClose(0) < priceLow(1)) return -100; // sell if(priceClose(0) > priceHigh(1)) return 100; // buy } return 0; } var cdl3DayCompression() { vars TRs = series(TrueRange(),4); if(TRs[0] < TRs[3] && TRs[1] < TRs[3] && TRs[2] < TRs[3]) return 100; else return 0; } var cdlIslandReversal() { if(priceLow(0) > priceHigh(1) && priceClose(0) < priceOpen(0)) return -100; // sell if(priceLow(1) < priceHigh(0) && priceClose(0) > priceOpen(0)) return 100; // buy else return 0; } var cdlOutsideDay() https://libta.org

{

if(priceHigh(0) > priceHigh(1) && priceLow(0) < priceLow(1)) { if(priceClose(0) < 0.75*priceLow(0) + 0.25*priceHigh(0)) return -100; // sell if(priceClose(0) > 0.25*priceLow(0) + 0.75*priceHigh(0)) return 100; // buy } return 0; }

Symbol SPY QQQ IWM AAPL AMZN GE WMT TSLA

cases 265/82 235/68 149/82 198/60 158/34 129/89 82/80 126/62

Day 1 1071/-604 -695/-2639 956/-121 3994/-1240 -367/-2245 -283/655 -678/-1166 5200/-5307

Day 2 3290/50 -293/-5285 1113/1497 3198/-2862 1686/-5913 -2680/4809 -111/-508 13983/-5237

Day 3 5615/-2910 1977/-9691 2096/179 4214/-5816 1232/-6319 -3070/4147 -82/-1009 21086/-4802

Day 4 5675/-3681 5434/-11494 2909/2132 8094/-5577 4469/-7560 -2321/6090 -1140/-713 33549/-2898

Day 5 6978/-5998 6820/-13151 4466/1356 11433/-6916 8272/-6198 -1472/2813 464/-1995 43231/-2216

FIGURE 6: ZORRO. Example result for the gap opening pattern with trend.

var cdlWideRangeDays() { if(TrueRange() > 1.5*ATR(20)) return cdlOutsideDay(); else return 0; } var cdlGapOpening() { var Ratio = (priceOpen(0) - priceClose(1))/ATR(20); if(Ratio >= 0.5) return 100; if(Ratio <= -0.5) return -100; return 0; }

Following the convention of the classic candle patterns from the TA indicator library, the pattern functions return 100 for a bullish pattern, -100 for a bearish pattern, and 0 for no pattern. We will test the patterns with IWM, AAPL, AMZN, GE, WMT, and TSLA stocks, as well as SPY and QQQ index ETFs. There are two differences from the test in Kaufman’s article. First, we will use not merely price differences, but will simulate real trades with spread and commission. So the returns will be a bit worse but more realistic. Second, we test from 2010 to 2020 to help ensure that the results of all assets are comparable. Some of them, like TSLA, didn’t exist before 2010. Here is the test script:

rt); printf(" %s: %.0f/%.0f ",Algo, WinLong-LossLong,WinShort-LossShort); } }} // asset/algo loops }

Here are some explanations for the code: At the start of the run() function, the pattern and the trend mode are set up. For convenience we’re using a function pointer that is set to the pattern function to be tested. The test uses two nested loops, first for selecting the stocks, and second for selecting the trade lifetime to get the results from a 1-day trade up to a 5-day trade. The predefined Itor2 variable is the iterator of the second loop and runs from 0 to 4, so we just use it to set the LifeTime variable for the subsequent trade. The number of stocks purchased is calculated in the same way as in Kaufman’s article and code. The results are printed in the EXITRUN at the last day of the simulation. The table in Figure 6 shows an example result for the gap opening pattern with trend. The numbers are the returns of long/short trades in US dollars. The pattern functions and the test script can be downloaded from the 2020 script repository on https://financialhacker.com. The Zorro platform can be downloaded from https://zorro-project.com. —Petra Volkova The Zorro Project by oP group Germany www.zorro-project.com

var pattern(); // function pointer void run() { pattern = cdlGapOpening; // place pattern function here bool WithTrend = true; // false without trend BarPeriod = 1440; // 1 day StartDate = 2010; // TSLA went public in 2010 var Investment = 10000; while(asset(loop("SPY","QQQ","IWM","AAPL","AMZN","GE","W MT","TSLA"))) { vars Trend = series(SMA(seriesC(),80)); while(algo(loop("Day1","Day2","Day3","Day4","Day5"))) { Lots = Investment/priceClose(); LifeTime = Itor2+1; // life time in days if(pattern() > 0 && (!WithTrend || rising(Trend))) enterLong(); else if(pattern() < 0 && (!WithTrend || falling(Trend))) enterShort(); if(is(EXITRUN)) { // print statistics in the last run if(Itor2 == 0) // first loop run printf("\n%s Cases %i/%i -",Asset, NumWinLong+NumLossLong,NumWinShort+NumLossSho

® F OPTUMA: JANUARY 2021 TRADERS’ TIPS CODE Here is a list of formulas for use with Optuma based on the article in this issue by Perry Kaufman, “A Fresh Look At Short-Term Patterns.” To include the 80-trend filter, users just need to add ‘and MA(BARS=80) IsUp’ for bullish trend, or ‘MA(BARS=80) IsDown’ for bearish. Key Revesal - Bullish BARTYPES().Outside and CLOSE()>HIGH()[1] Key Reversal - Bearish BARTYPES().Outside and CLOSE()
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Island Reversal - Bullish HIGH()OPEN() Island Reversal - Bearish LOW()>HIGH()[1] and CLOSE() TR1[3]) and (TR1[4] > TR1[2]) and (TR1[4] > TR1[1]); CompHigh = HIGHESTHIGH(BARS=4); Compression and CLOSE() CrossesAbove CompHigh Compression - Bearish TR1 = TRUERANGE(); Compression = (TR1[4] > TR1[3]) and (TR1[4] > TR1[2]) and (TR1[4] > TR1[1]); CompLow = LOWESTLOW(BARS=4); Compression and CLOSE() CrossesBelow CompLow Outside Days - Bullish BARTYPES().Outside and CLOSE() > 0.75*(HIGH() - LOW()) +LOW() Outside Days - Bearish BARTYPES().Outside and CLOSE() < 0.25*(HIGH() - LOW()) +LOW()

FIGURE 7: OPTUMA. This chart displays sample test results for the bullish opening gap pattern. In this test, there were 1,502 total signals showing performance 5 days before and 10 days after each signal.

Wide Ranging Days - Bullish ATR1 = ATR(BARS=1); ATR20 = ATR(BARS=20, MULT=1.50); (ATR1>ATR20) and CLOSE() > 0.75*(HIGH() - LOW()) +LOW() Wide Ranging Days - Bearish ATR1 = ATR(BARS=1); ATR20 = ATR(BARS=20, MULT=1.50); (ATR1>ATR20) and CLOSE() < 0.25*(HIGH() - LOW()) +LOW() Opening Gaps - Bullish ATR20=ATR(BARS=20, MULT=0.50); OPEN()>(CLOSE()[1]+ATR20) and CLOSE()>OPEN()

FIGURE 8: OPTUMA. For the instruments tested you can view the trade statistics and metrics, including number of signals found, probability of gain or loss, standard deviation, and mean.

Opening Gaps - Bearish ATR20=ATR(BARS=20, MULT=0.50); OPEN()<(CLOSE()[1]-ATR20) and CLOSE()
Testing Optuma has a Signal Testing module that can run these formulas over any timeframe and universe of stocks with a couple of clicks, giving the results in seconds. The results show the average percentage returns, and other statistics (including 20th/80th percentiles, standard deviation, and a Monte Carlo simulation). Here are two example tests since January 2000 on the three ETFs and five stocks used in the article. Opening gap—Bullish Figure 7 shows 1,502 total signals showing performance 5 days before and 10 days after

FIGURE 9: OPTUMA. This chart displays sample test results for the bearish compression pattern with a trend filter.

54 • January 2021 • Technical Analysis of Stocks & Commodities

https://libta.org

each signal. After 10 days, there was a probability of gain of 58%, for an average return of 0.51%. The individual instrument breakdown is as follows: 289 signals for SPY with probability of gain after 10 days of 60.5%, with a mean gain of 0.06%. TSLA had a higher mean return (4.3%) but a lower probability of gain (56%) and a higher standard deviation (15.5%) in the 82 events. (See Figure 8.)

FIGURE 10: OPTUMA. For the instruments tested you can view the trade statistics and metrics.

Compression—Bearish with trend filter For this test, we had 433 results showing an average gain after 10 days of 0.3% (see Figure 9). The individual components are shown in Figure 10. —[email protected]

F TRADERSSTUDIO: JANUARY 2021 TRADERS’ TIPS CODE The importable TradersStudio files based on Perry Kaufman’s article in this issue, “A Fresh Look At Short-Term Patterns (With And Without A Trend Filter),” can be obtained on request via email to info@ TradersEdgeSystems.com. The code is also available on this magazine’s website at Traders.com in the Traders’ Tips section. Code for the short-term patterns in the article is included in the system file ST_ Patterns_Sys both with and without the trend filter depending on the input parameters. All of the patterns are coded on one file so if all of the buy and sell rules for the patterns are uncommented then the backtest will run all the patterns in one run. To test each pattern individually, simply comment out all the other patterns not of current interest. The way I have supplied the code is with all but the BullGap and BearGap patterns commented out. Hence, the only one that will run on a backtest is the gap patterns. Figure 11 shows the equity curve of the BullGap and BearGap trading 100 shares per trade of the NASDAQ 100 list of stocks from 2000 to 2014 with the trend filter turned off. Figure 12 shows the equity curve for the same set except that the trend filter was turned on. The trend filter did not improve the returns.

FIGURE 11: TRADERSSTUDIO. Equity curve for BullGap and BearGap trading 100 shares per trade of the NASDAQ 100 without the trend filter.

—Richard Denning [email protected] FIGURE 12: TRADERSSTUDIO. Equity curve for BullGap and BearGap trading 100 shares per trade of the for TradersStudio NASDAQ 100 with the trend filter. January 2021

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FIGURE 13: AIQ. Equity curve (blue) for Bull Outside Day pattern compared to the NASDAQ 100 index (red) from 1999 to 2020, all trades closed on 4th bar’s open after entry.

F AIQ: JANUARY 2021 TRADERS’ TIPS CODE The importable AIQ EDS file based on Perry Kaufman’s article in this issue, “A Fresh Look At ShortTerm Patterns (With And Without A Trend Filter),” can be obtained on request via email to info@TradersEdgeSystems. com. The code is also available on this magazine’s website at Traders.com in the Traders’ Tips section. Code for short-term patterns in the article is included in the EDS file both with and without the trend filter. I ran a portfolio simulation trading NASDAQ 100 stocks with the Bull Outside Day pattern from 1999 to 2020. The equity curve (blue) compared to the NASDAQ index (red) is shown

FIGURE 14: AIQ. Account Statistics Analysis report for the portfolio simulation.

in Figure 13 and the ASA report for the test is shown in Figure 14.

—Richard Denning [email protected] for AIQ Systems

OSOBA/FEAR

Continued from page 22

riods of stress or fear. We can reactivate our prefrontal cortex by staying present and reminding ourselves that the fear we feel is simply a chemical process happening deep inside our brain. And we can control that chemical process through the thoughts that we allow ourselves to think. Stella Osoba is a financial writer and trader. She has earned the Charted Market Technician designation and has written for several financial websites and publications. She is a frequent contributor to this magazine and to the Traders. com Advantage online publication. She may be reached via email at [email protected]. 56 • January 2021 • Technical Analysis of Stocks & Commodities

We can choose to think the thoughts that will maximize our potential for right action when we trade. FURTHER READING

Watts, Dickson G. [1880]. Speculation As A Fine Art And Thoughts On Life. Livermore, Jesse [1940]. How To Trade In Stocks.

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thinkorswim (by TDAmeritrade) .. . . . . . . . . . . . . . . Wealth-Lab.com .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . NinjaTrader. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . NeuroShell Trader (Ward Systems Group) .. . . The Zorro Project .. . . . . . . . . . . . . . . . . . . . . . . . . . . TradersStudio . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . AIQ .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . www.mystockodds.com.. . . . . . . . . . . . . . . . . . . .

49 49 51 51 52 55 56 61

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January 2021

• Technical Analysis of Stocks & Commodities • 57

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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

Contracts to Trade for Equal Relative Contract Liquidity Dollar Profit S&P 500 E-Mini (Dec ’20) CME 7.4 19.1 3 ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••>>> Ultra T-Bond (Dec ’20) CBOT 5 4.7 1 ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••>>> 10-Year T-Note (Dec ’20) CBOT 1.2 8.1 11 ••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••> 5-Year T-Note (Dec ’20) CBOT 0.6 5.2 17 •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• T-Bond (Dec ’20) CBOT 3 13.8 6 •••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••••• Russell 2000 E-Mini (Dec ’20) CME 4 8.6 3 •••••••••••••••••••••••••••••••••••••••••••••••••••• Crude Oil WTI (Jan ’21) NYMEX 12.3 6.3 3 •••••••••••••••••••••••••••••••••••••••••••••••• Ultra 10-Year T-Note (Dec ’20) CBOT 1.7 8.1 7 •••••••••••••••••••••••••••••••••••••••••••• Nasdaq 100 E-Mini (Dec ’20) CME 7.9 15.4 2 •••••••••••••••••••••••••••••••••••••••••• 2-Year T-Note (Dec ’20) CBOT 0.2 3.4 22 ••••••••••••••••••••••••••••• Gold (Dec ’20) COMEX 6.8 17.8 3 ••••••••••••••••••• Soybean (Jan ’21) CBOT 1.7 4.9 6 •••••••••••••••• Euro FX (Dec ’20) CME 1.9 18.8 15 ••••••••••• Eurodollar (Dec ’20) CME 0.1 3.8 36 •••••••• S&P 500 VIX (Dec ’20) CFE 56.2 24.4 4 •••••••• Corn (Mar ’21) CBOT 4.4 14.6 36 ••••••• Natural Gas (Jan ’21) NYMEX 12.5 16.1 11 ••••••• Soybean Meal (Jan ’21) CBOT 0.7 2.3 3 ••••••• Dow Futures Mini (Dec ’20) CBOT 7.2 18.8 4 •••••• Gasoline RBOB (Jan ’21) NYMEX 10 10.6 5 ••••• ULSD NY Harbor (Jan ’21) NYMEX 8.1 9 5 ••••• Silver (Dec ’20) COMEX 13.6 26.4 4 •••• S&P Midcap E-Mini (Dec ’20) CME 6.9 15.1 2 ••• Sugar #11 (Mar ’21) ICE/US 6.1 15.2 34 ••• Australian Dollar (Dec ’20) CME 2.7 11.1 13 •• British Pound (Dec ’20) CME 4 28.4 20 •• High Grade Copper (Dec ’20) COMEX 5.6 14.4 7 •• Japanese Yen (Dec ’20) CME 3.3 35.3 21 •• Wheat (Mar ’21) CBOT 5 14.2 22 •• 30-Day Fed Funds (Jan ’21) CBOT 0.1 2.8 24 • Canadian Dollar (Dec ’20) CME 2.1 19.3 28 • Cocoa (Mar ’21) ICE/US 13.1 39.3 26 • CBOT Chicago Board of Trade, Division of CME CFE CBOE Futures Exchange Coffee (Mar ’21) ICE/US 10.1 36.8 19 • Chicago Mercantile Exchange CME Cotton #2 (Mar ’21) ICE/US 8 23.7 19 • Commodity Exchange, Inc. CME Group COMEX Hard Red Wheat (Mar ’21) KCBT 5.3 15 24 • Intercontinental Exchange-Futures - Europe ICE-EU Lean Hogs (Feb ’21) CME 12 27.6 21 • Intercontinental Exchange-Futures - US ICE-US Live Cattle (Feb ’21) CME 4.5 17 20 • KCBT Kansas City Board of Trade Mexican Peso (Dec ’20) CME 8 34.3 40 • Minneapolis Grain Exchange MGEX New Zealand Dollar (Dec ’20) CME 2.7 12.6 16 • NYMEX New York Mercantile Exchange Platinum (Jan ’21) NYMEX 8.1 19.5 12 • Bitcoin CME Futures (Nov ’20) CME 35.2 42.3 3 2101 Brazilian Real (Dec ’20) CME 8.9 12.2 17 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). Commodity Futures

Exchange

% Margin

Effective % Margin

58 • January 2021 • Technical Analysis of Stocks & Commodities

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archived S&C product reviews. TRADERS’ RESOURCE AT TRADERS.COM In addition to the trading systems listing at Traders.com, you’ll also find listings of other trading-related products and Traders’ Resource is available at our website, Traders.com. Just services such as brokerages, data services, courses and seminars, click on the Traders’ Resource link. Then follow the category software, and more. We hope this will help you learn about prod- link, or use the search feature to find products or services with ucts to help in your trading endeavors. specific attributes you’re looking for. 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].

January 2021

• Technical Analysis of Stocks & Commodities • 59

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Trading Perspectives SOME PERSPECTIVES ON THE EQUITIES WORLD Rob Friesen is a professional trader and president & COO of Bright Trading (www. stocktrading.com), a proprietary trading firm hosting independent trader/members, an online trading school, and utilizing the StockOdds database (www.mystockodds.com). Courses on advanced hedged trading and basket trading are offered at www.hedgedtrading.com. This column shares his thoughts and outlooks on trading, locating opportunity, probabilistic outcome, and maintaining perspective throughout industry changes. He can be reached at [email protected] or via www.stocktrading.com. Rob Friesen

BASKET TRADING: A LOW-VARIANCE APPROACH TO SCALING UP YOUR TRADING BUSINESS Markets won’t always go up. Besides the directional outcomes, there are also many inside days and choppy sessions to endure or to participate in, if you have the knowhow and the tools. In my work, my goal is not only to assist traders with naked single-stock trading, but also encourage traders to explore any additional strategies, methods, and techniques, so that they can broaden their toolchest. As I’ve discussed before in this column, basket trading is one of the methods traders can employ to go beyond naked stock trading. Both basket trading and hedged trading in general offer many benefits for career-minded traders. Most don’t go back to naked trading once they’ve learned to incorporate hedges. Basket trading is essentially trading a group of stocks simultaneously to potentially reduce the risk and lower the variance of the total capital that is utilized, whether that capital is your own or whether you are using leverage. If you are leveraged, it’s even more important to lower the risk per idea, as well as your total exposure to the market. Baskets can be deployed and hedged with ETFs or they can be traded against other baskets to further reduce risk. Spreading capital over many instruments along with a variety of strategies employed can increase your staying power by reducing noise, buying you more time, and ultimately, these factors can increase the probability of success. I’ll reflect for a moment on probability. I’m not talking about hedging trades as an afterthought or done simply because you read that hedging is a good idea, but rather because you are acting intentionally and with analytics to support any

long or short, or inverse, positions. The objective of basket trading is to get the greatest return on capital (ROC) during your designated timeframes, but it must be on a risk-adjusted basis as well. A basket can be as simple as three stocks, or it can be a large group of hundreds of symbols. As with any diversification, the number of instruments deployed may have a diminishing effect on the benefit of diversification at some point. It’s been debated as to what the optimal number of instruments should be, but historically, an amount on the order of 20 to 30 different instruments has been regarded as an approximate level of diversification for a portfolio.

Baskets can be deployed and hedged with ETFs or they can be traded against other baskets to further reduce risk. The Dow Jones Industrial Average (DJIA) is comprised of 30 stocks which do change from time to time as we saw with the changes this past August. It is weighted by stock price, so when AAPL had a 4:1 split, the index was rebalanced with other symbols. Apple dropped from the most heavily weighted stock of the 30 stocks in the DJIA to 17th place. Index managers replaced XOM, PFE, and RTX with CRM, AMGN, and HON. You can see from this how meaningful it is to have knowledge about what symbols push and pull at the index and at its tracking ETFs. (ETFs that track indexes include the DIA and SPY). If you are going to trade ETFs, you should understand their composition and what

60 • January 2021 • Technical Analysis of Stocks & Commodities

makes them “tick.” Index arbitrage is one form of basket trading, by using stocks against futures, but there are many ways to harvest anomalies staying within equity instruments only. When comparing the DJIA with the S&P 500 (SPX), the DJIA closely tracks the SPX over the long sample, showing that the benefits of 30 symbols rivals that of 500. I am not suggesting that you have to construct baskets of hundreds of different stocks (although some traders do), but just that grouping stocks “normalizes” outcomes, and provides that balance in contrast to the selection of a single stock. ETFs are statistically muted, as they are comprised of several symbols, but again, take some time to research and understand the composition. Most investors are already familiar with having a basket of stocks, which they regard as their portfolio. This goal of having a portfolio is usually to select a group of noncorrelated stocks from multiple industries and sectors. The purpose is to smooth out the returns and benefit from the overall performance of the group. Stock-specific news, earnings, and events will not make or break the entire portfolio. We do find though that in significant market moves, the correlations increase as the market begins to act as one. During the market crash in March 2020, most equity portfolios were seriously declining. The trading of baskets is similar, but with shortened timeframes. In addition, most investors don’t have hedges on, nor are short, but rather they are striving to diversify and reduce correlations. A basket trader could have exploited the market correction rather than be a passive victim of it. A basket within the same sector or same industry can allow a trader to https://libta.org

Trading Perspectives take advantage of macro influences, technical, and relative strength observations, while reducing the impact of adversity from a single stock or its lack of performance. It is fairly hard to pick one stock out of 500 to earn a living on, versus having a probabilistic approach to picking 25 longs and 25 shorts and earning your keep on the relative performance between long and short dollars. If you want to reduce FIGURE 1: SAMPLE REPORT FROM WWW.HEDGEDTRADING.COM market and macro influences simultaneously, then going long a few symbols in a peer group and short a few symbols in the same group is one approach. The idea is to have favorable odds for each long selection (meaning, likely to move up), and favorable odds for each short selection (meaning likely to move down). And if this could be made compoundable day after day, then this is not only a good starting point but also one stepping-stone on a path to a scalable potential FIGURE 2: SEASONALITY ALMANAC trading career. I’ll illustrate how we approach this. could try to select some long ideas and Figure 1 shows an example report from some short ideas that all have favorour dashboard, which is a free resource able odds of moving up or down. If the we offer at www.hedgedtrading.com. SYMBOL/SPY relationship moves up, With this information, we are seeking that means the symbol would outperform to gain insights into the performance the SPY on a relative basis. Since the of each symbol in the S&P 500 index common symbol is the SPY that every against the tracking ETF itself. other symbol is also ratioed with, and The dashboard works by analyzing that relationship has had the event (of signals generated and reporting the the percent penetration of the Bollinger subsequent average performance. In this Bands), then you could drop the SPY example, the widely used %B indicator from the equation and go long some is shown and reports the subsequent symbols against short some symbols. average performance for the 10 days The SPY could be utilized for any after the signal was generated for all the capital-balancing offset or for protection same events or signals in the lookback against drift, and to use only when valid period. Other reports on the website show and with defined parameters. three-day performance. Some traders will simply trade a symUsing this type of information, you bol against the SPY, which is perfectly January 2021

fine. Other reports offered include streaks, RSI-2 period, price performance, and a seasonality almanac (a sample report is shown in Figure 2). With this, the user can dial in the seasonal signals as well as price, volume, events, stocks, or ETFs. Additional diversification can come from trading various strategies, and trading over a variety of timeframes. Many market participants can gain a false sense of security through outsized returns in a momentum market. The goal of career traders is to look at the long sample of what works in all markets and most of the time, while protecting their capital and reducing risk of ruin. There are a variety of methods to position-size your baskets, and traders usually start with capitalbalancing long dollars against short dollars. This doesn’t account for the instruments’ volatility, so traders can use ATR (average true range) or ATR as a percentage of price, or a blend of beta and historical volatility. Regardless of your chosen method, the key is to use a systematic approach so that you don’t have the problem of a loss on one symbol that wipes out the gains from ten symbols. On the subject of executing the baskets, various platforms have the ability to perform a wave, or you could buy at the open using market or limit orders (we prefer limit orders, but that might mean you miss some trades). If you buy during the day, you must account for slippage. You also need to account for hedging all at once versus hedging in increments. More on this subject in a future issue!

• Technical Analysis of Stocks & Commodities • 61

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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.

Unknown Market Wizards: The Best Traders You've Never Heard Of (376 pages, £30 for hardback, £15 for eBook, November 2020, ISBN 9780857198693– 9780857198709) by Jack D. Schwager, published by Harriman-House. Unknown Market Wizards continues in the threedecade tradition of the hugely popular Market Wizards series, interviewing exceptionally successful traders to learn how they achieved their extraordinary performance results. The twist in Unknown Market Wizards is that the featured traders are individuals trading their own accounts. They are unknown to the investment world. Despite their anonymity, these traders have achieved performance records that rival, if not surpass, the best professional managers. Some of the stories include a trader who turned an initial account of $2,500 into $50 million; a trader who achieved an average annual return of 337% over a 13-year period; a trader who made tens of millions using a unique approach that employed neither fundamental nor technical analysis, and a promising junior tennis player in the UK who abandoned his quest for a professional sporting career for trading and generated a nine-year track record with an average annual return just under 300%. World-renowned author and trading expert Jack D. Schwager is the guide. His trademark knowledgeable and sensitive interview style encourages the Wizards to reveal the fascinating details of their training, experience, tactics, strategies, and their best and worst trades. There are dashes of humour and revelations about the human side of trading throughout. The result is an engrossing new collection of trading wisdom, brimming with insights that can help all traders improve their outcomes. Harriman-house.com

How I Invest My Money: Finance Experts Reveal How They Save, Spend, And Invest (192 pages, £18.99 for paperback, £14.49 for eBook, November 2020, ISBN 9780857198082 – 978 0 8 5719 8 0 9 9) by Joshua Brown and Brian Portnoy, published by Harriman-House. The world of investing normally sees experts telling us the ‘right’ way to manage our money. But how often do these experts pull back the curtain and tell us how they invest their own money? How I Invest My Money seeks to do just that. In this collection, 25 financial experts share how they navigate markets with their own capital. In this honest rendering of how they invest, save, spend, give, and borrow, this group of portfolio managers, financial advisors, venture capitalists and other experts detail the ‘how’ and the ‘why’ of their investments. They share stories about their childhood, their families, the struggles they face and the aspirations they hold. Sometimes raw, always revealing, these stories detail the indelible relationship between our money and our values. Harriman-house.com

Investing For Growth: How To Make Money By Only Buying The Best Companies In The World—An Anthology Of Investment Writing, 2010–20 (320 pages, £24.99 for hardback, £18.99 for eBook, October 2020, ISBN 9780857199010–9780857199027) by Terry Smith, published by Harriman-House. Some people love to make successful investing seem more complicated than it really is. In this anthology of essays and letters written be-

62 • January 2021 • Technical Analysis of Stocks & Commodities

tween 2010 and 2020, leading fund manager Terry Smith delights in debunking the many myths of investing—and making the case for simply buying the best companies. Smith not only reveals what these highquality companies really look like and where to find them, but also why you should avoid companies that abuse the English language; how most share buybacks actually destroy value; what investors can learn from the Tour de France; why ETFs are much riskier than most realize; how ESG investors often end up with investments that are far from green or ethical; his ten golden rules for investment, and much, much more. The result is an enjoyable and eye-opening tour through some of the most important topics in the world of investing—as well as a collection of practical insights on how to make your money work for you. Harriman-house.com

The VIX Trader’s Handbook: The History, Patterns, And Strategies Eve ry Vo l a t i l ity Trader Needs To Know (206 pages, £50 for hardback, £37.50 for eBook, October 2020, ISBN 9780857197115–9780857197122) by Russell Rhoads, published by Harriman-House. Russell Rhoads is an expert on VIX, the Cboe Volatility Index. He takes a deep dive into all things associated with volatility indexes and related trading vehicles, beginning with an explanation of what VIX is, how it is calculated, and why it behaves the way it does in various market environments. It also explains the various methods of getting exposure to volatility through listed markets. The focus then moves on to demonstrate how traders take advantage of various scenarios using futures, options, or exchange-traded products (ETPs) linked to the performance of VIX. Finally, a review is presented of volatility events that shook the markets, including the 1987 crash, Great Financial Crisis, 2010 flash crash, and the 2020 pandemic. Harriman-house.com

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