Expmonthly Vol3no7 Nov 1

November 2012 | Vol. 3 No. 7

M O N T H LY THE

OPTION

TR ADERS

JOURNAL

Correlation Risk

    as a Tradable Factor      and Return Predictor

The Evolution of the

  Holiday Effect in VIX Futures

Does the Position

Fit the Trade?

The Predictive   Value of SKEW

Contents

M O N T H LY THE

OPTION

TR ADERS

4

Editor’s Notes Bill Luby

JOURNAL

5

The Predictive Value of Skew Mark Sebastian

Editorial

7

Bill Luby

Does the Position Fit the Trade? Andrew Giovinazzi

Jared Woodard Mark Sebastian

9

Correlation Risk as a Tradable Factor and

Return Predictor

Andrew Giovinazzi

Jared Woodard

D e s i g n / l ay o u t

11

Lauren Woodrow

The Evolution of the Holiday Effect in VIX Futures Bill Luby

C o n ta c t I n f o r m at i o n

Editorial comments: [email protected] Advertising and Sales Expiring Monthly President Mark Sebastian: [email protected] Phone: 773.661.6620

The information presented in this publication does not consider your personal investment objectives or financial situation; therefore, this publication does not make personalized recommendations. This information should not be construed as an offer to sell or a solicitation to buy any security. The investment strategies or the securities may not be suitable for you. We believe the information provided is reliable; however, Expiring Monthly and its affiliated personnel do not guarantee its accuracy, timeliness, or completeness. Any and all opinions expressed in this publication are subject to change without notice. In respect to the companies or securities covered in these materials, the respective person, analyst, or writer certifies to Expiring Monthly that the views expressed accurately reflect his or her own personal views about the subject securities and issuing entities and that no part of the person’s compensation was, is, or will be related to the specific recommendations (if made) or views contained in this publication. Expiring Monthly and its affiliates, their employees, directors, consultants, and/ or their respective family members may directly or indirectly hold positions in the securities referenced in these materials. Options transactions involve complex tax considerations that should be carefully reviewed prior to entering into any transaction. The risk of loss in trading securities, options, futures, and forex can be substantial. Customers must consider all relevant risk factors, including their own personal financial situation, before trading. Options involve risk and are not suitable for all investors. See the options disclosure document Characteristics and Risks of Standardized Options. A copy can be downloaded at http://www.optionsclearing.com/about/publications/ character-risks.jsp. Expiring Monthly does not assume any liability for any action taken based on information or advertisements presented in this publication. No part of this material is to be reproduced or distributed to others by any means without prior written permission of Expiring Monthly or its affiliates. Photocopying, including transmission by facsimile or email scan, is prohibited and subject to liability. Copyright © 2012, Expiring Monthly.

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November 2012 

 2

About the

Expiring Monthly Team Bill Luby

Bill is a private investor whose research

Mark Sebastian

Mark is a professional option trader

and trading interests focus on volatility,

and option mentor. He graduated

market sentiment, technical analysis,

from Villanova University in 2001 with

and ETFs. His work has been has been

a degree in finance. He was hired into

quoted in the Wall Street Journal,

an option trader training program by

Financial Times, Barron’s and other

Group 1 Trading. He spent two years

publications. A contributor to Barron’s

in New York trading options on the

and Minyanville, Bill also authors the VIX

American Stock Exchange before

and More blog and an investment

moving back to Chicago to trade SPX

newsletter from just north of San

and DJX options For the next five

Francisco. He has been trading options since 1998. Prior to becoming a full-time investor, Bill was a business strat-

years, he traded a variety of option products successfully, both on and off the CBOE floor.

egy consultant for two decades and advised clients across a

In December 2008 he started working as a mentor at Sheridan

broad range of industries on issues such as strategy formula-

Option Mentoring. Currently, Mark writes a daily blog on all

tion, strategy implementation, and metrics. When not trading or

things option trading at Option911.com and works part time

blogging, he can often be found running, hiking, and kayaking

as risk manager for a hedge fund. In March 2010 he became

in Northern California.

Director of Education for a new education firm OptionPit.com.

Bill has a BA from Stanford University and an MBA from Carnegie-Mellon University.

Jared Woodard

Andrew Giovinazzi

the financial markets after graduating

Jared is the principal of Condor

from the University of California, Santa

Options. With over a decade of

Cruz with a B.A. in Economics in 1989.

experience trading options, equities,

He joined Group One, Ltd. and quickly

and futures, he publishes the Condor

became a member of the Pacific Stock

Options newsletter (iron condors) and

Exchange (and later the CBOE), where

associated blog.

he traded both equity and index

Jared has been quoted in various

options over a 15 year span. During

media outlets including The Wall Street Journal, Bloomberg, Financial Times Alphaville, and The Chicago Sun-Times. He is also a contributor to TheStreet’s Options Profits service. In 2008, he was profiled as a top options mentor in Stocks, Futures, and Options Magazine. He is also an associate member of the National Futures Association and registered principal of Clinamen Financial Group LLC, a commodity trading advisor. Jared has master’s degrees from Fordham University and the University of Edinburgh.

Andrew Giovinazzi started his career in

that period he never had a down year. At the same time, Andrew started and ran the Designated Primary Market Marker post for GroupOne on the floor of the CBOE. It became one of the highest-grossing posts for the company in 1992 and 1993. While actively trading, Andrew was instrumental in creating and managing an option trader training program for Group One. He left Group One, Ltd. to co-found Henry Capital Management in 2001. Andrew then joined Aqumin LLC (2008–2011) to help bring 3D quoting and analysis to financial data. He is Chief Options Strategist at Option Pit.

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November 2012 

 3

Editor’s

Notes Bill Luby it has been an exciting month for options traders, with

Instead of thinking of my gift list this holiday season, I

the never-ending Greek drama keeping the euro zone on

find myself contemplating some seasonal quirks in volatility

edge, elections in the United States, a leadership transi-

in “The Evolution of the Holiday Effect in VIX Futures.”

tion in China and of course the seemingly inexorable march

Whether your wish list includes higher volatility or lower

toward the fiscal cliff. Yet with all the drama, the November

volatility, all of us at Expiring Monthly wish you a happy,

expiration cycle was another relatively quiet one for volatil-

healthy and profitable holiday season.

ity, with the VIX now unable to rise above the teens for four months and counting. In the November issue, Expiring Monthly tackles a num-

As always, readers are encouraged to send questions, comments or guest article contribution ideas to editor@ expiringmonthly.com.

ber of timely issues. Mark Sebastian offers up some pioneering research and analysis of the CBOE SKEW Index and its

Have a good expiration cycle,

suitability as a tool for helping to predict the direction of the VIX. Elsewhere, Andrew Giovinazzi takes a hard look at real-

Bill Luby Contributing Editor

ized volatility and the “range of motion” in the underlying as a determinant in structuring positions that are best suited for specific volatility regimes. Jared Woodard extends his recent work on volatility risk premium with a look at correlation risk premium and in the process analyzes some of the findings presented in “OptionImplied Correlations and the Price of Correlation Risk,” a recent paper by Driessen, Maenhout, and Vilkov.

www.expiringmonthly.com



November 2012 

 4

The Predictive Value

of Skew Mark Sebastian

skew is a term used in several

opposite assumption. When the SKEW

different ways. The two most common

Index is steep, the market has hedged

ways I hear is the spread between

against a sell-off, and thus there are

months (although generally that is

serious head winds to a major sell-off.

tradable results. Basically, no matter

referred to as term structure). The

My goal was to determine whether the

where the VIX is, or where the VIX has

other and more common use of the

SKEW Index could be a leading indicator

been, a steep skew in and of itself is

term has to do with the relation of the

for the VIX. Will the VIX go up or down

not a good determinant of VIX direction

level of implied volatility of puts rela-

if the SKEW Index is overly flat or steep?

and produces results that are consis-

tive to the ATM options or OTM calls.

Let’s start with overly steep. Since

tently a coin flip. To be honest, the results did not

Shops use several different methods

2004, when the VIX switched its cal-

to measure skew. Many use the 25

culating methodology, the average

surprise me, the purchase of insur-

delta call relative to the 25 delta put

price of skew has been 119.54, with a

ance happens in times when we are in

at either 30, 60 or 90 days to expira-

median number of 119.42. I ran sev-

panic and when we are in calm. I then

tion. Others measure puts and calls

eral tests, if the SKEW Index was above

began to study whether flat skewness

relative to ATM option (my preferred

the mean for the previous 5 days, did

was more predictive than its cousin. I

method). The CBOE SKEW Index uses

the VIX over the next day increase?

fully expected to find something; how-

the relation of far out-of-the-money

The answer was yes, but only as often

ever, I have to admit, I was surprised

puts (sometimes called tail risk puts,

as it decreased. If the VIX was up and

by the results. Across many iterations,

swan puts, or units) relative to more

the SKEW Index was up, did that lead

the first real piece of useful data was

standard OTM puts.

to anything? Again the answer was no.

that when skew was below its mean,

Every test I ran came back with non-

falling, and the VIX decreased. Over

This is a much different approach to skew, instead of telling traders how

CBOE.com

expensive OTM puts that could conceivably come into play are relative to ATM options, the CBOE has chosen to measure how expensive a put is that would really only come into play in the event of the a black swan. Furthermore, it’s measuring them 30 days to expiration, a somewhat near term trade (my first criticism of the index is that it might make more sense to run a black swan index using the VXV calculation rather than VIX). This begs the question, why does this index exist? The trader who is not well versed in options might answer that when the index is super-expensive, a sell-off might be imminent. The versed option trader might make an

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Figure 1 SKEW and VIX, Jan 1990–Feb 2012



November 2012 

 5

The Predictive Value of Skew (continued)

an 8-year period there were 365 days

duced positive VIX expectations, our

ing 217 times. On those days the VIX

where that happened, on 226 of those

goal was to find enough vol to trade.

went up the next day 119 times, a win

days, the VIX decreased the next day.

The one thing I always tell my students

ratio of just below 55%. We managed,

A hit of over 60%, certainly a signifi-

is that vol begets volatility.

however, to capture almost all of our

cant result. I then moved to see how

Now we all know that the long

VIX points from our previous filter. On

many VIX points I could collect being

term mean of the VIX is just over 20;

those 217 days, the VIX picked up just

short vol when VIX was down and skew

however, because of the upper and

under 40 total points. A significant

was below its mean and falling. This is

lower limits of volatility, the VIX has

return of just under .50. While I am sure there are other

where I got my surprise. Despite fewer

many more occurrences below 20 than

days when the VIX went up, the net

above. I consider the true ‘mid point’

gain in VIX points over the 365 occur-

of VIX to be between 18–19 over the

found that a low SKEW is much more

rences was over about 44 points. An

long haul. This is why using 18 as a

predictive, especially when the VIX

ways the index can be used, we have

low VIX filter outperformed using 20

is elevated and falling. It might be a

for a filter. From 2004 the VIX was

leading indicator when VIX is already

dig. If we knew that skew falling and

above 18, falling and had a skew index

elevated, that the index is going to go

below the mean and a falling VIX pro-

below its long term mean and fall-

higher.  EM

average increase of .12 points. I now had something and began to

implied volatility

historical volatility

Fearful investors: keeping option premiums artificially high since 1987.

[email protected] www.condoroptions.com (212) 203-0693

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Condor Options Advisory Newsletter (iron condors) Calendar Options Advisory Newsletter (time spreads) Backtesting & Research Mentoring & Consulting



November 2012 

 6

Does the Position

Fit the Trade? Andrew Giovinazzi one of the first things we

vehicle to accomplish goals with the

teach Option Pit clients in our Gold

underlying. The idea is to take the

Using Realized Volatility as a Condition

Classes is how the option pricing

variable of forward volatility out of the

My simple definition of realized (histor-

model works. The simple reason we

equation. From an option model input

ical) volatility is close to close move-

do this is before traders put on a posi-

point of view most of the reliance for

ment in the underlying over some

tion they should know how that posi-

success is on price of the underlying,

previous period of time. Most normally

tion should perform best. The position

strike and time to expiration. At least it

the intervals are a 10-day, 20-day and

will work when the changes in model

should be.

30-day moving average of the past

inputs during the trade lifespan are

trading days. The idea here is to estab-

in line with the original intent of the

2. Use the stock to trade the

lish what I call a range of motion

trade. Where the educational process

options. Here is where the unique

for the underlying. Can the underly-

starts to turn on light bulbs early on is

properties of options come into play.

ing move enough for the position that

right here. Certain positions “act” bet-

Option values are one of the few

I have chosen for it? Is the underlying

ter under certain circumstances and

financial instruments that have a

moving too much for the position that

that is totally teachable. It is a concept

variable in forward pricing that is not

I have chosen for it? If beginning trad-

called conditional trading.

known for certain. The option mar-

ers thought about a position in this

ket uses the next best thing which is

light what they would start to realize

Conditional Trading

the implied volatility of the options

is that a poorly constructed position

First off all positions are going to fall

on the trading day. If a trader thinks

is doomed from the start because the

into two different camps. I discuss

the current implied volatility is too

realized volatility will not support (or overwhelm) the trade set up.

the two separately below but will only

expensive between now and expira-

spend a few sentences on the first.

tion for a given underlying, they can

The reason being is that most of the

create a position to sell it, regardless

ink in finance today is dedicated to

of whether they have a bullish or bear-

#1 so the balance of my article will be

ish opinion on the underlying. It is the

devoted to #2.

speed of the movement in the under-

1. Use the options to trade the

are trading is a secondary consider-

lying they care about. The name they stock. This is where most techni-

ation, not the first. The thought pro-

cal and fundamental investors go. For

cess is not the closing price of AAPL

example when Warren Buffet wants

today but more like is the implied vola-

to buy KO, he will sell puts below his

tility priced right for the next 3 weeks

The idea here is to establish what I call a range of motion for the underlying.

target price and not give a fig about

for the range of motion expected.

the volatility. Another example would

From an option model point of view the

recent activity in AAPL as of the week

be a trader relying on a short term

forward volatility used to generate the

of 11/23/2012. I have drawn a horizon-

buy signal to buy deeper calls and

value is the most important with price,

tal green line to illustrate the highs of

avoid the risk from a change in volatil-

time to expiration and strike second-

30-day implied volatility over the last

ity. Once the underlying hits the sell

ary. If the relative value of the volatility

6 months. For many traders looking

signal the position is unwound. In

component does not look interesting,

at implied volatility, AAPL trading at a

these cases the options are just a

there is no trade in the name.

near 6 month high in an off earnings

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Figure 1 is an example of the most

November 2012 

 7

Does the Position Fit the Trade? (continued)

terfly type setup is doomed to failure because the range of motion in the underlying is too great right now. In this case it would be better to wait until the realized volatility starts to soften, like it has, and sell a less gamma-intensive position like an iron condor or some out-of-the-money put spreads. Whether AAPL is a $500 stock or a $700 stock the volatility disparities are generating the trade idea, not necessarily the direction AAPL is going. The more traders look at realized volatility, the better the position

Figure 1

structure will start off in the first place implied volatility is trading at such a

and improved results should follow.

Normally I would be with them. The

huge discount to the recent realized

Waiting for conditions to improve for

problem is that the 10-day realized

volatility.

better entry points will help the results

cycle would be a reason to sell options.

volatility (white line) is making a new

At the minimum this would change

6 month high too. It is very difficult to

the position type a trader would use.

make money selling options when the

Selling near term gamma in a but-

as well.  EM

Visit Our Website

www.optionpit.com

For Information Call (888) TRADE-01 Specializing in Trade Structure, Risk Management and Capital Efficiency

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November 2012 

 8

Correlation Risk as a Tradable Factor and

Return Predictor Jared Woodard the promise of mod-

premium is not clear. Positing

ern portfolio theory was

a model and finding that the

that a basket of uncorre-

data fits the model is not the

lated assets would pro-

same thing as an argument or

vide better risk-adjusted

an explanation. I think the idea

returns, over time, than a

is that, without priced correlation risk, there would be no way

portfolio whose constitufind that the CRP is negative, meaning

to explain why index options tend to

confronted many investors in 2008 and

that option buyers have tended to pay

be overpriced. The authors explain

in the years since was that, in a crisis,

a higher price to hedge against corre-

that the VRP for index options is nega-

ents move together. The problem that

even traditionally dissimilar assets had

lation than has actually occurred in the

tive, as has been widely observed,

the potential to become highly cor-

underlying assets.

and they also note that for individual

related, making diversification efforts fruitless. Investors concerned that

Two other claims in the paper are of particular interest. The authors find

equity options, we cannot reject the null hypothesis that options are fairly

a portfolio of stocks might become

that the CRP is a key driver of the

priced, i.e. that the VRP on individual

increasingly correlated in a crisis have

VRP. In fact, the model they give for

stock options is zero. Presumably the

turned to equity index options to pro-

pricing correlation risk “attributes the

inference the authors are making is

tect against that risk.

entire index variance risk premium to

that index options have a negative

In “Option-Implied Correlations and the Price of Correlation Risk,”

priced correlation risk.” (p. 9) This is

VRP because stock investors are using

an important claim because it is not

those options to hedge against correla-

Driessen, Maenhout, and Vilkov

initially obvious, conceptually, whether

tion; and that individual equity options

argue that correlation risk is a priced

an increase in the volatility of a basket

have zero VRP because, if the worry is that individual stocks will become

of assets would be a cause of higher basket correlation

the premium paid for correlation risk

or vice versa. For

(abbreviated below as CRP) as the

example, while

difference between the implied cor-

the range of daily

relation in an option’s price and the

Dow Jones returns

subsequent realized correlation of the

has been wider at

underlying index constituents. This

higher levels of cor-

method should be familiar to our read-

relation, a scatter

ers, since it is similar to the method

plot of that rela-

of subtracting realized volatility from

tionship does not

option implied volatility to estimate

suggest a relation-

the volatility risk premium (VRP).

ship (Figure 1).

To analyze the properties of the

The argument

CRP, the authors look at the time

for the claim that

series of this premium for the S&P 500

correlation risk

and Dow Jones Industrials over the last

drives the index-

fifteen years. As with the VRP, they

level variance risk

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Yahoo!, Condor Options

factor that can be measured from equity option prices. They estimate

Figure 1 1-Month DJIA Realized Correlation and Daily Stock Returns



November 2012 

 9

Correlation Risk as a Tradable Factor and Return Predictor (continued)

more correlated, options on those

ing correlations during a crisis could

increased CRP in recent years (higher

individual stocks will not provide the

hedge with the options of historically

spread between implied and realized

low beta assets instead of using index

correlation), the index VRP is not also

puts. If stocks originally intended to

higher than its historical average.

desired protection. As a description of investor behav-

diversify failed to do so in a market decline, buyers of puts on those stocks

implied correlations explain future

is right, a strategy suggests itself.

would benefit from being short deltas

market returns, with high predictive

Investors worried about increas-

and long vegas in those stocks, and at

power even out to 6 and 12 months.

Driessen et al. 2012

ior, this all sounds fair and plausible. But assuming the above explanation

Finally, the authors claim that

a lower cost than they

The surprise here (Figure 2) is that,

would be expected to

while VRP has a higher predictive

pay using equity index

value at a one-month horizon, the

options. And since the

r-squared value for implied correla-

equity option VRP is not

tion estimates for both the Dow Jones

negative, option buy-

Industrials and the S&P 500 were

ers would not incur the

higher for 100 days forward, and

same hedging costs in

increased to 0.10 even as far out as

bull markets.

one year. The authors mention some

I am still a bit skep-

possible explanations for these rela-

tical of the strength

tionships including the effects of high

of the claim that cor-

correlation on future dividend and con-

relation risk entirely

sumption growth volatility.  EM

explains the index VRP. Other studies have found other priced factors to be determinants of index VRP, like daily Figure 2 R^2 Predictive Value for S&P 500 Returns of Implied Correlation and Variance Risk Premium

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jump risk and the volatility of volatility. We can also ask why, given the



References Driessen, Joost, Maenhout, Pascal J. and Vilkov, Grigory, Option-Implied Correlations and the Price of Correlation Risk (October 25, 2012). Advanced Risk & Portfolio Management Paper. Available at SSRN: http://ssrn.com/abstract=2166829

November 2012 

 10

The Evolution of the

Holiday Effect

in VIX Futures Bill Luby

with fewer trading days and a

VIX usually occurs from the middle of

month of December. Figure 2 below

historical record that favors an uptick

the month right up to the Christmas

is a snapshot of the VIX futures curve

in stocks and a downtick in volatil-

holiday.

from September 12, 2012. Here I have added a dotted black line to show what

ity, the end of the year never fails to present an intriguing set of trading opportunities.

The December VIX Futures Angle

a linear interpolation of the December VIX futures would look like, with the

Most VIX traders are aware of the ten-

green line showing the 0.50 point dif-

above is something I have labeled

dency of implied volatility in general

ferential between the actual December

One phenomenon related to the the “holiday effect,” which is the ten-

and the VIX in particular to decline in

VIX futures settlement value of 20.40

dency of the CBOE Volatility Index

December. As a result, since the launch

on that date and the 20.90 interpo-

(VIX) December futures to trade at a

of VIX futures in 2004, there has usu-

lated value, which is derived from the

discount to the midpoint of the VIX

ally been a noticeable dip in the VIX

November and January VIX futures con-

November and January futures.

futures term structure curve for the

tracts. (Apart from the distortions present in the December

This article provides some historical lyzes how the holiday effect has been manifest and evolved over the course of the past few years.

Background and Context on the Holiday Effect on the VIX Index

VIX futures, a linear

CBOE Futures Exchange, VIX and More

analysis of the holiday effect and ana-

interpolation utilizing the first and third month VIX futures normally provides an excellent estimate of the value of the second month VIX futures.)

Part of the explanation for the holiday

Looking at the

effect is embedded in the historical record. For instance, in eight of the last

full record of histori-

twenty years, the VIX index has made

cal data, the mean

its annual low during the month of

Figure 1 The Composite December VIX Index, 1990–2011

holiday effect for all days in which the

December. In fact, the VIX has demonstrated a marked tendency to decline

November, December

steadily for the first 17 trading days of

and January futures

the month, as shown below in Figure 1,

traded is 1.87%,

which uses normalized VIX December

which means that

data to compare all VIX values for

the December VIX

each trading day dating back to 1990.

futures have been,

Not surprisingly, those 17 trading

on average, 1.87%

days neatly coincide with the typical

lower than the value

number of December trading days in

predicted by a lin-

advance of the Christmas holiday.

ear interpolation of

Readers should also note that, on average, the steepest decline in the

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Figure 2 VIX Futures Curve from September 12, 2012, Showing Holiday Effect



the November and January VIX futures.

November 2012 

 11

CBOE Futures Exchange, VIX and More

The Evolution of the Holiday Effect in VIX Futures (continued)

Further analysis reveals that on 91% of all trading days, the December VIX futures are lower than their NovemberJanuary interpolated value. The holiday effect, therefore, is persistent and substantial.

The History of the Holiday Effect in the December VIX Futures

Figure 3 VIX December Futures Holiday Effect, 2006–2012

Determining whether the holiday

is consistent with a smaller holiday

1999 that turned out to be a volatility

effect is statistically significant is a

effect. The data is much less com-

non-event when the calendar flipped

more daunting task, as there are only

pelling when one tries to determine

to 2000.

six holiday seasons from which one

whether the time remaining until the

While the opportunities to capital-

can derive meaningful VIX futures

holiday season has an influence on the

ize on the 2012 holiday effect may be

data. Figure 3 shows the monthly aver-

magnitude of the holiday effect. While

difficult to pinpoint and fleeting, all

age VIX December futures (solid blue

one might expect the holiday effect to

investors should be attuned to sea-

line) as well as the midpoint of the

become magnified later in the season,

sonal volatility cycles as 2013 unfolds

November and the January VIX futures

the evidence to support this hypoth-

and volatility expectations ebb and

(dotted red line) for each month since

esis is scant at this stage.

flow with the news cycle as well as the

the VIX futures consecutive contracts were launched in October 2006. Here

To sum up, investors have readily

the green bars represent the magni-

for December and the downward blip

tude of the holiday effect expressed

in December for the VIX futures term

in percentage terms, with the sign

structure reflects this thinking. As far

inverted (i.e., a +2% holiday effect

as whether this seasonal anomaly is

means that the VIX December futures

tradable, there is still a limited amount

would be 2% below the interpolated

of data—not to mention some highly

value derived from November and

unusual volatility years­­­—from which

January futures.)

to develop and back test a robust VIX

Conclusions

the holiday effect.

futures strategy designed to capture With limited data from which to draw

In terms of trading the holiday

conclusions, it is tempting to eyeball

effect for the remainder of the year,

the data and look for emerging pat-

the coming holiday season is also com-

terns which may repeat in the future.

plicated by matters such as the fiscal

Clearly one pattern is that an elevated

cliff deadline and various euro zone

or rising VIX appears to coincide with

milestones that are set for early 2013.

a larger magnitude holiday effect,

In fact, there may not be a reasonable

whereas a depressed or falling VIX

equivalent since the Y2K fears in late

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calendar.  EM

accepted that a lower VIX is warranted



Further Reading “Exploring the VIX Futures Term Structure, Part I” Expiring Monthly, August 2010 “An Interpretive Framework for VIX Futures (Second in a Series)” Expiring Monthly, September 2010 “VIX Futures: Putting Ideas into Action (Third in a Series)” Expiring Monthly, October 2010 “A History of VIX Futures Roll Yields” Expiring Monthly, September 2011 “Investing Implications of the VIX Term Structure” Expiring Monthly, October 2011 “Calculating the Future Range of the VIX” Expiring Monthly, February 2012 “The VIX Term Structure as a Predictor of Future Returns” Expiring Monthly, March 2012

November 2012 

 12