day1 session3 cole

7/27/2019 Day1 Session3 Cole

1/36

Christopher Cole, CFAArtemis Capital Management LLC

Artemis Vega Fund LP

520 Broadway, Suite 350

Santa Monica, CA 90401

(310) 496-4526 phone

(310) 496-4527 fax

[email protected]

VOLATILITY PARADIGM AND PARADOX C B O E R I S K M A N A G E M E N T C O N F E R E N C E - M A R C H 3 , 2013

For Investment Professional Use. Not for Distribution


2/36

VOLATILITY

PARADIGMAND

PARADOX

What is Volatility?

2

Volatility at Worlds End Deflation

Imagine the world economy as an armada of ships passing through a narrow and

dangerous strait between the waterfall of deflation and hellfire of inflation

Our resolution to avoid one fate may damn us to the other

Illustration by Brendan Wuiff based on concept by Christopher Cole


3/36

50

500

5,000

50,000

0

20

40

60

80

100

120

1928

1930

1932

1934

1936

1938

1940

1942

1944

1946

1948

1950

1952

1954

1956

1958

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

JI(

l

ari

t

ics

cal

)

RealizedVolatility

(%)

Volatility at World's End Deflation

Dow Jones Industrial Index (RHS) vs. 1-month Realized Volatility of DJIA (LHS)

VOLATILITY

PARADIGMAND

PARADOX

Volatility in Worlds End Deflation

3

Volatility shocks are rightfully associated with deflationary crashes


4/36

VOLATILITY

PARADIGMAND

PARADOX

Volatility in Hellfire of Inflation

4Source: Economicsof Inflation; A Study of Currency Depreciation in Post-War Germany" by Constantino Bresciani-Turroni Out of Print / 1968(1) Based upon monthly realized variance from available stock price data.

Extreme volatility can also occur in hyperinflation

0000001101001,00010,000100,0001,000,00010,000,000100,000,000

0

20

40

60

80

100

120

Feb

-18

May-1

8- - - - - -

Feb

-20

May-2

0

Aug-2

0

Nov-2

0

Feb

-21

- - - - - -

Nov-2

2

Feb

-23

May-2

3

Aug-2

3-

Perfor

anceinpaper

arks

(

il)

Perfo

rmanceadj.forfixedexchange Performance of German Stock Market

during Weimar Republic Hyperinflaton

Adj. according to USD exchange rate

Adj. according to wholesale index numbers

In paper marks, Weimar

0

500

1,000

1,500

2,000

Feb

-18

May-1

8

Aug-1

8

Nov-1

8

Feb

-19

May-1

9

Aug-1

9

Nov-1

9

Feb

-20

May-2

0

Aug-2

0

Nov-2

0

Feb

-21

May-2

1

Aug-2

1

Nov-2

1

Feb

-22

May-2

2

Aug-2

2

Nov-2

2

Feb

-23

May-2

3

Aug-2

3

Nov-2

3

Volatility(%)

Weimar VIX?(1)

Realized Volatility of German Stock Market during Weimar Republic Hyperinflation

(monthly volatility data annualized)


5/36

VOLATILITY

PARADIGMAND

PARADOX

Volatility of an Impossible Object

5Illustration by Brendan Wiuff based on concept by Christopher Cole

Modern financial markets are an impossible object

Volatility of an impossible object is our changing perception of risk


6/36


6

Volatility itself is now a paradox

(both in time and space)

Temporal Paradox

Low Spot-VIX but steep VIX Futures

term structure

Power law distortions in dailyvolatility moves

Steep Volatility-of-Volatility term

structure & Skew but low-spot VOV

Spatial Paradox

Low volatility-of-volatility (realized)

but higher potential for volatility-of-

volatility (implied) Historically expensive gamma on tails

of probability distribution

Steeper volatility-of-volatility skew

Volatility is Global Macro

VOLATILITY

PARADIGMAND

PARADOX


7/36

Unknown UnknownsKnown Unknowns

Volatility of VolatilityVolatility

Everything you need to know about trading volatility

7

Debt Ceiling Crisis

China hard landing

War with Iran

European Crisis

Global Recession

Fiscal Austerity

Thereare known knowns; there are things we know that we know. There are known unknowns;

that is to say there are things that, we now know we don't know. But there are also unknown

unknownsthere are things we do not know, we don't know.

Donald Rumsfeld, United States Secretary of Defense

? Vanilla Options

VIX Index

Implied Volatility

Vol Term Structure

Forward Volatility

Convexity

Tail Risk Hedging

Vol Curve Trades

Risks that you

know and can

quantity

Risks that you

know but cant

quantify

Risks that you

dont know but

could quantify

Risks that you

dont know and

cant quantify

VOLATILITY

PARADIGMAND

PARADOX


8/36

VOLATILITY

PARADIGMAND

PARADOX

Bull Market in Fear

8

Bull Market in Fear is Defined by

1. Abnormally Steep Volatility Term-Structure

2. Distortions in Volatility from Monetary Policy

3. Expensive Portfolio Insurance

4. Violent Volatility Spikes and Hyper-Correlation

What is the Bull Market in Fear?New paradigm for pricing risk that emerged after the 2008 financial crisis as

related to our collective fear of the next deflationary crash

Bull Market in Fear is not about where volatility is today as so much as it is

about where markets think volatility will be tomorrow


9/36

I. Emotional Post-traumatic Deflation Disorder Desire for safety and security at any cost

II. Monetary Forced participation in risk assets drives desire for hedging

Unspoken feeling that gains in financial assets are artificial

III. Macro-Risks Debtor-developed economies face structural headwinds

Unrest in Middle East, Iran, Japan & China Tensions

IV. Regulatory Government regulation (Dodd-Frank, Volcker rule) has

constrained risk appetite for banks to supply volatility

Lower demand for structured products by investors

Structural imbalances in supply-demand dynamics of volatility markets

VOLATILITY

PARADIGMAND

PARADOX

Bull Market in Fear

9

Greater

Demand for

Volatility

Less Supply

of Volatility


10/36

TEMPORAL PARADOX - Abnormally Steep VIX Futures Term Structure

10

BULL MARKET IN FEAR

"There is no terror in the bang, only in the anticipation of it." Alfred Hitchcock

VOLATILITY

PARADIGMAND

PARADOX

VIX

36

0.50x

0.70x

0.90x

1.10x

1.30x

1.50x

1.70x

1.90x

r-

J

- -v-0

4

F

-05

r-

Jl- - -

r- - -t-

J

-r-

J

- - -

F

-08

r-08

Jl- - -

r- - - t-

J

-r-

J

- - - -r-

Jl- - - -

Jl-

t- -

Expiry

VixFutures/SpotVix

Bull Market in Fear / VIX Futures Curve2004 to Present


11/36

10

15

20

25

30

35

Spot Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8

ForwardVIXind

ex(%)

Low Volatility? Really?VIX Futures Curve Comparison

August 2012 vs. September 2008

August 17, 2012 / Lowest VIX in 5 years at time

September 15, 2008 / Day after Lehman Bros. Bankruptcy

February 19, 2013

TEMPORAL PARADOX - Abnormally Steep VIX Futures Term Structure

11

Low VIX index does not mean cheap volatility

!

VOLATILITY

PARADIGMAND

PARADOX


12/36

11

16

21

26

31

36

41

46

60%

70%

80%

90%

100%

110%

120%

130%

Mar-09

May-09

Jul-09

Sep-09

Nov-09

Jan-10

Mar-10

May-10

Jul-10

Sep-10

Nov-10

Jan-11

Mar-11

May-11

Jul-11

Sep-11

Nov-11

Jan-12

Mar-12

May-12

Jul-12

Sep-12

Nov-12

Jan-13

II

ex()

FedBS%Changes

inceSeptember2008

No Fed Action

QEIQEII

Op. Twist+LTRO(ECB)

QEIII

VIX

TEMPORAL PARADOX - VIX Regimes Defined by Central Banking

12

Since 2008 global central banks have expanded their balance sheets by $9 trillion - enough fiat

money to buy every person on earth a 55'' wide-screen 3D television

VIX spikes consistently occur after the end of central bank balance sheet expansion

Flash Crash

Aug 2011 Crash

QEII

LTRO (ECB)

Fed Balance Sheet Expansion and VIX index

VOLATILITY

PARADIGMAND

PARADOX


13/36

-

.

-

.

-

.-.

. .

0%

10%

20%

30%

40%

50%

CumulativeProbability

Implied 12m %G/L

in S&P 500 index

S&P 500 Index 12-month % Contribution to Model-Free Variance by Expected Returns(1995 to March 2012)

40%-50%

30%-40%

20%-30%

10%-20%

0%-10%

SPATIAL PARADOX - High Cost of Tail Risk Insurance

13

Fat Left Tails have Dominated the Distribution of S&P 500 index Variance

You are not smart for hedging what everyone else already knows!

1995 to 2012

Note: Artemis calculates the implied probability distribution using interpolated weights from variance swap pricing. This methodology may occasionally give higher weightings to tails in down markets than othermethods like taking the second derivative of call prices, fitting mixture of normal PDFs to recover prices, or fitting vol mod els (SVI,SABR).

VOLATILITY

PARADIGMAND

PARADOX


14/36

0%

2%

4%

6%

8%

10%

12%

14%

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

Yield(%)

Volatility Yield (%) vs UST Bond Yields (%)1990 - 2013

-25% from SPX Strike Rate Breached

Volatility Yield (sell 1yr SPX put / -25% discount)

10yr UST Yield

30yr UST Yield

SPATIAL PARADOXVOLATILITY and BONDS

14

For the first time in history the annualized short volatility yield (OTM SPX Put) is

competitive with the yield on long dated UST Bonds!

WOW!

VOLATILITY

PARADIGMAND

PARADOX


15/36

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

-65%-55%-45%-35%-25%-15%-5%

SPATIAL PARADOXVOLATILITY and BONDS

15

When the Bull Market in Fear meets a Bubble in Safety a short equity option

position and risk-free UST bond have similar risk-to-reward payoffs!

Risk / Unrealized Loss in Stress Test Scenario

SPX -9% to -14%68% to 33% probability

SPX -50%2% probability

10yr USTBond

30yr UST

Bond

SPX Short Put

(Strike @-25% OTM)

Rates 320bps to 600bps13% to 2% probability

Rates 100bps to 200bps68% to 33% probability

Note: All data as of February 17, 2013. Estimated unrealized loss on position given stress test scenario. Historic probability data based on period of 1960 - 2012 for the UST bonds and 1950 to 2012 for the S&P 500 index.Option pricing based on estimated local volatility shifts, however actual shifts may differ from estimates during a real crash depending. All stress tests are assumed to occur close to the purchase period of theinstrument. Unrealized losses may differ closer to maturity.

SPX -25%13% chance

SPX Put

Stress Test

UST Bond

Stress Test

Risk / Unrealized Loss in Stress Test Scenario

Efficient Frontier / Risk to Reward Comparison

Long Dated UST Bond vs.1yr OTM Short Puts (collateralized)

Return/

Yield

VOLATILITY

PARADIGMAND

PARADOX


16/36

0%

5%

10%

15%

20%

-50% -43% -35% -28% -20% -13% -5% +3% +10% +18% +25% +33% +40% +48%

Cum

ulativeProbabilityW

eighting

One Year Gain/Loss % in S&P 500 index

Mirror Reflection: Deflation vs. HyperinflationS&P 500 Probability Distributions in different Regimes of Risk

1-year Gain-Loss%

Implied from March 2012 SPX options

Simulated from in 2013-2022 Hyperinflationary Model (1 scenario of 10k)

VOLATILITY

PARADIGMAND

PARADOX

The more people fear the LEFT TAIL the more you should buy the RIGHT

16

Maybe it is correct to buy tail risk insurance ... but is everyone just hedging the

wrong tail?

Note: Artemis created a model to simulate the behavior of the S&P 500 index and volatility during an inflationary shock. The model is not intended to be a prediction of the future but is merely a rudimentary stochastic-based method to understand what modern markets may look like in rampant inflation. The simulation runs 10,000 price scenarios for the S&P 500 index over 10 years modeling daily stock price behavior using ageneralized Wiener process (Wiener.. not Weimar) and a drift rate that assumes linkages between annual CPI and equity performance. We assume inflation rises sharply from current levels of 2.87% in 2012 to 26% by2015 and stays elevated at that level until 2017 (20% a year overall). The average volatility shifts are based upon assumptions regarding equity return to variance parameters observed in prior inflationary episodes(1970s US & 1920s Germany). The simulation shows annualized SPX returns for the decad e at +9.94% but adjusted for inflation this d rops to -9.8%.

Future?


17/36

PARADOX IS FUNDAMETNAL

17

Effects of Volatility Paradox

I. VIX index

Fire danger (VOV) is higher despite low spot-Vol

Higher potential for Volatility-of-Volatility (kindling)

Skew Realization

II. VIX Futures & Options

Inconsistent hedging ratios

Loss of hedging effectiveness

Roll-Yield Deception

III. VIX Structured Products & ETNs To many players shorting the front of the curve

Shadow Risk in dynamicVIX structured products

Roll Yield Short Squeeze?

Inconsistent Deltas

Shadow Gamma

Shadow Theta

VOLATILITY

PARADIGMAND

PARADOX


18/36

0

0.2

0.4

0.6

0.8

1

000

001

002

003

003

004

005

006

007

008

009

010

011

012

Correlation(

0-1)

HIGHER CORRELATIONS lead to...

S&P 500 Sector Correlation (60 day)2000 to 2012

45

65

85

105

125

145

165

185

205

000

001

002

003

004

005

006

007

008

009

010

011

012

Volatilit

y(%)

More VIOLENT VOLATILITY SPIKES

Volatility of VIX index (60 day)

2000 to 2012

18

Fire Risk can be high when the forest is calm

Higher correlations are kindlingfor violent VIX fires(spike)

Volatility of Volatility WILDFIRE - Correlations VOLATILITY

PARADIGMAND

PARADOX


19/36

Volatility of Volatility WILDFIRE - Correlations

Today the difference between high implied and falling realized correlations

makes hedging single stock names cheaper than buying index vol

Source: Barlcays GlobalVol

VOLATILITY

PARADIGMAND

PARADOX

19

S&P 500 Implied Correlation (12m)

S&P 500 Realized Correlation (12m)


20/36

BSM Put-Call Parity Relationship is consistent when VIX options are priced usingVIX futures as the underlying

When the VIX futures curve is in contango deep in-the-money VIX puts will trade at a discount

to intrinsic value when evaluated against spot VIX

Likewise deep in-the-money calls will trade at a discount during backwardization

Most commercial options programs do not make this adjustment, erroneously pricing implied

vol from the spot VI

5.MODEL

FREEVOLATILITY

EXPOSURE

VIX options widely misunderstoodVIX options are priced off VIX Futures, NOT the VIX Index

20

Violation of BSM put-call parity when vol

calculated on spot VIX index

BSM Put-Call parity holds when vol is calculated

based on the VIX futures (accurate method)

Expiration

Type Strike Jun-11 Jul-11 Aug-11 Sep-11 Oct-11

Put 16 60% 43% 35% 26% 23%

Put 17 65% 43% 35% 24% 22%

Put 18 72% 45% 36% 22% 20%

Call 18 103% 119% 127% 130% 65%

Call 19 103% 115% 123% 126% 67%

Call 20 110% 116% 118% 124% 66%

Vix Index 17.88 17.88 17.88 17.88 17.88

Expiration

Type Strike Jun-11 Jul-11 Aug-11 Sep-11 Oct-11

Put 16 69% 63% 58% 51% 44%

Put 17 75% 66% 62% 53% 47%

Put 18 84% 73% 67% 56% 58%

Call 18 87% 72% 66% 51% 65%

Call 19 90% 73% 68% 56% 67%

Call 20 98% 79% 69% 61% 66%

VIX Future 18.40 20.00 21.05 22.40 22.30

Understanding VIX Options


21/36

Understanding VIX options

21

Dimensions of VIX optionality

VOV Term Structure (z-axis) & VIX Skew (x-axis)

VOLATILITY

PARADIGMAND

PARADOX

Mar-13

pr-13

ay-13

Jun-13

Jul-13

40%

60%

80%

100%

120%

140%

160%

-1.0

0.5

2.0

3.5

5.0

Maturity

VolofVol

Moneyness (Sigma)

VIX Volatility Surface


22/36

65

75

85

95

105

115

125

135

8 18 28 38 48 58 68 78

Vo

latilityoftheVIX(1m

O

ptions)

VIX index

New Regimes of FearVIX index vs. Vol of VIX / SKew of the VIX (Smoothed)

Bull Market (Jan 2006 to Jul 2007)

Credit Crisis Onset (Aug 2007 to Aug 2008)

Market Crash (Sep 2008 to Feb 2009)

Recovery to Flash Crash (Mar 2009 to May 2010)

Post-Flash Crash Steepening (May 10 to Sep 11)

LTRO Steepening Regime (Nov 11 to Mar 12)

QEIII Regime (Sep 12 to Feb 13)

SPATIAL PARADOXVolatility of Volatility Skew

22

Vol of VIX skew has built in a higher probability of volatility spikes to account for

this wildfire effect

VOLATILITY

PARADIGMAND

PARADOX


23/36

45

55

65

75

85

95

0.08 0.17 0.25 0.33 0.42 0.50

VolatilityofVIXFutu

res(%)

Expiration / Terms

New Regimes of FearVolatility of VIX Futures Term Structure / 2006 to 2013

Bull Market Jan 2007 to July 2007)Credit Crisis Onset (Aug 2007 to Aug 2008)Market Crash (Sep 2008 to Feb 2009)Recovery to Flash Crash (Mar 2009 to May 2010)Post-Flash Crash Steepening (May 2010 to Oct 2011)LTRO Steepening (Nov 2011 to Aug 2012)QEIII (Sep2012-Feb2013)

Temporal PARADOXVolatility of Volatility Term Structure

23

Steepening VIX VOL Term Structure

Volatility of VIX Term Structure has steepened in the bull market for fear

implying greater futures delta sensitivity to spot-VIX movement

VOLATILITY

PARADIGMAND

PARADOX


24/36

60

70

80

90

100

110

120

130

140

Jan-07

Mar-07

ay-07

Jul-07

ep-07

ov-07

Jan-08

Mar-08

ay-08

Jul-08

ep-08

ov-08

Jan-09

Mar-09

ay-09

Jul-09

ep-09

ov-09

Jan-10

Mar-10

ay-10

Jul-10

ep-10

ov-10

Jan-11

Mar-11

ay-11

Jul-11

ep-11

ov-11

Jan-12

Mar-12

ay-12

Jul-12

ep-12

ov-12

Jan-13

VolofVIX(%)

Volatility of Volatility Drift

TEMPORAL PARADOXVOV is falling from highs

24

Nonetheless VVIX has continued to drift lower tempered by the bull market in

equities and QEIIIvolatility cant fight the Fed

VOLATILITY

PARADIGMAND

PARADOX

Bull Market (Jan 2006 to Jul 2007)

Credit Crisis Onset (Aug 2007 to Aug 2008)

Market Crash (Sep 2008 to Feb 2009)

Recovery to Flash Crash (Mar 2009 to May 2010)

Post-Flash Crash Steepening (May 10 to Sep 11)

LTRO Steepening Regime (Nov 11 to Mar 12)

QEIII Regime (Sep 12 to Feb 13)


25/36

VIX Exchange Traded Products vs. Traditional Volatility Strategies

25

VIX ETPs gain in popularity despite muddled performance in comparison to classic

volatility strategies

VOLATILITY

PARADIGMAND

PARADOX0.3

0.5

0.70.9

1.1

1.3

1.5

1.7

1.9

2.1

Dec-10

Jan-11

Feb-11

Mar-11

Apr-11

May-11

Jun-11

Jul-11

Aug-11

Sep-11

Oct-11

Nov-11

Dec-11

Jan-12

Feb-12

Mar-12

Apr-12

May-12

Jun-12

Jul-12

Growthof$1

VIX ETPs vs. Traditional SPX Volatility Trades

Dec 2010 to July 2012

Traditional Volatility Trading Volatility ETNs

ATM LongStraddle

ATM ShortStraddle

10% OTM Put VXX VXZ XIV XVIX

Vol Bias Long Vol Short Vol Long Vol Long Vol Long Vol Short Vol Short Vol

Annualized Return -28.62% 31.31% -15.36% -52.35% -26.98% 12.13% -3.61%

Sortino Ratio -1.77x 0.79x -0.61x -1.94x -1.53x 0.18x -0.45x

Sharpe Ratio -1.20x 0.85x -0.45x -1.05x -0.87x 0.16x -0.30x

Return to Drawdown -0.57x 1.10x -0.36x -0.65x -0.58x 0.15x -0.20x

Max Drawdown -50.16% -28.39% -42.87% -80.38% -46.50% -79.53% -18.06%


26/36

Note: Prior to 1990 there was not VIX index. We have substituted the CBOE VXO index, the precursor to the VIX, which was available starting in 1986. 26

When the shoeshine boy is shorting VIX ETNs maybe it is time to be cautiousFront-month VIX futures are increasingly influenced by short squeezes due to rising popularity

of short selling strategies

Shorting the front of the Vol Curve

May 2012 VIX

spike to 25

Ratio of 1m VIX Future Volatility vs. VIX Volatility

(2007 to 2012)

Late 2011 VIX

rebound to 30

VOLATILITY

PARADIGMAND

PARADOX


27/36

2012(VIXFut)

2012(Vix)

2011(Vix)

2010(Vix)

2009(Vix)

2008(Vix)

20

30

4050

60

70

80

90

100

9:31

9:

10:03

10:19

10:35

10:51

1

1:0

11:23

11

:39

:

:

:

:

:

:

:

:

2:03

:

:

:

:

:

:

:

:

VolatilityofVI

XbyMinute(%annualized)

Volatility of VIX Index vs 1m Vix Future (2012) by Trading Minute

Averages by Year (annualized)

2012 (VIX Fut) 2012 (Vix) 2011 (Vix) 2010 (Vix) 2009 (Vix) 2008 (Vix)


Volatility-of-VIX futures in the last 15 minutes is substantially higher than that of

the VIX index itself demonstrating the power of structural flows

Source: Calculations executed by Artemis Capital Management LLC with data from CQG data factory. Average executed trades by minute.

VOLATILITY

PARADIGMAND

PARADOX

27


28/36


28

Short Roll Yield

Vol-of-Vol Timing

Leverage

Evolution of a Volatility Flash Crash

(aka Killer Rabbit)

Artificially Low Vol from Monetary Expansion+

Higher potential for Volatility-of-Volatility+

Dangerous Global Macro catalysts+VIX Derivatives Short Squeeze

=

? ?

Short Vol Squeeze

Hyper Vol-of-Vol

Self-Reflexivity

VOLATILITY

PARADIGMAND

PARADOX


29/36

12

13

14

15

16

17

18

19

20

VIX Month 1 Month 2 Month 3 Month 4 Month 5 Month 6

VIX Futures Curve following Largest VIX %

Spikes (VIX < 20 to start)

2004-2013

February 27, 2007 / 50% Vix Log Move

February 25, 2013 / 29% Vix Log Move

March 30, 2006 / 27% Vix Log Move

March 13, 2007 / 26% Vix Log Move13

14

15

16

17

18

19

20

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

:

Minute by Minute Performance of VIX and

Front Month FutureVIX Jumps 29% (log) on February 25th, 2013

VIX Index

March VIX Future


February 25th2013 - Volatility Killer Rabbit

Source: Calculations executed by Artemis Capital Management LLC with data from CQG data factory. Average executed trades by minute.

VOLATILITY

PARADIGMAND

PARADOX

29

10% of futurevolume in last

minute of trading!


30/36

The Next Volatility Regime

30

Three Possible Macro-VIX regimes for the next decade

I. Bull Market in Fear = New Normal Post-2008 vol environment of steep term-structure is here to stay

Traders short the front and buy the back but with violent corrections

High Implied Correlations, Volatility of Volatility, but low spot-vol

VOLATILITY

PARADIGMAND

PARADOX

II. Bear Market in Fear = Japanization of US Volatility Positive real rates lead to volatility as fixed income alternative

Long-term volatility and skew collapse as investors short rich vol

Rise of volatility short sellers builds systemic risk

III. Inflationary Volatility Spiral (Japan moving to this regime)

Runaway inflation actually drives higher volatility

Options skew flipsto compensate (OTM Calls Vol)

OTM calls re-priced as we all have been hedging the wrong tail


31/36

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

6% 7% 8% 9% 10% 11% 12% 13% 14% 15%

Allocationfor3%RealR

eturn

Nominal Expected Return on Stocks

Optimal Portfolio with Positive Real Rates(Stocks, Bonds, Cash & Vol) / Portfolio Target = 3% real return

Inflation = 3%

Long Volatility (-3% nominal return, -6% real return)Cash (3.5% nominal return, 0.5% real return)Stocks (SPX, 3-15% nominal return, 0-9% real return)Bonds (10yr UST / 6% nominal return, 3% real return)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

6% 7% 8% 9% 10% 11% 12% 13% 14% 15%

Allocationfor3%R

ealR

eturn

Nominal Expected Return on Stocks

Optimal Portfolio in Financial Repression(Stocks, Bonds, Cash & Vol) / Portfolio Target = 3% real return

Inflation = 3%

Long Volatility (-3% nominal return, -6% real)Cash (0% nominal return, -3% real)Stocks (SPX, 3-10% nominal return, 0-7% real)Bonds (10yr UST / 2% nominal return, -1% real)

Bull Market in Fear and Modern Portfolio Theory

Bull Market in Fear is Explained by Markowitz Portfolio Theory

Long volatility exposure extremely valuable to portfolio optimization in financial repression despite

substantial negative carry because it hedges forced over-allocation to equity

5-12% is optimal volatility portfolio exposure in negative real interest rate environment!

VOLATILITY

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Equity %

Long Volatility %

Fixed Income %

Fixed Income %

Cash %

Cash %

Cash %


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Post-Modern Volatility can be more than just FEAR

32

Volatility is the ultimate post-modern asset for our existential economic future

because it protects you from the fracture of the abstraction

Forward

Variance

Volatility of

Volatility

Volatility

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Visualizing Volatility

33

Volatility at Worlds End: Two Decades of Movement in Markets is a depiction of real stock

market variance using trading data from 1990 to 2011. The visuals are designed from S&P 500

index option data replicating the implied volatility wave (or variance swap curve) extending to

an expiration of one year. The front of the volatility wave contains the same data used to

calculate the CBOE VIX index. The movement of this wave demonstrates changing traderexpectations of future stock market volatility. As the wave moves through time the expected

(or implied) volatility surface transforms into a realized volatility surface derived from

historical S&P 500 index movement. The transition represents what professional traders call

volatilityarbitrage. The color variation in the volatility waves show the volatility-of-volatility

or internal movement of the wave. The track underneath the volatility wave represents

underlying S&P 500 index prices.

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Christopher Cole, CFAGeneral Partner and FounderContact Information Reference Material & Acknowledgements

34

Artemis Research:

Volatility of an Impossible Object: Risk, Fear, and Safety in Games of Perception

Volatility at Worlds End: Deflation, Hyperinflation and the Alchemy of Risk, March 30, 2012

Fighting Greek Fire with Fire: Volatility Correlation, and Truth, September 30, 2011

Is Volatility Broken? Normalcy Bias and Abnormal Variance, March 30, 2011

The Great Vega Short- volatility, tail risk, and sleeping elephants, January 4, 2011

Unified Risk Theory - Correlation, Vol, M3 and Pineapples, September 30, 2010

Artwork:

"Volatility of an Impossible Object" by Brendan Wiuff / Concept by Christopher Cole 2012 / copyright owned by Artemis Capital Management LLC

Jack-o-Lantern Istock photo / used based on purchase of rights

Ocean Waves Istock photo / used based on purchase of rights

"Odysseus facing the choice between Scylla and Chrybdis" by Henry Fuseli 1794 / public domain

"Penrose Triangle, Devils Turning Fork & Neckers Cube Derrick Coetzee / Public Domain

Reference Material:

Kritzman, M. and Y. Li. Skulls, Financial Turbulence, and Risk Management. The Financial Analysts Journal, May/June 2010

Simulacra and Simulation by Jean Baudrillard / University of Michigan / 1994

"A Tale of Two Indices" by Peter Carr & Liuren Wu December 22, 2005

VIX Derivatives: A Poor Practitioners Model Maneesh Deshpande / May 19 2011

Understanding VIX Futures and Options Dennis Dzekounoff; Futures Magazine/ August 2010

The Volatility Surface: A Practitioners Guide. Jim Gatheral / John Wiley and Sons, Hoboken, NJ, 2006

"Think Fast and Slow" by Daniel Kahneman / Farrar, Staus and Giroux 2012

Options, Futures, and Other Derivatives John C. Hull, Fifth Edition; Prentice Hall 2003

"Lifetime Odds of Death for Selected Causes, United States, 2007" / National Safety Council 2011 Edition

Volatility Trading Evan Sinclair, Wiley Trading 2008

"Dying of Money: Lessons of the Great German and American Inflations" by Jens O. Parsson / Wellspring Press 1974

"Economics of Inflation; A Study of Currency Depreciation in Post-War Germany" by Constantino Bresciani-Turroni Out of Print / 1968

Variance Swaps Peter Allen, Stephen Einchcomb, Nicolas Granger; JP Morgan Securities / November 2006"Laughter in the Dark - The Problem of the Volatility Smile" by Emanuel Derman May 26, 2003

Robust Hedging of Volatility Derivatives Roger Lee & Peter Carr; Columbia Financial Engineering Seminar / September 2004

More than you Ever Wanted to Know About Volatility Swaps Kresimir Demeterfi, Emanual Derman, Michael Kamal & Joseph Zou; Goldman Sachs / March 1999

The Performance of VIX Option Pricing Models: Empirical Evidence Beyond Simulation Zhiguang Wang; Florida International University / April 2009

Recent Developments in VIX Exchange Traded Products Maneesh Deshpande/ April 3, 2012

"Deflation: making sure 'it' doesn't happen here" by Ben S. Bernanke (speech) / US Federal Reserve November 2002

"US Options Strategy TVIX Explosion Drives Vol-of-Vol Higher" Deutsche Bank February 23, 2012

"Unknown Unknowns: Vol-of-Vol and the Cross Section of Stock Returns" Guido Baltussen, Sjoerd Van Bekkum and Bart Van Der Grient / Erasmus School of Economics & Robeco Quantitative

Strategies/ July 30, 2012

Definition of "Impossible Object" / Wikipedia / http://en.wikipedia.org/wiki/Impossible_object

VOLATILITY

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Christopher Cole, CFAGeneral Partner and Founder

Artemis Vega Fund L.P.Artemis Capital Management, L.L.C.

520 Broadway, Suite 350Santa Monica, CA 90401

[email protected]

Christopher Cole, CFAManaging Partner & Portfolio Manager

(310) 496-4526 phone(310) 496-4527 fax

[email protected]

Contact Information Artemis Capital ManagementContact Information

35

Christopher Cole, CFA

Managing Partner & Portfolio Manager / Artemis Capital Management LLC

Christopher R. Cole, CFA is the founder of Artemis Capital Management LLC and the portfolio manager of theArtemis Vega Fund LP. Mr. Coles core focus is systematic, quantitative, and behavioral based trading of

exchange-traded volatility futures and options. His decision to form a fund came after achieving significantproprietary returns during the 2008 financial crash trading volatility futures. His research letters andvolatility commentaries have been widely quoted including by publications such as the Financial Times,Bloomberg, International Financing Review, CFA Magazine, and Forbes. He previously worked in capitalmarkets and investment banking at Merrill Lynch. During his career in investment banking and pensionconsulting he structured over $10 billion in derivatives and debt transactions for many high profile issuers.Mr. Cole holds the Chartered Financial Analyst designation, is an associate member of the NFA, andgraduated Magna Cum Laude from the University of Southern California.

Key Information/ Biography

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LEGALDISC

LAIMER

Legal Disclaimer

THIS IS NOT AN OFFERING OR THE SOLICITATION OF AN OFFER TO PURCHASE AN INTEREST IN ARTEMIS VEGA FUND,

L.P. (THE FUND). ANY SUCH OFFER OR SOLICITATION WILL ONLY BE MADE TO QUALIFIED INVESTORS BY MEANS

OF A CONFIDENTIAL PRIVATE PLACEMENT MEMORANDUM (THE MEMORANDUM) AND ONLY IN THOSE

JURISDICTIONS WHERE PERMITTED BY LAW. AN INVESTMENT SHOULD ONLY BE MADE AFTER CAREFUL REVIEW OF

THE FUNDS MEMORANDUM. THE INFORMATION HEREIN IS QUALIFIED IN ITS ENTIRETY BY THE INFORMATION INTHE MEMORANDUM.

AN INVESTMENT IN THE FUND IS SPECULATIVE AND INVOLVES A HIGH DEGREE OF RISK. OPPORTUNITIES FOR

WITHDRAWAL, REDEMPTION AND TRANSFERABILITY OF INTERESTS ARE RESTRICTED, SO INVESTORS MAY NOT HAVE

ACCESS TO CAPITAL WHEN IT IS NEEDED. THERE IS NO SECONDARY MARKET FOR THE INTERESTS AND NONE IS

EXPECTED TO DEVELOP. NO ASSURANCE CAN BE GIVEN THAT THE INVESTMENT OBJECTIVE WILL BE ACHIEVED OR

THAT AN INVESTOR WILL RECEIVE A RETURN OF ALL OR ANY PORTION OF HIS OR HER INVESTMENT IN THE FUND.

INVESTMENT RESULTS MAY VARY SUBSTANTIALLY OVER ANY GIVEN TIME PERIOD.

CERTAIN DATA CONTAINED HEREIN IS BASED ON INFORMATION OBTAINED FROM SOURCES BELIEVED TO BEACCURATE, BUT WE CANNOT GUARANTEE THE ACCURACY OF SUCH INFORMATION.

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