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Fascinating presentation that I found on the web discussing volatility and risk. C
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Christopher Cole, CFA Artemis Capital Management LLC Artemis Vega Fund LP 520 Broadway, Suite 350
Santa Monica, CA 90401
(310) 496-4526 phone
(310) 496-4527 fax
BULL MARKET IN FEAR G R A N T ’ S F A L L C O N F E R E N C E / N E W Y O R K C I T Y - O C T O B E R 2 3 , 2 0 1 2
For Investment Professional Use. Not for Distribution
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1
“You cannot stop the waves, but you can learn to surf” Jon Kabat-Zinn
We live in uncertain times… a bull market in fear Volatility is the market price of uncertainty
Definition of fear from Merriam-Webster
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What is Volatility?
2
Volatility at World’s 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
50
500
5,000
50,000
0
20
40
60
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100
120
192819301932193419361938194019421944194619481950195219541956195819601962196419661968197019721974197619781980198219841986198819901992199419961998200020022004200620082010
DJI
A (l
oga
rith
mic
sca
le)
Rea
lize
d V
ola
tilit
y (%
)
Volatility at World's End DeflationDow Jones Industrial Index (RHS) vs. 1-month Realized Volatility of DJIA (LHS)
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Volatility in World’s End Deflation
3
Volatility shocks are rightfully associated with deflationary crashes
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Volatility in Hellfire of Inflation
4 Source: “Economics of 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
-18
Au
g-18
No
v-18
Feb
-19
May
-19
Au
g-19
No
v-19
Feb
-20
May
-20
Au
g-20
No
v-20
Feb
-21
May
-21
Au
g-21
No
v-21
Feb
-22
May
-22
Au
g-22
No
v-22
Feb
-23
May
-23
Au
g-23
No
v-23
Pe
rfo
rman
ce in
pap
er
mar
ks (
mil
)
Pe
rfo
rman
ce a
dj.
fo
r fi
xed
exc
han
ge 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
-18
Au
g-18
No
v-18
Feb
-19
May
-19
Au
g-19
No
v-19
Feb
-20
May
-20
Au
g-20
No
v-20
Feb
-21
May
-21
Au
g-21
No
v-21
Feb
-22
May
-22
Au
g-22
No
v-22
Feb
-23
May
-23
Au
g-23
No
v-23
Vo
lati
lity
(%)
Weimar VIX?(1)
Realized Volatility of German Stock Market during Weimar Republic Hyperinflation(monthly volatility data annualized)
Unknown Unknowns Known Unknowns
Volatility of Volatility Volatility
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Everything you need to know about trading volatility
5
US Fiscal Cliff
China hard landing
War with Iran
European Crisis
Global Recession
Fiscal Austerity
“There are 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 unknowns – there are things we do not know, we don't know.”
Donald Rumsfeld, United States Secretary of Defense
?
Regimes of Volatility-of-Volatility (2007 to 2012)
Period Average
Volatility Regime Vol of VIX VIX indexSPX Return
(annual)
Total
(2007 to Sep 2012)87.5 24.8 +1%
Bull Market
(2006 to July 2007)81.7 13.8 +5%
Credit Crisis Onset
(Aug 2007 to Aug
2008)
82.7 23.0 -11%
Market Crash
(Sep 2008 to Feb
2009)
95.7 49.6 -71%
Recovery to Flash
Crash
(Mar 2009 to May
80.8 26.7 +35%
Post-Flash Crash
Steepening
(May 2010 to Oct
90.5 23.2 +10%
LTRO Steepening
(Nov 2011 to Sep
2012)
97.7 20.3 +16% Vanilla Options
VIX Index
Realized Volatility
Variance Swap
Forward Volatility
Convexity
Tail Risk Hedging
Vol Curve Trades
volatility) are associated with lower equity returns
Many people who trade volatility do not realize they
Risks that you know and can
quantity
Risks that you know but can’t
quantify
Risks that you don’t know but could quantify
Risks that you don’t know and can’t quantify
Unknown Unknowns Known Unknowns
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Everything you need to know about trading volatility
6
Two very different styles of crash depending…
?
Regimes of Volatility-of-Volatility (2007 to 2012)
Period Average
Volatility Regime Vol of VIX VIX indexSPX Return
(annual)
Total
(2007 to Sep 2012)87.5 24.8 +1%
Bull Market
(2006 to July 2007)81.7 13.8 +5%
Credit Crisis Onset
(Aug 2007 to Aug
2008)
82.7 23.0 -11%
Market Crash
(Sep 2008 to Feb
2009)
95.7 49.6 -71%
Recovery to Flash
Crash
(Mar 2009 to May
80.8 26.7 +35%
Post-Flash Crash
Steepening
(May 2010 to Oct
90.5 23.2 +10%
LTRO Steepening
(Nov 2011 to Sep
2012)
97.7 20.3 +16%
Existential Flash Crash (Black Monday 1987, 2010 Crash)
Debt-Cycle Crash (2008 Crash, Great Depression)
Crash occurs over time (months)
Slow recovery
Natural end of leveraging cycle
High volatility for long period
Elevated volatility-of-volatility
Start of a recession or depression
Predictable
(in retrospect) Unpredictable
(even In retrospect)
Hyper-speed crash (days, seconds)
Fast recovery
Market fragmentation
Extreme volatility for shorter period
Extreme volatility-of-volatility
Omen of future recession (often)
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Bull Market in Fear
7
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
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
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
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Bull Market in Fear
8
Greater Demand for
Volatility
Less Supply of Volatility
BU
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9
"There is no terror in the bang, only in the anticipation of it." Alfred Hitchcock Volatility term-structure measures the anticipation of future volatility
VIX
M3
M6
0.50x
0.70x
0.90x
1.10x
1.30x
1.50x
1.70x
1.90x
Ma
r-0
4Ju
n-0
4S
ep
-04
No
v-0
4F
eb
-05
Ma
y-0
5A
ug
-05
Oct
-05
Jan
-06
Ap
r-0
6Ju
n-0
6S
ep
-06
De
c-0
6M
ar-
07
Ma
y-0
7A
ug
-07
No
v-0
7
Fe
b-0
8
Ap
r-0
8
Jul-
08
Oct
-08
De
c-0
8
Ma
r-0
9
Jun
-09
Se
p-0
9
No
v-0
9
Fe
b-1
0
Ma
y-1
0
Jul-
10
Oct
-10
Jan
-11
Ap
r-1
1
Jun
-11
Se
p-1
1
De
c-1
1
Fe
b-1
2
Jul-
12
Expiry
Vix
Fu
ture
s/S
po
t V
ix
Bull Market in Fear / VIX Futures Curve (normalized by spot VIX) 2004 to Present
1.2x
1.4x
1.6x
1.8x
2.0x
2.2x
2.4x
0.08 0.17 0.25 0.33 0.42 0.50 0.58 0.67 0.75 0.83 0.92 1.00 1.08 1.17 1.25 1.33 1.42 1.50
Exp
ect
ed
Vo
lati
lity
as a
Rat
io t
o S
po
t V
ola
tilit
y
Expiry (1=year)
Cumulative Average (1990-Mar 2012) 2012 YTD (avg.)
Bull Market of 1990s (avg.) 2000 to Feb 2009 (avg.)
2009 to 2012 Bull Market in Fear
BU
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10
The most extreme term-structure for S&P 500 index volatility in two decades reflects continued anticipation of a deflationary collapse
Ratio of Expected Future Volatility as Ratio to Spot Volatility S&P 500 options
VIX Index
10
15
20
25
30
35
Spot Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8
Forw
ard
VIX
ind
ex
(%)
Low Volatility? Really?VIX Futures Curve Comparison
August 2012 vs. September 2008
August 17, 2012 / Lowest VIX in 5 years
September 15, 2008 / Day after Lehman Bros. Bankruptcy
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Volatility is cheap and expensive at the same time
11
Low VIX index does not mean cheap volatility
!
15
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30
35
40
45
50
60%
70%
80%
90%
100%
110%
120%
130%
Mar-0
9
May-0
9
Jul-0
9
Sep-0
9
No
v-09
Jan-1
0
Mar-1
0
May-1
0
Jul-1
0
Sep-1
0
No
v-10
Jan-1
1
Mar-1
1
May-1
1
Jul-1
1
Sep-1
1
No
v-11
Jan-1
2
Mar-1
2
May-1
2
Jul-1
2
Sep-1
2
VIX
Ind
ex
(%)
Fed
BS
% C
han
ge s
ince
Se
pte
mb
er
20
08
No Fed ActionQEIQEIIOp. Twist+LTRO(ECB)QEIIIVIX
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Volatility 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
Volatility spikes consistently occur after the end of central bank balance sheet expansion
Risk and Vol Returns in Fed BS Regimes
Crisis and Recovery (September 2008 to September 2012)
Period Average Weekly Change
SPX VIX 21d SV Fed BS
Fed Balance Sheet ↑ 0.6% -1.7% 0.0% 1.5%
Fed Balance Sheet > +1σ ↑ 3.2% -7.4% 0.0% 8.1%
Fed Balance Sheet ↓ 0.0% 1.3% -2.0% -0.9%
Fed Balance Sheet < -1σ ↓ 1.2% 2.7% -1.9% -4.7%
Post-Crisis Recovery Period (Mar 2009 to Sep 2012)
Period Average Weekly Change
SPX VIX 21d SV Fed BS
QEI con't (March09-Jun 09) 1.4% -2.6% -2.5% 0.6%
Post QEI (Jun09-Oct10) 0.2% -0.2% -0.8% 0.2%
QEII (Sep10-June11)(1) 0.5% -1.0% 0.0% 0.5%
Post-QEII (July11-Nov11) -0.2% 2.2% 2.3% -0.1%
LTRO (Dec11 to Sep 0.3% -1.5% -2.7% 0.0%
(1) period following announcement of QEII at Jackson Hole August 2010.
Sources: Federal Reserve Bank, ECB, Bloomberg
Flash Crash
Aug 2011 Crash
QEII
LTRO (ECB), Op Twist (Fed) & QEIII (Fed)
Fed Balance Sheet Expansion and VIX index
0%
5%
10%
15%
20%
25%
-50
%
-45
%
-40
%
-35
%
-30
%
-25
%
-20
%
-15
%
-10
%
-5%
0%
5%
10
%
15
%
20
%
25
%
30
%
35
%
40
%
Cu
mu
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Pro
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bil
ity
Implied 12m %G/L in S&P 500 Index
Actual from Sep 2008 to Sep 2012
Implied from Jan 1990 to Sep 2008
Implied from Sep 2008 to Sep 2012
September 2012 (average)
BU
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13
Tail Events are now priced as if they are standard risks Highly unlikely events are either ignored or vastly over weighted based on our collective experiences
Implied Odds of % Returns for S&P 500 index SPX Options (1year)
A “black swan” is not dying because your parachute didn’t open while skydiving…. it is dying because the guy whose parachute didn’t open landed on you while you were golfing
Heart Disease 1 in 6
Stroke 1 in 28
Car Crash 1 in 88
Lifetime odds of Dying from these causes is 1 in 4.7(1)
Black Swan?
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 other methods like taking the second derivative of call prices, fitting mixture of normal PDFs to recover prices, or fitting vol models (SVI,SABR).
(1) "Lifetime Odds of Death for Selected Causes, United States, 2007" / National Safety Council 2011 Edition
-50
.0%
-35
.0%
-20
.0%
-5.0
%
10
.0%
25
.0%
0%
10%
20%
30%
40%
50%
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95
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09
20
10
Cu
mu
lati
ve
Pro
ba
bil
ity
Implied 12m %G/Lin 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%
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High Cost of Tail Risk Insurance
14
Fear of deflation is not MISPLACED but it is MISPRICED
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 other methods like taking the second derivative of call prices, fitting mixture of normal PDFs to recover prices, or fitting vol models (SVI,SABR).
0
0.2
0.4
0.6
0.8
1
20
00
20
01
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20
12
Co
rre
lati
on
(0-1
)
HIGHER CORRELATIONS lead to...S&P 500 Sector Correlation (60 day)
2000 to 20120
0.2
0.4
0.6
0.8
1
20
00
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01
20
02
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11
20
12
Co
rre
lati
on
(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
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
Vo
lati
lity
(%)
More VIOLENT VOLATILITY SPIKESVolatility of VIX index (60 day)
2000 to 2012
(0.80)(0.60)(0.40)(0.20)
-0.20 0.40 0.60 0.80 1.00
Au
g-0
3
Feb
-04
Au
g-0
4
Feb
-05
Au
g-0
5
Feb
-06
Au
g-0
6
Feb
-07
Au
g-0
7
Feb
-08
Au
g-0
8
Feb
-09
Au
g-0
9
Feb
-10
Au
g-1
0
Feb
-11
Au
g-1
1
Feb
-12
Au
g-1
2
Hedge Fund Strategies 12m Correlation to ATM Short Straddle on SPX
(HFRX Absolute Return, Equity Nuetral, Hedge Index, Merger Arb, RV Arb, Convertible Arb / Monthly)
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15
Fire Risk is High Today in the Forest Higher correlations are kindling for violent volatility fires (spike)
Extreme Volatility-of-Volatility and Hyper-Correlations
-0.4
-0.2
0
0.2
0.4
0.6
19
86
19
87
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88
19
89
19
90
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00
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01
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02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
Correlation of $USD Index to VIX Index(1986 to 2012)
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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.
16
Volatility is a Shadow Currency in the Bull Market for Fear $USD currency index strength = Higher Volatility
Extreme Volatility-of-Volatility and Hyper-Correlations
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Volatility of an Impossible Object
17
How to beat a “Bull Market in Fear”
When Risk-Free is Risky… buy Volatility on Safety Itself! when a “bull market in fear” meets a “bubble in safety” bet on interest rate volatility
Fear is a better reason to buy than fundamentals Volatility (fear) is an effective leading indicator to inform asset allocation
The more we fear the left tail the more you should buy the right Tail risk pricing (both left and right) has been consistently late to the game
Hedge unknown unknowns and sell known unknowns When the market identifies a risk it is usually overpriced in volatility markets
40
60
80
100
120
140
160
180
200
220
240
11-Oct-12 6-Nov-12 3-Dec-12 28-Dec-12 25-Jan-13 21-Feb-13 19-Mar-13 15-Apr-13 9-May-13
Vo
lati
lity
of
VIX
(%
)
Forward Period
Fiscal Cliff or Volatility of Volatility Cliff?Predicted Volatility of VIX vs. Realized Vol of VIX
October 2012
Market Expected Volatility of VIX (local)
5yr Average Realized Vol-of-VIX
1yr Average Realized Vol-of-VIX
6mo Average Realized Vol-of-VIX
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Bet on unknown unknowns… don’t hedge known unknowns
18
Cheap Fear
Very Expensive Fear
US Fiscal Cliff
Volatility markets are surprisingly bad at predicting future risk
When markets identify a ‘known unknown’ that risk traditionally is overblown or at the very minimum over-hedged
Volatility of VIX was 200% on Oct 13, 2008 Maximum was 265% on Aug 29, 2011
1.0x
1.1x
1.2x
1.3x
1.4x
1.5x
1.6x
Month 1 Month 2 Month 3 Month 4 Month 5 Month 6 Month 7 Month 8
Forw
ard
Vo
lati
lity
Te
rm S
tru
ctu
re
Forward Volatility (October 2012) Historical Average Forward Volatility (since 2004)
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Bet on unknown unknowns… don’t hedge known unknowns
19
Sell “known unknowns” and Buy “unknown unknowns”… …monetize the bull market in fear by playing the term structure
Fear Arbitrage (Volatility futures & Options, SPX Vol Term Structure)
Known-Unknown Crash Unknown Unknown Crash
US EquityIntl. Equity (Dev)Intl. Equity (Emerg)UST 30yrUST 10yrHY BondsOilGold
0%
10%
20%
30%
40%
50%
60%
-3.0σ
-2.5σ
-2.0σ
-1.5σ
-1.0σ
-0.5σ
+0.0σ
+0.5σ
+1.0σ
+1.5σ
+2.0σ
+2.5σ
Pro
bab
ility
Of
Ret
urn
Expected 1yr Asset Return Distributionby Standard Deviation (Historical)
US EquityIntl. Equity (Dev)Intl. Equity (Emerg)UST 30yrUST 10yrHY BondsOilGold
0%
10%
20%
30%
40%
50%
60%
-3.0
σ
-2.5
σ
-2.0
σ
-1.5
σ
-1.0
σ
-0.5
σ
+0.0
σ
+0.5
σ
+1.0
σ
+1.5
σ
+2.0
σ
+2.5
σ
Pro
bab
ilit
y O
f R
etu
rn
Expected 1yr Asset Class Return Distribution by Standard Deviation (Historical)
BU
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The more people fear the LEFT TAIL the more you should buy the RIGHT… and vice versa
20
Role of the trader is not so much to predict the future but to identify mispriced risk The options market is consistently late to the game in pricing both the right and left tails
financial crash options market is marked by the transfer of risk premium from the right of the return distribution to the left tail
2012 Pre-Crisis 2008
Right Tail Bias
Left tail bias
Cross Asset Implied Probability Distribution Comparison (2008 pre-crisis to 2012) Variance Swap Weighting { SPY, EFA, EEM, TLT, IEF, HYG, USO, GLD }
US EquityIntl. Equity (Dev)Intl. Equity (Emerg)UST 30yrUST 10yrHY BondsOilGold
0%
10%
20%
30%
40%
50%
60%
-3.0σ
-2.5σ
-2.0σ
-1.5σ
-1.0σ
-0.5σ
+0.0σ
+0.5σ
+1.0σ
+1.5σ
+2.0σ
+2.5σ
Pro
bab
ility
Of
Ret
urn
Expected 1yr Asset Return Distributionby Standard Deviation (Historical)
Note: Artemis calculates the implied probability distribution using interpolated weights from variance swap pricing. This methodology may give higher weightings to tails in down markets than more traditional methods like taking the second derivative of call prices, fitting mixture of normal PDFs to recover prices, or fitting vol models (SVI,SABR).
0%
5%
10%
15%
20%
-50% -43% -35% -28% -20% -13% -5% +3% +10% +18% +25% +33% +40% +48%
Cu
mu
lati
ve P
rob
abili
ty W
eig
hti
ng
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)
BU
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The more people fear the LEFT TAIL the more you should buy the RIGHT…
21
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 a generalized 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% by 2015 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 decade at +9.94% but adjusted for inflation this drops to -9.8%.
…but it is a valuable exercise to theorize! … Volatility markets turn
0%
5%
10%
20.0%30.0%40.0%
0
500
1,000
1,500
2,000
2,500
15%20%
25%30%
35%40%
45%
50%
5yr UST Yield
Val
ue
of C
all O
pti
on
5yr implied vol
Double Convexity in Inflation Boom SPX 10yr OTM Call - 10K Strike
5 yrs to expiry/ SPX @ 3,000 (16% annual gain)
Future?
100
150
200
250
300
350
400
450
500
550
600
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Gro
wth
of
$1
00
Period of Steep Vol Slope (1yr VarK / VIX > 1.10)
S&P 500 Index
Tactical Allocation to S&P 500 during periods with Steep Vol Slope
75
175
275
375
475
575
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Gro
wth
of
$1
00
Period of Steep Vol Slope (1yr VarK / VIX > 1.10)
S&P 500 Index
Tactical Allocation to S&P 500 during periods with Steep Vol Slope
05
101520253035404550
1-1
88
15
-18
84
9-1
88
71
-18
91
5-1
89
49
-18
97
1-1
90
15
-19
04
9-1
90
71
-19
11
5-1
91
49
-19
17
1-1
92
15
-19
24
9-1
92
71
-19
31
5-1
93
49
-19
37
1-1
94
15
-19
44
9-1
94
71
-19
51
5-1
95
49
-19
57
1-1
96
15
-19
64
9-1
96
71
-19
71
5-1
97
49
-19
77
1-1
98
15
-19
84
9-1
98
71
-19
91
5-1
99
49
-19
97
1-2
00
15
-20
04
9-2
00
71
-20
11
Cyclically Adjusted PE Ratio
(Price to Average Inflation Adjusted Earning from past 10-years)1881 to 2012
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Fear over Fundamentals
22
It is hard to have a bear market in a bull-market for fear Volatility term-structure is an effective indicator to inform equity exposure
It pays to have exposure to stocks when markets are hedged! S&P 500 index portfolio exposure based on Vol Slope
1996 to 2012
0.5
1
1.5
2
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012
Ra
tio
Volatility Term Structure1-year Volatility / 1-month Volatility
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Risk Free Assets are Risky
23
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!
0.00x
0.20x
0.40x
0.60x
0.80x
May-03 May-04 May-05 May-06 May-07 May-08 May-09 May-10 May-11 May-12
TLT 20+ US Treasury Bond ETF - 5% OTM Vol Skew
Yield to Risk / UST Bond vs. "Volatility Bond" (Collateralized Short Put on S&P 500 index)Investment Stress Test #1 Stress Test #2 Stress Test #3 Stress Test #4
Volatility Bond / Short SPX Put + Collateral SPX ↓ -9% SPX ↓ -14% SPX ↓ -25% SPX ↓ -50%
Yield MaturityEst. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
SPX Put (Strike @-25%) 2.69% 1 year -2% 68% 1.373x -4% 39% 0.616x -11% 13% 0.242x -33% 2% 0.081x
SPX Put (Strike @2009 lows) 0.51% 1 year -0.4% 68% 1.319x -0.9% 39% 0.588x -3% 13% 0.176x -15% 2% 0.034x
US Treasury Bond UST Rates ↑ 100bps UST Rate ↑ 200bps UST Rate ↑ 325bps UST Rate ↑ 600bps
Yield MaturityEst. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
US Treasury Bond / 10-year 1.87% 10 years -9% 68% 0.214x -17% 39% 0.113x -25% 13% 0.074x -41% 2% 0.045x
US Treasury Bond /30-year 3.09% 30 years -18% 68% 0.176x -31% 39% 0.099x -44% 13% 0.070x -62% 2% 0.050x
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
-65%-55%-45%-35%-25%-15%-5%
1yr Volatility Bond (short OTM SPX Put Option Collateralized)
Lond Dated UST Bonds
Risk / Unrealized Loss in Stress Test Scenario
SPX ↓ -9% to -14% 68% to 33% probability
SPX ↓ -50% 2% probability
10yr UST Bond
30yr UST Bond
SPX Short Put (Strike @-25% OTM)
Rates ↑ 320bps to 600bps 13% to 2% probability
Rates ↑ 100bps to 200bps 68% to 33% probability
Note: All data as of September 14, 2012. 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 the instrument. 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)
Ret
urn
/ Y
ield
50
100
150
200
250
Oct-0
8
Dec-0
8
Feb-0
9
Ap
r-09
Jun
-09
Au
g-09
Oct-0
9
Dec-0
9
Feb-1
0
Ap
r-10
Jun
-10
Au
g-10
Oct-1
0
Dec-1
0
Feb-1
1
Ap
r-11
Jun
-11
Au
g-11
Oct-1
1
Dec-1
1
Feb-1
2
Ap
r-12
Jun
-12
Au
g-12
Oct-1
2
Interest Rate Volatility is Low... and a better bargain on a forward basis than equity vol
Merrill Lynch MOVE Index = VIX for UST BondsWeighted Volatility of 2yr,5yr,10yr & 20yr UST
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Yield to Risk / UST Bond vs. "Volatility Bond" (Collateralized Short Put on S&P 500 index)Investment Stress Test #1 Stress Test #2 Stress Test #3 Stress Test #4
Volatility Bond / Short SPX Put + Collateral SPX ↓ -9% SPX ↓ -14% SPX ↓ -25% SPX ↓ -50%
Yield MaturityEst. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
SPX Put (Strike @-25%) 2.69% 1 year -2% 68% 1.373x -4% 39% 0.616x -11% 13% 0.242x -33% 2% 0.081x
SPX Put (Strike @2009 lows) 0.51% 1 year -0.4% 68% 1.319x -0.9% 39% 0.588x -3% 13% 0.176x -15% 2% 0.034x
US Treasury Bond UST Rates ↑ 100bps UST Rate ↑ 200bps UST Rate ↑ 325bps UST Rate ↑ 600bps
Yield MaturityEst. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
Est. MTM
Loss
Historic Prob.
%
Risk to
Reward
US Treasury Bond / 10-year 1.87% 10 years -9% 68% 0.214x -17% 39% 0.113x -25% 13% 0.074x -41% 2% 0.045x
US Treasury Bond /30-year 3.09% 30 years -18% 68% 0.176x -31% 39% 0.099x -44% 13% 0.070x -62% 2% 0.050x
0.0%
0.5%
1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
-65%-55%-45%-35%-25%-15%-5%
1yr Volatility Bond (short OTM SPX Put Option Collateralized)
Lond Dated UST Bonds
Source: Bloomberg
When risk-free is risky … it is time to buy volatility on safety itself
Higher interest rate volatility can be realized in deflation and inflation
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Volatility of an Impossible Object
25 Illustration 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
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Volatility of an Impossible Object
26
the next “Unknown Unknown” Crash… What is not priced into markets that will seem as obvious in 10 years as it is
laughable today?
Today everyone is afraid of the next 2008
I am afraid of the next 1987…. possibly for stocks…
but more likely bonds
Fracture between the fundamental
and the abstract is a source of great risk
Bull Market in Fear is prepared for yesterday’s crash… you want to be hedged for what happens tomorrow
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Post-Modern Economy
27
Post-Modern Economy & “Simulacra and Simulation” Baudrillard recalls Borges fable about cartographers of a great empire who drew a detailed map
When the empire collapses the map is accepted as truth and the empire forgotten In the postmodern economy market expectations are more important to fundamental growth
than the reality of supply and demand the market was designed to mimic
What Baudrillard calls “the desert of the real” is what Bernanke identifies as the “wealth effect” The real economy is not slave to the shadow banking system… our economy IS the
shadow banking system… the empire is gone and we live in the abstraction
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Volatility can be more than just FEAR
28
Volatility is the perfect post-modern asset class for our existential economic future…
Volatility
Fiat Currency
Volatility Markets
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Truth and Volatility
29
Volatility as a concept is widely misunderstood. Volatility is not fear. Volatility is not the
VIX index. Volatility is not a statistic or a standard deviation, Black-Scholes input, or any
other number derived by abstract formula.
Volatility is no different in markets than it is to life.
Regardless of how it is measured volatility reflects the difference between the world
as we imagine it to be and the world that actually exists
We will only prosper if we relentlessly search for nothing but the truth, otherwise
the truth will find us through volatility
Volatility is an instrument of truth
the Truth is that Capitalism can save us… but First We Must Find a Way to Save Capitalism
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Christopher Cole, CFA – General Partner and Founder Contact Information Reference Material & Acknowledgements
30
Artemis Research:
Volatility of an Impossible Object: Risk, Fear, and Safety in Games of Perception
Volatility at World’s 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 at World's End" by Brendan Wiuff 2012 / copyright owned by Artemis Capital Management LLC
"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, Devil’s Turning Fork & Necker’s Cube” Derrick Coetzee / Public Domain
"Liberty Leading the People" by Eugène Delacroix 1830 / public domain
Ocean wave pictures provided by istockphoto.com
Reference Material:
“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 Practitioner’s Model” Maneesh Deshpande / May 19 2011
“Understanding VIX Futures and Options” Dennis Dzekounoff; Futures Magazine/ August 2010
“The Volatility Surface: A Practitioner’s 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
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Christopher Cole, CFA – General Partner and Founder
Artemis Vega Fund L.P. Artemis Capital Management, L.L.C.
520 Broadway, Suite 350 Santa Monica, CA 90401
[email protected] www.artemiscm.com
Christopher Cole, CFA
Managing Partner & Portfolio Manager (310) 496-4526 phone
(310) 496-4527 fax [email protected]
Contact Information Artemis Capital Management – Contact Information
31
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 the Artemis Vega Fund LP. Mr. Cole’s 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 significant proprietary returns during the 2008 financial crash trading volatility futures. His research letters and volatility 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 capital markets and investment banking at Merrill Lynch. During his career in investment banking and pension consulting 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, and graduated Magna Cum Laude from the University of Southern California.
Key Information/ Biography
LEG
AL D
ISCLA
IMER
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 FUND’S MEMORANDUM. THE INFORMATION HEREIN IS QUALIFIED IN ITS ENTIRETY BY THE INFORMATION IN THE 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 BE ACCURATE, BUT WE CANNOT GUARANTEE THE ACCURACY OF SUCH INFORMATION.
32
DISC
LOSU
RE
General Disclosure Statement
An investment in the Partnership and strategies discussed in this document involve a number of significant risks. For a full list of potential risk factors please review the
Offering Memorandum. Prospective Limited Partners should read the entire Memorandum and the Partnership Agreement and consult with their own advisers before
deciding whether to invest in the Partnership. In addition, as the Partnership’s investment program develops and changes over time, an investment in the Partnership may
be subject to additional and different risk factors. Prospective investors should also consult with their own financial, tax and legal advisors regarding the suitability of this
investment. Artemis Capital Management, L.L.C. does not guarantee returns and investors bear the risk of losing a substantial portion of or potentially their entire
investment.
All 2009 performance numbers quoted within this document are derived from financial statements that were audited by Spicer Jeffries. Proprietary trading results for
White Fox, LLC (the “Proprietary Account”) are presented within this document that were verified by Spicer Jeffries. The Principal of the General Partner, Christopher R.
Cole, used the Proprietary Account as a vehicle to incubate the investment strategy of the Partnership with personal funds as well as those of close family members. Note
that no management or performance fees were charged to the Proprietary Account profiled. Accordingly, the Pro Forma Performance presented in this document includes
imposition of a 2% Management Fee and 20% Performance Allocation (in line with those charged against the Partnership).Past performance is not indicative of future
returns.
Commodity Pool Operator Disclosure Statement
YOU SHOULD CAREFULLY CONSIDER WHETHER YOUR FINANCIAL CONDITION PERMITS YOU TO PARTICIPATE IN A COMMODITY POOL. IN SO DOING, YOU SHOULD BE
AWARE THAT FUTURES AND OPTIONS TRADING CAN QUICKLY LEAD TO LARGE LOSSES AS WELL AS GAINS. SUCH TRADING LOSSES CAN SHARPLY REDUCE THE NET
ASSET VALUE OF THE POOL AND CONSEQUENTLY THE VALUE OF YOUR INTEREST IN THE POOL. IN ADDITION, RESTRICTIONS ON REDEMPTIONS MAY AFFECT YOUR
ABILITY TO WITHDRAW YOUR PARTICIPATION IN THE POOL.
FURTHER, COMMODITY POOLS MAY BE SUBJECT TO SUBSTANTIAL CHARGES FOR MANAGEMENT, ADVISORY AND BROKERAGE FEES. IT MAY BE NECESSARY FOR
THOSE POOLS THAT ARE SUBJECT TO THESE CHARGES TO MAKE SUBSTANTIAL TRADING PROFITS TO AVOID DEPLETIONS OR EXHAUSTION OF THEIR ASSETS. THE
OFFERING MEMORANDUM CONTAINS A COMPLETE DESCRIPTION OF EACH EXPENSE TO BE CHARGED THIS POOL AND A STATEMENT OF THE PERCENTAGE RETURN
NECESSARY TO BREAK EVEN, THAT IS, TO RECOVER THE AMOUNT OF YOUR INITIAL INVESTMENT .
THIS BRIEF STATEMENT CANNOT DISCLOSE ALL THE RISKS AND OTHER FACTORS NECESSARY TO EVALUATE YOUR PARTICIPATION IN THIS COMMODITY POOL.
THEREFORE, BEFORE YOU DECIDE TO PARTICIPATE IN THIS COMMODITY POOL, YOU SHOULD CAREFULLY STUDY THE OFFERINGMEMORANDUM, INCLUDING A
DESCRIPTION OF THE PRINCIPAL RISK FACTORS OF THIS INVESTMENT.
YOU SHOULD ALSO BE AWARE THAT THIS COMMODITY POOL MAY TRADE FOREIGN FUTURES OR OPTIONS CONTRACTS. TRANSACTIONS ON MARKETS LOCATED
OUTSIDE THE UNITED STATES, INCLUDING MARKETS FORMALLY LINKED TO A UNITED STATES MARKET, MAY BE SUBJECT TO REGULATIONS WHICH OFFER DIFFERENT
OR DIMINISHED PROTECTIONS TO THE POOL AND ITS PARTICIPANTS. FURTHER, UNITED STATES REGULATORY AUTHORITIES MAY BE UNABLE TO COMPEL THE
ENFORCEMENT OF THE RULES OR REGULATORY AUTHORITIES OR MARKETS IN NON-UNITED STATES JURISDICTIONS WHERE TRANSACTIONS FOR THE POOL MAY BE
EFFECTED.
33