SUMMER RESEARCH PROJECT DANIEL GUETTA with PROF. PAUL GLASSERMAN Detecting Bubbles Using Option...
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Transcript of SUMMER RESEARCH PROJECT DANIEL GUETTA with PROF. PAUL GLASSERMAN Detecting Bubbles Using Option...
SUMMER RESEARCH PROJECT
DANIEL GUET TAwith PROF. PAUL GLASSERMAN
Detecting Bubbles Using Option Prices
Bubbles
What is a Bubble?
Bubbles are often associated with a large increase in the asset price followed by a collapse when the bubble “bursts”.
In the context of financial markets, bubbles refer to asset prices that exceed the asset's fundamental, intrinsic value possibly because those that own the asset believe that they can sell the asset at a higher price in the future.
What is a Bubble?
“Asset Price Bubbles in Complete Markets”, Jarrow, Protter & Shimbo, 2007
“Asset Price Bubbles in Incomplete Markets”, Jarrow, Protter & Shimbo, 2010
A Very (Very, Very) Short Introduction to Financial Math
Financial Mathematics
tS
t
Google Stock – 1st January 2007 to 1st January 2011
t
d ( , ) d ( , ) dt t t t t t
S S t S t S t S Wm s= +
Financial Mathematics
d ( , ) d ( , ) dt t t t t t
S S t S t S t S Wm s= +
d ( , ) dt t t t
S S t S Ws=
First Fundamental Theorem of Asset Pricing
Price Distributions
Price Distributions
Price Distributions
Price Distributions
Price Distributions
Price Distributions
1T
Price Distributions
1T
2T
The Kolmogorov Forward Equation
22 2
2
1( ) ( , ) ( )
2t tx x t x x
t xf s f
¶ ¶ é ù= ê úë û¶ ¶
d ( , ) dt t t t
S S t S Ws= ( )t t
Sf
Detecting Bubbles
The Bubble Test
Assumption:
d ( , ) dt t t t
S S t S Ws=
“How to Detect an Asset Bubble”, Jarrow, Kchia & Protter, March 2011
The Bubble Test
2 d
( )
xx
xa s
¥< ¥ò
Bubble exists in the asset price St
St is a strict local martingale
Assumption:
d ( ) dt t t t
S S S Ws=
“How to Detect an Asset Bubble”, Jarrow, Kchia & Protter, March 2011
Using Options to Find
What is an Option?
( ),K T
When time T comes along, the call option gives its owner the right, but not the obligation, to buy one unit of the financial asset at price K.
Strike Maturity
Pricing Options
( )( )Payoff at maturity
max[ ,0]
max( ,0) ( )
( , )
dT
T
S K
x
C K T
K x xf
= -
=
=
-ò
E
E
KT
S
Payoff
Magic!
2
2
2
2
( , )
d( , ) step( ) ( ) d
dd
( , )
max( ,0)
( ) ( ) dd
d( , ) ( )
d
( ) d
T
T
T
T
C K T
C K T x K x xK
C K T x K x xK
C K T KK
x K x x
f
f
d f
f
= - -
= -
=
= -
ò
ò
ò
x
The Dupire Equation
22 2
2
1( ) ( , ) ( )
2t tx x t x x
t xf s f
¶ ¶ é ù= ê úë û¶ ¶
2
2
d( , ) ( )
d T
CK T K
Kf=+
2
221
2 2
( , )
CTK T
CK
K
s
¶¶=
¶
¶
=
Kolmogorov Forward Equation
The Dupire Equation
Reality
Optio
n
price
MaturityStrike
1st September 2006, Options on the S&P 500
Local Least Squares
“Arbitrage-free Approximation of Call Price Surfaces and Input Data Risk”, Glaser and
Heider, March 2010
Local Least Squares
Optio
n
price
Maturity
Strike
1st September 2006, calls
Local Least Squares
Optio
n
price
Maturity
Strike
Local Least Squares
Optio
n
price
Maturity
Strike
Local Least Squares
Optio
n
price
Maturity
Strike
Local Least Squares
Optio
n
price
Maturity
Strike
Local Least Squares
Optio
n
price
Maturity
Strike
21 2 3 4
( , )C K T a a K a K aT= + + +
Local Least Squares
Optio
n
price
Maturity
Strike
1st September 2006, calls
Local Least Squares
Optio
n
price
Maturity
Strike
1st September 2006, calls
The Local Volatility
2(K
,T)
K
T
1st March 2004, calls
The Local Volatility
2(K
,T)
KT
2nd July 2007, calls
The Local Volatility
2(K
,T)
KT
2nd July 2007, puts
Results
2 d B b
)l
(u b e
xx
xa s
¥Û< ¥ò
Bubble Indicator
Date
Bubble Indicator
Date
VIX
In
dex
Correlation coefficient: 0.15
Bubble Indicator
Date
S&
P 5
00
2 d B b
)l
(u b e
xx
xa s
¥Û< ¥ò
Correlation coefficient: 0.01
Concluding Remarks
Conclusions
A promising approach to implementing the bubble test.
The non-parametric approach we used might have been slightly too ambitious.
Fitting options prices rather than volatilities might have compounded the problem.
Other Approaches
Use some sort of spline (“Reconstructing the Unknown Volatility Function”, Coleman, Li and Verma, “Computation of Deterministic Volatility Surfaces”, 2001. Jackson, Suli and Howison, 1999. “Improved Implementation of Local Volatility and Its Application to S&P 500 Index Options”, 2010.)
Estimate the local volatility via the implied volatility.
Other Approaches
Assume the volatility is piecewise constant, and solve the Dupire Equation to find the “best” constants. (“Volatility Interpolation”, Andreasen and Huge, 2011).
Assume some sort of parametric pricing model (such as Heston or SABR), fit to option price data and then deduce local volatility.
Questions