An Empirical Comparison of Two Stochastic Volatility Models using Indian Market Data

We conduct an empirical comparison of hedging strategies for two different stochastic volatility models proposed in the literature. One is an asymptotic expansion approach and the other is the risk-minimizing approach applied to a Markov-switched geometric Brownian motion. We also compare these with...

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Bibliographic Details
Published inAsia-Pacific financial markets Vol. 20; no. 3; pp. 243 - 259
Main Authors Iyer, Srikanth K., Nanda, Seema, Kumar, Swapnil
Format Journal Article
LanguageEnglish
Published Tokyo Springer Japan 01.09.2013
Springer Nature B.V
Subjects
Brownian motion
Decomposition
Econometrics
Economic Theory/Quantitative Economics/Mathematical Methods
Economics and Finance
Finance
Hedging
International Economics
Macroeconomics/Monetary Economics//Financial Economics
Markov analysis
Mathematics
Optimization techniques
Parameter estimation
Partial differential equations
Put & call options
Random variables
Stochastic models
Stock exchanges
Volatility
India
C02
Option pricing
Risk minimizing
Regime switching
Stochastic volatility
G13
C90
Mean reverting
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Summary:We conduct an empirical comparison of hedging strategies for two different stochastic volatility models proposed in the literature. One is an asymptotic expansion approach and the other is the risk-minimizing approach applied to a Markov-switched geometric Brownian motion. We also compare these with the Black–Scholes delta hedging strategies using historical and implied volatilities. The derivatives we consider are European call options on the NIFTY index of the Indian National Stock Exchange. We compare a few cases with profit and loss data from a trading desk. We find that for the cases that we analyzed, by far the better results are obtained for the Markov-switched geometric Brownian motion.
ISSN:1387-2834
1573-6946
DOI:10.1007/s10690-013-9166-3