Empirical Performance of Alternative Option Pricing Models

1997/12/01 by Gurdip Bakshi, Charles Cao, Zhiwu Chen · 2,728 citations
Economics, Econometrics and Finance · Mathematics · Social Sciences · #Capital Investment and Risk Analysis #Computer science #Consistency (knowledge bases) #Econometrics #Economics #Financial economics #Generalization #Implied volatility #Insurance, Mortality, Demography, Risk Management #Mathematics #SABR volatility model #Stochastic processes and financial applications #Stochastic volatility #Valuation of options #Volatility (finance) #Volatility smile #Volatility swap

paper · pdf · doi:10.1111/j.1540-6261.1997.tb02749.x

published in The Journal of Finance 52(5), 2003-2049 (Wiley)

openalex publication_date 1997/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

ABSTRACT Substantial progress has been made in developing more realistic option pricing models. Empirically, however, it is not known whether and by how much each generalization improves option pricing and hedging. We fill this gap by first deriving an option model that allows volatility, interest rates and jumps to be stochastic. Using S&P 500 options, we examine several alternative models from three perspectives: (1) internal consistency of implied parameters/volatility with relevant time‐series data, (2) out‐of‐sample pricing, and (3) hedging. Overall, incorporating stochastic volatility and jumps is important for pricing and internal consistency. But for hedging, modeling stochastic volatility alone yields the best performance.

Citations

• Conditional Heteroskedasticity in Asset Returns: A New Approach
• The Pricing of Options and Corporate Liabilities
• A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity

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