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Empirical Performance of Alternative Option Pricing Models

Listed author(s):
  • Charles Quanwei Cao


    (Department of Finance)

  • Gurdip S. Bakshi


    (University of Maryland, Robert H. Smith School of Business)

  • Zhiwu Chen


    (International Center for Finance)

Substantial progress has been made in extending the Black- Scholes model to incorporate such features as stochastic volatility, stochastic interest rates and jumps. On the empirical front, however, it is not yet known whether and by how much each generalized feature will improve option pricing and hedging performance. This paper fills this gap by first developing an implementable option model in closed form that allows volatility, interest rates and jumps to be stochastic and that is parsimonious in the number of parameters. The model includes many known ones as special cases. Delta- neutral and single-instrument minimum-variance hedging strategies are derived analytically. Using S&P 500 options, we examine a set of 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 performance. The models of focus include the benchmark Black-Scholes formula and the ones that respectively allow for (i) stochastic volatility, (ii) both stochastic volatility and stochastic interest rates, and (iii) stochastic volatility and jumps. Overall, incorporating both stochastic volatility and random jumps produces the best pricing performance and the most internally-consistent implied-volatility process. Its implied volatility does not "smile" across moneyness. But, for hedging, adding either jumps or stochastic interest rates does not seem to improve performance any further once stochastic volatility is taken into account.

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Paper provided by Yale School of Management in its series Yale School of Management Working Papers with number ysm54.

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Date of creation: 06 Mar 1997
Handle: RePEc:ysm:somwrk:ysm54
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