Pricing and Hedging Long-Term Options

Charles Cao, Gurdip S. Bakshi () and Zhiwu Chen
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Gurdip S. Bakshi: University of Maryland, Robert H. Smith School of Business

Yale School of Management Working Papers from Yale School of Management

Abstract: Recent empirical studies find that once an option pricing model has incorporated stochastic volatility, allowing interest rates to be stochastic does not improve pricing or hedging any further while adding random jumps to the modeling framework only helps the pricing of extremely short-term options but not the hedging performance. Given that only options of relatively short terms are used in existing studies, this paper addresses two related questions: Do long-term options contain different information than short-term options? If so, can long-term options better differentiate among alternative models? Our inquiry starts by first demonstrating analytically that differences among alternative models usually do not surface when applied to short term options, but do so when applied to long-term contracts. For instance, within a wide parameter range, the Arrow-Debreu state price densities implicit in different stochastic-volatility models coincide almost everywhere at the short horizon, but diverge at the long horizon. Using regular options (of less than a year to expiration) and LEAPS, both written on the S&P 500 index, we find that short- and long-term contracts indeed contain different information and impose distinct hurdles on any candidate option pricing model. While the data suggest that it is not as important to model stochastic interest rates or random jumps (beyond stochastic volatility) for pricing LEAPS, incorporating stochastic interest rates can nonetheless enhance hedging performance in certain cases involving long-term contracts.

JEL-codes: G10 G12 G13 (search for similar items in EconPapers)
Date: 1998-05-06
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Citations: View citations in EconPapers (9)

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Journal Article: Pricing and hedging long-term options (2000)
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