This article is the first attempt to test empirically a numerical solution to price American options under stochastic volatility The model allows for a mean-reverting stochastic-volatility process with non-zero risk premium for the volatility risk and correlation with the underlying process. A general solution of risk-neutral probabilities and price movements is derived, which avoids the common negative-probability problem in numerical-option pricing with stochastic volatility. The empirical test shows clear evidence supporting the occurrence of stochastic volatility. The stochastic-volatility model outperforms the constant-volatility model by producing smaller bias and better goodness of fit in both the in-sample and out-of-sample test. It not only eliminates systematic moneyness bias produced by the constant-volatility model, but also has better prediction power. In addition, both models perform well in the dynamic intraday hedging test. However, the constant-volatility model seems to have a slightly better hedging effectiveness. The profitability test shows that the stochastic volatility is able to capture statistically significant profits while the constant volatility model produces losses. (C) 2000 John Wiley & Sons, Inc.
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Cent Washington Univ, Coll Business, Dept Finance & Supply Chain Management, Des Moines, WA 98198 USA
Rayliant Investment Res, 11 Zephyr, Irvine, CA 92602 USACent Washington Univ, Coll Business, Dept Finance & Supply Chain Management, Des Moines, WA 98198 USA
Pae, Yuntaek
Bae, Sung C.
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Bowling Green State Univ, Coll Business, Dept Finance, Bowling Green, OH 43403 USACent Washington Univ, Coll Business, Dept Finance & Supply Chain Management, Des Moines, WA 98198 USA
Bae, Sung C.
Lee, Namhoon
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Southern Wesleyan Univ, Sch Business, Central, SC USACent Washington Univ, Coll Business, Dept Finance & Supply Chain Management, Des Moines, WA 98198 USA