A Continuous-Time Arbitrage-Pricing Model With Stochastic Volatility and Jumps

Abstract

We formulate and test a continuous-time asset-pricing model using U.S. equity market data. We assume that stock returns are driven by common factors including random jump-size Poisson processes and Brownian motions with stochastic volatility. The model places overidentifying restrictions on the mean returns, allowing one to identify risk-neutral probability distributions useful in pricing derivative securities. We test for the restrictions and decompose moments of the asset returns into the contributions made by different factors. Our econometric methods take full account of time aggregation.

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