Probability distribution of returns in the Heston model with stochastic volatility
Adrian A. Dragulescu and
Victor Yakovenko ()
Papers from arXiv.org
We study the Heston model, where the stock price dynamics is governed by a geometrical (multiplicative) Brownian motion with stochastic variance. We solve the corresponding Fokker-Planck equation exactly and, after integrating out the variance, find an analytic formula for the time-dependent probability distribution of stock price changes (returns). The formula is in excellent agreement with the Dow-Jones index for the time lags from 1 to 250 trading days. For large returns, the distribution is exponential in log-returns with a time-dependent exponent, whereas for small returns it is Gaussian. For time lags longer than the relaxation time of variance, the probability distribution can be expressed in a scaling form using a Bessel function. The Dow-Jones data for 1982-2001 follow the scaling function for seven orders of magnitude.
Date: 2002-03, Revised 2002-11
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Published in Quantitative Finance 2, 443 (2002)
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Journal Article: Probability distribution of returns in the Heston model with stochastic volatility (2002)
Working Paper: Probability distribution of returns in the Heston model with stochastic volatility (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:cond-mat/0203046
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