# Probability distribution of returns in the Heston model with stochastic volatility

*Adrian A. Dragulescu* and
*Victor Yakovenko* ()

Papers from arXiv.org

**Abstract:**
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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**Related works:**

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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