Goodness-of-fit of the Heston model
| dc.creator | Daniel, Gilles | |
| dc.date | 2003-05-29 | |
| dc.date.accessioned | 2026-07-07T03:19:44Z | |
| dc.date.available | 2026-07-07T03:19:44Z | |
| dc.description | An analytical formula for the probability distribution of stock-market returns, derived from the Heston model assuming a mean-reverting stochastic volatility, was recently proposed by Dragulescu and Yakovenko in Quantitative Finance 2002. While replicating their results, we found two significant weaknesses in their method to pre-process the data, which cast a shadow over the effective goodness-of-fit of the model. We propose a new method, more truly capturing the market, and perform a Kolmogorov-Smirnov test and a Chi Square test on the resulting probability distribution. The results raise some significant questions for large time lags -- 40 to 250 days -- where the smoothness of the data does not require such a complex model; nevertheless, we also provide some statistical evidence in favour of the Heston model for small time lags -- 1 and 5 days -- compared with the traditional Gaussian model assuming constant volatility. | |
| dc.description | 10 pages, 3 figures, The 9th International Conference of Computing in Economics and Finance, Seattle (July 2003) | |
| dc.identifier | https://arxiv.org/abs/cs/0305055 | |
| dc.identifier | http://arxiv.org/abs/cs/0305055 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/31582 | |
| dc.subject | Computational Engineering, Finance, and Science | |
| dc.subject | G3 | |
| dc.title | Goodness-of-fit of the Heston model | |
| dc.type | text |