Stochastic volatility and the goodness-of-fit of the Heston model
Recently, Drăgulescu and Yakovenko proposed an analytical formula for computing the probability density function of stock log returns, based on the Heston model, which they tested empirically. Their research design inadvertently favourably biased the fit of the data to the Heston model, thus overstating their empirical results. Furthermore, Drăgulescu and Yakovenko did not perform any goodness-of-fit statistical tests. This study employs a research design that facilitates statistical tests of the goodness-of-fit of the Heston model to empirical returns. Robustness checks are also performed. In brief, the Heston model outperformed the Gaussian model only at high frequencies and even so does not provide a statistically acceptable fit to the data. The Gaussian model performed (marginally) better at medium and low frequencies, at which points the extra parameters of the Heston model have adverse impacts on the test statistics.
Year of publication: |
2005
|
---|---|
Authors: | Daniel, Gilles ; Joseph, Nathan ; Bree, David |
Published in: |
Quantitative Finance. - Taylor & Francis Journals, ISSN 1469-7688. - Vol. 5.2005, 2, p. 199-211
|
Publisher: |
Taylor & Francis Journals |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
Pricing Stocks with Yardsticks and Sentiments
Martinez Bustos, Sebastian, (2012)
-
Pricing stocks with yardsticks and sentiments
Sebast\ian Mart\inez Bustos, (2011)
-
Stochastic volatility and the goodness-of-fit of the Heston model
Daniel, Gilles, (2005)
- More ...