Revisiting the finite mixture of Gaussian distributions with application to futures markets

Thierry Ané and Chiraz Labidi

Journal of Futures Markets, 2001, vol. 21, issue 4, 347-376

Abstract: We present a new estimation method for Gaussian mixture modeling, namely, the kurtosis‐controlled expectation‐maximization (EM) algorithm, which overcomes the limitations of the usual estimation techniques via kurtosis control and kernel splitting. Our simulation study shows that the dynamic allocation of kernels according to the value of the total kurtosis measure makes the proposed kurtosis‐controlled EM algorithm an efficient method for Gaussian mixture density estimation. This algorithm yielded considerable improvements over the classical EM algorithm. We then used the discrete Gaussian mixture framework to account for the observed thick‐tailed distributions of futures returns and applied the kurtosis‐controlled EM algorithm to estimate the distributions of real (agricultural, metal, and energy) and financial (stock index and currency) futures returns. We proved that this framework is perfectly adapted to capturing the departures from normality of the observed return distributions. Unlike in previous studies, we found that a two‐component Gaussian mixture is too poor a model to accurately capture the distributional properties of returns. Similar results have been obtained for stocks, indexes, currencies, interest rates, and commodities. This has important implications in many financial studies using Gaussian mixtures to incorporate the thickness of the tails of the distributions in the computation of the value at risk or to infer implied risk‐neutral densities from option prices, to name but a few. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21: 347–376, 2001

Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jfutmk:v:21:y:2001:i:4:p:347-376

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0270-7314

Access Statistics for this article

Journal of Futures Markets is currently edited by Robert I. Webb

More articles in Journal of Futures Markets from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley Content Delivery ().