44 Pages Posted: 7 Jan 2011 Last revised: 10 Oct 2012
Date Written: October 9, 2012
We provide a new alternative to thin-tailed regression models by introducing robust numerical methods, based on the minimum relative U−entropy (MRUE) principle, to estimate heteroskedastic, fat-tailed, flexible univariate probability density functions, conditioned on a number of explanatory variables. We benchmark our method against state-of-the-art asset return models on the 30 constituents of the Dow 30 and find that our models outperform the benchmarks out-of-sample.
Keywords: Minimum Relative U−Entropy, Conditional Probability Distribution, Fat-tailed, Power-Law Distribution, Heteroskedastic, Financial Data, Asset Returns
Suggested Citation: Suggested Citation
Friedman, Craig A. and Zhang, Yangyong and Cao, Wenbo, Estimating Flexible, Fat-Tailed Conditional Asset Return Distributions (October 9, 2012). Available at SSRN: https://ssrn.com/abstract=1735522 or http://dx.doi.org/10.2139/ssrn.1735522