Stochastic Volatility Models for Asset Returns with Leverage, Skewness and Heavy-Tails via Scale Mixture

Research output: Contribution to journalArticlepeer-review

Abstract

We propose and estimate a new class of equity return models that incorporate scale mixtures of the skew-normal distribution for the error distribution into the standard stochastic volatility framework. The main advantage of our models is that they can simultaneously accommodate the skewness, heavy-tailedness, and leverage effect of equity index returns observed in the data. The proposed models are flexible and parsimonious, and include many asymmetrically heavy-tailed error distributions-such as skew-t and skew-slash distributions-as special cases. We estimate a variety of specifications of our models using the Bayesian Markov Chain Monte Carlo method, with data on daily returns of the S&P 500 index over 1987-2009. We find that the proposed models outperform existing ones of index returns.

Original languageEnglish (US)
Article number1450011
JournalQuarterly Journal of Finance
Volume4
Issue number3
DOIs
StatePublished - Sep 1 2014

All Science Journal Classification (ASJC) codes

  • Finance
  • Economics and Econometrics
  • Strategy and Management

Fingerprint Dive into the research topics of 'Stochastic Volatility Models for Asset Returns with Leverage, Skewness and Heavy-Tails via Scale Mixture'. Together they form a unique fingerprint.

Cite this