{"title":"Stochastic Volatility Models for Asset Returns with Leverage, Skewness and Heavy-Tails via Scale Mixture","authors":"Jing-Zhi Huang, Li Xu","doi":"10.1142/S2010139214500116","DOIUrl":null,"url":null,"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.","PeriodicalId":45339,"journal":{"name":"Quarterly Journal of Finance","volume":"23 1","pages":"1450011"},"PeriodicalIF":0.9000,"publicationDate":"2014-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quarterly Journal of Finance","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1142/S2010139214500116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 2
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.
期刊介绍:
The Quarterly Journal of Finance publishes high-quality papers in all areas of finance, including corporate finance, asset pricing, financial econometrics, international finance, macro-finance, behavioral finance, banking and financial intermediation, capital markets, risk management and insurance, derivatives, quantitative finance, corporate governance and compensation, investments and entrepreneurial finance.