Abstract #302127

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JSM 2003 Abstract #302127
Activity Number: 365
Type: Contributed
Date/Time: Wednesday, August 6, 2003 : 10:30 AM to 12:20 PM
Sponsor: Business & Economics Statistics Section
Abstract - #302127
Title: A Stochastic Volatility Model with Skew Error Terms
Author(s): Nicola Raria Rinaldo Loperfido*+ and Marc G. Genton
Companies: Universita Di Urbino and North Carolina State University
Address: Instituto Di Scienze Economiche, Urbino, , 61033, Italy
Keywords: generalized skew-normal ; invariance ; likelihood sufficiency
Abstract:

Stochastic volatility models are known to describe many features of financial returns, such as zero mean, changing variance, and excess kurtosis. However, when the error term is normal, they ignore the skewness which is often observed in financial data. This paper proposes a stochastic volatility model whose error term generalizes the normal one in order to describe skewness as well as the above features. The choice of the error term is motivated through arguments from economic theory. The computational burden required for model estimation is not significantly heavier than the ordinary stochastic volatility model's.

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