Asymmetric Stochastic Volatility Models: Properties and ABC Filter-based Maximum Likelihood Estimation
56 Pages Posted: 3 Jan 2015 Last revised: 15 Dec 2016
Date Written: December 13, 2016
Abstract
In this paper, we derive the statistical properties of a general family of Stochastic Volatility (SV) models with leverage effect which capture the dynamic evolution of asymmetric volatility in financial returns. We provide analytical expressions of moments and autocorrelations of power-transformed absolute returns. Moreover, we use an Approximate Bayesian Computation (ABC) filter-based Maximum Likelihood (ML) method to estimate the parameters of the SV models. In Monte Carlo simulations we show that the ABC filter-based ML accurately estimates the parameters of a very general specification of the log-volatility with standardized returns following the Generalized Error Distribution (GED). The results are illustrated by analyzing series of daily S&P 500 and MSCI World returns.
Keywords: ABC filtering, Leverage effect, SV models, Value-at-Risk
JEL Classification: C11, C51, C58
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