Publication

Asymmetric Stochastic Volatility Models: Properties and Particle Filter-based Simulated Maximum Likelihood Estimation

2020
Xiuping Mao ,
Esther Ruiz ,
Helena Veiga

2020, Econometrics and Statistics, 13, pp.84-105

Résumé

The statistical properties of a general family of asymmetric stochastic volatility (A-SV) models which capture the leverage effect in financial returns are derived providing analytical expressions of moments and autocorrelations of power-transformed absolute returns. The parameters of the A-SV model are estimated by a particle filter-based simulated maximum likelihood estimator and Monte Carlo simulations are carried out to validate it. It is shown empirically that standard SV models may significantly underestimate the value-at-risk of weekly S&P 500 returns at dates following negative returns and overestimate it after positive returns. By contrast, the general specification proposed provide reliable forecasts at all dates. Furthermore, based on daily S&P 500 returns, it is shown that the most adequate specification of the asymmetry can change over time.