Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation

Xiuping Mao, Veronika Czellar, Esther Ruiz () and Helena Veiga

Econometrics and Statistics, 2020, vol. 13, issue C, 84-105

Abstract: 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.

Keywords: Particle filtering; Leverage effect; SV models; Value-at-risk (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecosta:v:13:y:2020:i:c:p:84-105

DOI: 10.1016/j.ecosta.2019.08.002

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