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

publication date

  • January 2020

start page

  • 84

end page

  • 105

volume

  • 13

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 analyt- ical 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 max- imum 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 fore- casts 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

  • leverage effect; particle filtering; sv models; value-at-risk