Mao, XiupingCzellar, VeronikaRuiz Ortega, EstherLopes Moreira Da Veiga, María Helena2022-06-012022-06-012020-01-01Mao, X., Czellar, V., Ruiz, E., & Veiga, H. (2020). Asymmetric stochastic volatility models: Properties and particle filter-based simulated maximum likelihood estimation. Econometrics and Statistics, 13, pp. 84-105.2452-3062https://hdl.handle.net/10016/34968The 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. Itis 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 itafter 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 mostadequate specification of the asymmetry can change over time.eng© 2019 EcoSta Econometrics and Statistics. Published by Elsevier B.V. All rights reserved.Atribución-NoComercial-SinDerivadas 3.0 EspañaLeverage effectParticle filteringSV modelsValue-at-riskresearch articleEstadísticahttps://doi.org/10.1016/j.ecosta.2019.08.002open access84105Econometrics and Statistics13AR/0000025524