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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Mao, 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, 84-105
Exportar Referência (IEEE) 
X. Mao et al.,  "Asymmetric stochastic volatility models: properties and particle filter-based simulated maximum likelihood estimation", in Econometrics and Statistics, vol. 13, pp. 84-105, 2020
Exportar BibTeX 
@article{mao2020_1764921613962,
	author = "Mao, X. and Czellar, V. and Ruiz, E. and Veiga, H.",
	title = "Asymmetric stochastic volatility models: properties and particle filter-based simulated maximum likelihood estimation",
	journal = "Econometrics and Statistics",
	year = "2020",
	volume = "13",
	number = "",
	doi = "10.1016/j.ecosta.2019.08.002",
	pages = "84-105",
	url = "https://www.sciencedirect.com/journal/econometrics-and-statistics/vol/13/suppl/C"
}
Exportar RIS 
TY  - JOUR
TI  - Asymmetric stochastic volatility models: properties and particle filter-based simulated maximum likelihood estimation
T2  - Econometrics and Statistics
VL  - 13
AU  - Mao, X.
AU  - Czellar, V.
AU  - Ruiz, E.
AU  - Veiga, H.
PY  - 2020
SP  - 84-105
SN  - 2452-3062
DO  - 10.1016/j.ecosta.2019.08.002
UR  - https://www.sciencedirect.com/journal/econometrics-and-statistics/vol/13/suppl/C
AB  - 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. 
ER  -