Forecasting variance using stochastic volatility and GARCH

Autor:	Peter Hördahl, Björn Hansson
Rok vydání:	2005
Předmět:	symbols.namesake Stochastic volatility Constant elasticity of variance model Gaussian Autoregressive conditional heteroskedasticity Economics Econometrics and Finance (miscellaneous) Statistics Leverage effect Econometrics symbols Economics Variance (accounting) Conditional variance
Zdroj:	The European Journal of Finance. 11:33-57
ISSN:	1466-4364 1351-847X
DOI:	10.1080/1351847021000025803
Popis:	This paper estimates the conditional variance of daily Swedish OMX-index returns with stochastic volatility (SV) models and GARCH models and evaluates the in-sample performance as well as the out-of-sample forecasting ability of the models. Asymmetric as well as weekend/holiday effects are allowed for in the variance, and the assumption that errors are Gaussian is released. Evidence is found of a leverage effect and of higher variance during weekends. In both in-sample and out-of-sample comparisons SV models outperform GARCH models. However, while asymmetry, weekend/holiday effects and non-Gaussian errors are important for the in-sample fit, it is found that these factors do not contribute to enhancing the forecasting ability of the SV models.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7637dbc47293c166b0980e89709dc1c6 https://doi.org/10.1080/1351847021000025803 Zobrazit plný text záznamu