Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH

DOI10.1016/j.csda.2007.09.031zbMath1452.62787OpenAlexW2011780523MaRDI QIDQ1023615

Helena Veiga, Esther Ruiz Ortega

Publication date: 12 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10016/5024

zbMATH Keywords

kurtosisconditional heteroscedasticityautocorrelations of squares and of absolute valuesEMM estimator

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Computational methods for problems pertaining to statistics (62-08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Related Items (10)

Realized stochastic volatility with leverage and long memory ⋮ On the estimation and diagnostic checking of the ARFIMA-HYGARCH model ⋮ A threshold stochastic volatility model with explanatory variables ⋮ Implied volatility in oil markets ⋮ A note on the properties of power-transformed returns in long-memory stochastic volatility models with leverage effect ⋮ Persistence in volatility, conditional kurtosis, and the Taylor property in absolute value GARCH processes ⋮ Theoretical results on fractionally integrated exponential generalized autoregressive conditional heteroskedastic processes ⋮ Editorial: Special issue on statistical and computational methods in finance ⋮ Modelling the US, UK and Japanese unemployment rates: fractional integration and structural breaks ⋮ MCMC Bayesian Estimation in FIEGARCH Models

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