Risk–return relationship in equity markets: using a robust GMM estimator for GARCH-M models

DOI10.1080/14697680801898584zbMath1171.91332OpenAlexW1995358251MaRDI QIDQ3182651

Beum J. Park

Publication date: 12 October 2009

Published in: Quantitative Finance (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/14697680801898584

zbMATH Keywords

additive outliersrisk premiumfinite-sample biasrisk-return relationshipGARCH-M modelrobust GMM estimation

Mathematics Subject Classification ID

Auctions, bargaining, bidding and selling, and other market models (91B26)

Related Items (1)

GMM estimation of a realized stochastic volatility model: A Monte Carlo study

Cites Work

• Large Sample Properties of Generalized Method of Moments Estimators
• ARCH modeling in finance. A review of the theory and empirical evidence
• GMM inference when the number of moment conditions in large
• Market efficiency, asset returns, and the size of the risk premium in global equity markets.
• A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• The Influence Curve and Its Role in Robust Estimation
• Robust Estimation of the First-Order Autoregressive Parameter
• Inference in Arch and Garch Models with Heavy-Tailed Errors
• Robust inference with GMM estimators

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