Factor Stochastic Volatility in Mean Models: A GMM Approach

DOI10.1080/07474930600713325zbMath1113.62128OpenAlexW2074705079MaRDI QIDQ5485106

Catherine Doz, Eric Renault

Publication date: 28 August 2006

Published in: Econometric Reviews (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07474930600713325

zbMATH Keywords

asset pricingstochastic volatilitygeneralized method of momentscommon featuresmultiperiod conditional moment restrictionsconditional factor modelsmultivariate conditional heteroskedasticity

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.) (60J70)

Related Items (8)

Multivariate Wishart stochastic volatility and changes in regime ⋮ Indirect estimation of large conditionally heteroskedastic factor models, with an application to the Dow 30 stocks ⋮ ON STANDARD INFERENCE FOR GMM WITH LOCAL IDENTIFICATION FAILURE OF KNOWN FORMS ⋮ Bootstrapping the GMM overidentification test under first-order underidentification ⋮ Inference in second-order identified models ⋮ The asymptotic properties of GMM and indirect inference under second-order identification ⋮ Method of moments estimation of GO-GARCH models ⋮ Multivariate Stochastic Volatility: A Review

Cites Work

• Closing the GARCH gap: Continuous time GARCH modeling
• Marginalization and contemporaneous aggregation in multivariate GARCH processes
• Temporal aggregation of volatility models
• Funds, Factors, and Diversification in Arbitrage Pricing Models
• Efficiency Bounds Implied by Multiperiod Conditional Moment Restrictions
• Volatility and Links between National Stock Markets
• Transform Analysis and Asset Pricing for Affine Jump-diffusions
• Likelihood-Based Estimation of Latent Generalized ARCH Structures
• AUTOMATED INFERENCE AND LEARNING IN MODELING FINANCIAL VOLATILITY
• Identification, estimation and testing of conditionally heteroskedastic factor models

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