Volatility spillovers, interdependence and comovements: a Markov switching approach

DOI10.1016/j.csda.2007.09.016zbMath1452.62766OpenAlexW2078790260MaRDI QIDQ1023631

Edoardo Otranto, Giampiero M. Gallo

Publication date: 12 June 2009

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

Full work available at URL: https://doi.org/10.1016/j.csda.2007.09.016

zbMATH Keywords

Markov switchingvolatilityspillover effectcomovementsmultiple chains

Mathematics Subject Classification ID

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 (12)

Multivariate Wishart stochastic volatility and changes in regime ⋮ Sovereign credit ratings, market volatility, and financial gains ⋮ A wavelet-based approach to test for financial market contagion ⋮ A Markov-switching regression model with non-Gaussian innovations: estimation and testing ⋮ Identifying financial time series with similar dynamic conditional correlation ⋮ Market linkages, variance spillovers, and correlation stability: empirical evidence of financial contagion ⋮ Bayesian causal effects in quantiles: accounting for heteroscedasticity ⋮ Capturing the Spillover Effect With Multiplicative Error Models ⋮ A time varying hidden Markov model with latent information ⋮ Editorial: Special issue on statistical and computational methods in finance ⋮ Clustering heteroskedastic time series by model-based procedures ⋮ Measuring contagion of subprime crisis based on MVMQ-CAViaR method

Cites Work

• Risk, jumps, and diversification
• Analysis of time series subject to changes in regime
• Stylized facts of financial time series and hidden semi-Markov models
• Nonlinear dynamics in Nasdaq dealer quotes
• Simulation-based sequential analysis of Markov switching stochastic volatility models
• Dynamic linear models with Markov-switching
• Autoregressive conditional heteroskedasticity and changes in regime
• Markov-switching vector autoregressions. Modelling, statistical inference, and application to business cycle analysis
• Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
• A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle

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