Robust bootstrap densities for dynamic conditional correlations: implications for portfolio selection and Value-at-Risk

DOI10.1080/00949655.2018.1462811OpenAlexW3124753439MaRDI QIDQ4960660

Carlos Trucíos, Luiz Koodi Hotta, Esther Ruiz Ortega

Publication date: 23 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2018.1462811

zbMATH Keywords

outliersMGARCHVaRminimum variance portfolioforecast density

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Editorial

Cites Work

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• Bootstrapping realized multivariate volatility measures
• Robust estimates for GARCH models
• Bootstrap prediction for returns and volatilities in GARCH models
• Accurate value-at-risk forecasting based on the normal-GARCH model
• The uncertainty of conditional returns, volatilities and correlations in DCC models
• Iterated smoothed bootstrap confidence intervals for population quantiles
• Generalized autoregressive conditional heteroscedasticity
• On the estimation of dynamic conditional correlation models
• Multivariate value at risk and related topics
• Bootstrap prediction in univariate volatility models with leverage effect
• Robust M-estimation of multivariate GARCH models
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Robust bootstrap forecast densities for GARCH returns and volatilities

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