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Bayesian Tail Risk Forecasting using Realised GARCH

Contino, Christian; Gerlach, Richard H. - Business School, University of Sydney - 2014

A Realised Volatility GARCH model is developed within a Bayesian framework for the purpose of forecasting Value at Risk …-t distributions in the measurement equation in a GARCH framework to forecast tail risk in eight international equity index markets … over a four year period. Three Realised Volatility proxies are considered within this framework. Realised Volatility GARCH …

Persistent link: https://www.econbiz.de/10010938731

Bayesian time-varying quantile forecasting for Value-at-Risk in financial markets

Gerlach, Richard; Chen, Cathy W.S.; Chan, Nancy Y. C. - Business School, University of Sydney - 2009

Recently, Bayesian solutions to the quantile regression problem, via the likeli-hood of a Skewed-Laplace distribution, have been proposed. These approaches are extended and applied to a family of dynamic conditional autoregressive quantile models. Popular Value at Risk models, used for risk...

Persistent link: https://www.econbiz.de/10010533715

Bayesian time-varying quantile forecasting for Value-at-Risk in financial markets

Chan, Nancy Y. C.; Chen, Cathy W.S.; Gerlach, Richard - Business School, University of Sydney - 2009

Recently, Bayesian solutions to the quantile regression problem, via the likelihood of a Skewed-Laplace distribution, have been proposed. These approaches are extended and applied to a family of dynamic conditional autoregressive quantile models. Popular Value at Risk models, used for risk...

Persistent link: https://www.econbiz.de/10010699863