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Diagnostics for time series analysis

Gerlach, Richard; Carter, Chris K.; Kohn, Robert - 1997

Persistent link: https://www.econbiz.de/10000965127

Bayesian semi-parametric realized conditional autoregressive expectile models for tail risk forecasting

Gerlach, Richard; Wang, Chao - In: Journal of financial econometrics 20 (2022) 1, pp. 105-138

Persistent link: https://www.econbiz.de/10012878188

Exponentially smoothing the skewed laplace distribution for value-at-risk forecasting

Gerlach, Richard; Lu, Zu-di; Huang, Hai - In: Journal of forecasting 32 (2013) 6, pp. 534-550

Persistent link: https://www.econbiz.de/10009789677

Variational Bayes for assessment of dynamic quantile forecasts

Gerlach, Richard; Abeywardana, Sachin - In: International journal of forecasting 32 (2016) 4, pp. 1385-1402

Persistent link: https://www.econbiz.de/10011622172

Time-varying parameters realized GARCH models for tracking attenuation bias in volatility dynamics

Gerlach, Richard; Naimoli, Antonio; Storti, Giuseppe - In: Quantitative finance 20 (2020) 11, pp. 1849-1878

Persistent link: https://www.econbiz.de/10012295647

Bayesian model selection for heteroskedastic models

Chen, Cathy W.S.; Gerlach, Richard; So, Mike K.P. - In: Bayesian econometrics, (pp. 567-594). 2008

It is well known that volatility asymmetry exists in financial markets. This paper reviews and investigates recently developed techniques for Bayesian estimation and model selection applied to a large group of modern asymmetric heteroskedastic models. These include the GJR-GARCH, threshold...

Persistent link: https://www.econbiz.de/10015383628

Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators

Naimoli, Antonio; Gerlach, Richard; Storti, Giuseppe - In: Economic modelling 107 (2022), pp. 1-19

Persistent link: https://www.econbiz.de/10013367470