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Distributionally robust chance constraint with unimodality-skewness information and conic reformulation

Shang, Chao; Wang, Chao; You, Keyou; Huang, Dexian - In: Operations research letters 50 (2022) 2, pp. 176-183

Persistent link: https://www.econbiz.de/10013192686

Bayesian realized-GARCH models for financial tail risk forecasting incorporating the two-sided Weibull distribution

Wang, Chao; Chen, Qian; Gerlach, Richard - In: Quantitative finance 19 (2019) 6, pp. 1017-1042

Persistent link: https://www.econbiz.de/10012194739

Tail Risk Forecasting Using Bayesian Realized Egarch Models

Tendenan, Vica; Gerlach, Richard H.; Wang, Chao - 2022

This paper develops a Bayesian framework for the realized exponential generalized autoregressive conditional heteroskedasticity (realized EGARCH) model and adopts a standardized Student-t and a standardized skewed Student-t distributions for the return equation. The Bayesian estimators show more...

Persistent link: https://www.econbiz.de/10014239179

A Bayesian realized threshold measurement GARCH framework for financial tail risk forecasting

Wang, Chao; Gerlach, Richard - In: Journal of forecasting 43 (2024) 1, pp. 40-57

Persistent link: https://www.econbiz.de/10014443184

Modeling uncertainty in financial tail risk : a forecast combination and weighted quantile approach

Storti, Giuseppe; Wang, Chao - In: Journal of forecasting 42 (2023) 7, pp. 1648-1663

Persistent link: https://www.econbiz.de/10014432743