Follow
Chao Wang
Title
Cited by
Cited by
Year
Forecasting risk via realized GARCH, incorporating the realized range
R Gerlach, C Wang
Quantitative Finance 16 (4), 501-511, 2016
472016
Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures
R Gerlach, C Wang
International Journal of Forecasting 36 (2), 489-506, 2020
322020
Bayesian realized-GARCH models for financial tail risk forecasting incorporating the two-sided Weibull distribution
C Wang, Q Chen, R Gerlach
Quantitative Finance 19 (6), 1017-1042, 2019
212019
Semi-parametric Bayesian tail risk forecasting incorporating realized measures of volatility
R Gerlach, D Walpole, C Wang
Quantitative Finance 17 (2), 199-215, 2017
142017
Bayesian semi-parametric realized conditional autoregressive expectile models for tail risk forecasting
R Gerlach, C Wang
Journal of Financial Econometrics 20 (1), 105-138, 2022
122022
Nonparametric Expected Shortfall Forecasting Incorporating Weighted Quantiles
G Storti, C Wang
International Journal of Forecasting. In press., 2021
102021
A bayesian long short-term memory model for value at risk and expected shortfall joint forecasting
Z Li, MN Tran, C Wang, R Gerlach, J Gao
arXiv preprint arXiv:2001.08374, 2020
72020
A semi-parametric realized joint value-at-risk and expected shortfall regression framework
C Wang, R Gerlach, Q Chen
arXiv preprint arXiv:1807.02422, 2018
72018
Bayesian semi-parametric realized-care models for tail risk forecasting incorporating realized measures
R Gerlach, C Wang
arXiv preprint arXiv:1612.08488, 2016
52016
A semi-parametric conditional autoregressive joint value-at-risk and expected shortfall modeling framework incorporating realized measures
C Wang, R Gerlach, Q Chen
Quantitative Finance 23 (2), 309-334, 2023
22023
Bayesian semi-parametric realized-care models for tail risk forecasting incorporating range and realized measures
R Gerlach, C Wang
Business Analytics., 2015
22015
Semi-parametric Realized Nonlinear Conditional Autoregressive Expectile and Expected Shortfall
C Wang, R Gerlach
arXiv preprint arXiv:1906.09961, 2019
12019
A Bayesian realized threshold measurement GARCH framework for financial tail risk forecasting
C Wang, R Gerlach
Journal of Forecasting 43 (1), 40-57, 2024
2024
DeepVol: A Deep Transfer Learning Approach for Universal Asset Volatility Modeling
C Liu, MN Tran, C Wang, R Gerlach, R Kohn
arXiv preprint arXiv:2309.02072, 2023
2023
Machine Learning and Deep Learning Forecasts of Electricity Imbalance Prices
S Deng, JN Inekwe, V Smirnov, A Wait, C Wang
Available at SSRN 4475210, 2023
2023
Realized recurrent conditional heteroskedasticity model for volatility modelling
C Liu, C Wang, MN Tran, R Kohn
arXiv preprint arXiv:2302.08002, 2023
2023
A multivariate semi-parametric portfolio risk optimization and forecasting framework
G Storti, C Wang
arXiv preprint arXiv:2207.04595, 2022
2022
Modelling uncertainty in financial tail risk: a forecast combination and weighted quantile approach
G Storti, C Wang
Journal of Forecasting. In press., 2021
2021
Tail risk forecasting using Bayesian realized EGARCH models
V Tendenan, R Gerlach, C Wang
arXiv preprint arXiv:2008.05147, 2020
2020
Forecasting risk via realized GARCH, incorporating the realized range
G Richard, W Chao
Business Analytics., 2014
2014
The system can't perform the operation now. Try again later.
Articles 1–20