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ECONIS (ZBW)
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A novel nonlinear value-at-risk method for modeling risk of option portfolio with multivariate mixture of normal distributions
Chen, Rongda
;
Yu, Lean
- In:
Economic modelling
35
(
2013
),
pp. 796-804
Persistent link: https://www.econbiz.de/10010336666
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2
Market fragmentation, liquidity measures and improvement perspectives from China's emissions trading scheme pilots
Chang, Kai
;
Chen, Rongda
;
Chevallier, Julien
- In:
Energy economics
75
(
2018
),
pp. 249-260
Persistent link: https://www.econbiz.de/10011974318
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3
Forecasting volatility and correlation between oil and gold prices using a novel multivariate GAS model
Chen, Rongda
;
Xu, Jianjun
- In:
Energy economics
78
(
2019
),
pp. 379-391
Persistent link: https://www.econbiz.de/10012159962
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4
Realized volatility forecast of stock index under structural breaks
Yang, Ke
;
Chen, Langnan
;
Tian, Fengping
- In:
Journal of forecasting
34
(
2015
)
1
,
pp. 57-82
Persistent link: https://www.econbiz.de/10011305343
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5
Realized volatility forecast of agricultural futures using the HAR models with bagging and combination approaches
Yang, Ke
;
Tian, Fengping
;
Chen, Langnan
;
Li, Steven
- In:
International review of economics & finance : IREF
49
(
2017
),
pp. 276-291
Persistent link: https://www.econbiz.de/10011748442
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6
Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity
Tian, Fengping
;
Yang, Ke
;
Chen, Langnan
- In:
International journal of forecasting
33
(
2017
)
1
,
pp. 132-152
Persistent link: https://www.econbiz.de/10011754691
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7
Volatility forecasting : long memory, regime switching and heteroscedasticity
Ma, Feng
;
Lu, Xinjie
;
Yang, Ke
;
Zhang, Yaojie
- In:
Applied economics
51
(
2019
)
38
,
pp. 4151-4163
Persistent link: https://www.econbiz.de/10012196974
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8
Realized volatility forecasting of agricultural commodity futures using long memory and regime switching
Tian, Fengping
;
Yang, Ke
;
Chen, Langnan
- In:
Journal of forecasting
36
(
2017
)
4
,
pp. 421-430
Persistent link: https://www.econbiz.de/10011860462
Saved in:
9
Forecasting crude oil volatility using the deep learning-based hybrid models with common factors
Yang, Ke
;
Hu, Nan
;
Tian, Fengping
-
2024
Persistent link: https://www.econbiz.de/10015110666
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