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Forecasting using random subspace methods
Boot, Tom; Nibbering, Didier - 2016
provide a theoretical justification of the use of random subspace methods and show their usefulness when forecasting monthly …
Persistent link: https://www.econbiz.de/10011531132
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Forecasting global equity market volatilities
Zhang, Yaojie; Ma, Feng; Liao, Yin - In: International journal of forecasting 36 (2020) 4, pp. 1454-1475
Persistent link: https://www.econbiz.de/10012546804
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Does high-frequency crude oil futures data contain useful information for predicting volatility in the US stock market? : new evidence
Wang, Jiqian; Huang, Yisu; Ma, Feng; Chevallier, Julien - In: Energy economics 91 (2020), pp. 1-13
Persistent link: https://www.econbiz.de/10012518664
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Oil price volatility predictability : new evidence from a scaled PCA approach
Guo, Yangli; He, Feng; Liang, Chao; Ma, Feng - In: Energy economics 105 (2022), pp. 1-9
Persistent link: https://www.econbiz.de/10013201946
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A near optimal test for structural breaks when forecasting under square error loss
Boot, Tom; Pick, Andreas - 2017
forecasting occur much less frequently than indicated by existing tests. …
Persistent link: https://www.econbiz.de/10011636475
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Climate policy uncertainty and world renewable energy index volatility forecasting
Liang, Chao; Umar, Muhammad; Ma, Feng; Toan Luu Duc Huynh - In: Technological forecasting & social change : an … 182 (2022), pp. 1-13
Persistent link: https://www.econbiz.de/10013449113