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Forecasting value at risk and expected shortfall using a semiparametric approach based on the asymmetric laplace distribution
Taylor, James W. - In: Journal of business & economic statistics : JBES ; a … 37 (2019) 1, pp. 121-133
Persistent link: https://www.econbiz.de/10012176554
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Return-volatility relationship : insights from linear and non-linear quantile regression
Allen, David E.; Singh, Abhay Kumar; Powell, Robert; … - 2013
Persistent link: https://www.econbiz.de/10009724826
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An approximate long-memory range-based approach for value at risk estimation
Meng, Xiaochun; Taylor, James W. - In: International journal of forecasting 34 (2018) 3, pp. 377-388
Persistent link: https://www.econbiz.de/10012030985
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Forecasting wind power quantiles using conditional kernel estimation
Taylor, James W.; Jeon, Jooyoung - In: Renewable Energy 80 (2015) C, pp. 370-379
The efficient management of wind farms and electricity systems benefit greatly from accurate wind power quantile forecasts. For example, when a wind power producer offers power to the market for a future period, the optimal bid is a quantile of the wind power density. An approach based on...
Persistent link: https://www.econbiz.de/10011263801