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Investigating improvements in the accuracy of prediction intervals for combinations of forecasts : a simulation study
Taylor, James W.; Bunn, Derek W. - In: International journal of forecasting 15 (1999) 3, pp. 325-339
Persistent link: https://www.econbiz.de/10001428497
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A quantile regression neural network approach to estimating the conditional density of multiperiod returns
Taylor, James W. - In: Journal of forecasting 19 (2000) 4, pp. 299-311
Persistent link: https://www.econbiz.de/10001504631
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A quantile regression approach to estimating the distribution of multiperiod returns
Taylor, James W. - In: The journal of derivatives : the official publication … 7 (1999) 1, pp. 64-78
Persistent link: https://www.econbiz.de/10001432473
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Evaluating volatility and interval forecasts
Taylor, James W. - In: Journal of forecasting 18 (1999) 2, pp. 111-128
Persistent link: https://www.econbiz.de/10001368220
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Exponential smoothing with a damped multiplicative trend
Taylor, James W. - In: International journal of forecasting 19 (2003) 4, pp. 715-725
Persistent link: https://www.econbiz.de/10001818902
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Volatility forecasting with smooth transition exponential smoothing
Taylor, James W. - In: International journal of forecasting 20 (2004) 2, pp. 273-286
Persistent link: https://www.econbiz.de/10002033481
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Smooth transition exponential smoothing
Taylor, James W. - In: Journal of forecasting 23 (2004) 6, pp. 385-404
Persistent link: https://www.econbiz.de/10002233157
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Density forecasting of intraday call center arrivals using models based on exponential smoothing
Taylor, James W. - In: Management science : journal of the Institute for … 58 (2012) 3, pp. 534-549
Persistent link: https://www.econbiz.de/10009525268
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Exponentially weighted information criteria for selecting among forecasting models
Taylor, James W. - In: International journal of forecasting 24 (2008) 3, pp. 513-524
Persistent link: https://www.econbiz.de/10003764146
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An evaluation of methods for very short-term load forecasting using minute-by-minute British data
Taylor, James W. - In: International journal of forecasting 24 (2008) 4, pp. 645-658
Persistent link: https://www.econbiz.de/10003808342