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Estimating Value at Risk and Expected Shortfall Using Expectiles
Expectile models are derived using asymmetric least squares. A simple formula has been presented that relates the expectile to the expectation of exceedances beyond the expectile. We use this as theExpand
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The role of risk in consumer behavior.
R AYMOND Bauer first formally proposed that consumer behavior be viewed as risk taking in 1960.1 Over a dozen years have passed since that proposal was made, and during that period a substantial bodyExpand
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A comparison of univariate methods for forecasting electricity demand up to a day ahead
This empirical paper compares the accuracy of six univariate methods for short-term electricity demand forecasting for lead times up to a day ahead. The very short lead times are of particularExpand
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Triple seasonal methods for short-term electricity demand forecasting
  • J. W. Taylor
  • Mathematics, Computer Science
  • Eur. J. Oper. Res.
  • 1 July 2010
TLDR
We extend the three double seasonal methods in order to accommodate the intrayear seasonal cycle, and also a univariate neural network approach. Expand
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Forecasting Value at Risk and Expected Shortfall Using a Semiparametric Approach Based on the Asymmetric Laplace Distribution
Value at Risk (VaR) forecasts can be produced from conditional autoregressive VaR models, estimated using quantile regression. Quantile modeling avoids a distributional assumption, and allows theExpand
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Strong biological controls on Sr/Ca ratios in aragonitic marine bivalve shells: Geochemistry
[1] It is well known that skeletal remains of carbonate secreting organisms can provide a wealth of information about past environments. Sr/Ca ratios have been successfully used as a temperatureExpand
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Angiotensinogen gene expression in adipose tissue: analysis of obese models and hormonal and nutritional control.
Synthesis of angiotensin II (ANG II) has recently been described in adipose cells and has been linked to regulation of adiposity. Angiotensinogen (AGT), the substrate from which ANG II is formed, wasExpand
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Using weather ensemble predictions in electricity demand forecasting
Weather forecasts are an important input to many electricity demand forecasting models. This study investigates the use of weather ensemble predictions in electricity demand forecasting for leadExpand
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Forecasting daily supermarket sales using exponentially weighted quantile regression
  • J. W. Taylor
  • Economics, Computer Science
  • Eur. J. Oper. Res.
  • 1 April 2007
TLDR
Inventory control systems typically require the frequent updating of forecasts for many different products. Expand
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