Weather Derivative Pricing and the Year-Ahead Forecasting of Surface Air Temperature: An Empirical Evaluation of Damped Linear Detrending
The pricing of temperature derivatives is often based on statistical methods that predict the surface air temperature a year in advance. We perform an empirical comparison of three simple methods for such year-ahead temperature forecasting and draw clear conclusions about their relative merits. The three methods we consider are the standard flat-line and best-fit linear detrending methods and the recently introduced damped linear detrending method.
Weather Derivative Pricing and the Year Ahead Forecasting of Temperature Part 2: Theory
In part 1 of this article we showed results from the backtesting of different year ahead forecasting methods for US temperatures. We now attempt to explain some of the features of those results using a simple model and simulations of artificial data.
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