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 Surface Air Temperature: A Comparison of Predictions Based on Local and Global Trend Estimates
The actuarial pricing of weather swaps often depends on predicting the temperature several months in advance. Such predictions can be made by modelling the trends in historical temperature indices and extrapolating them forward in time. Linear trends are one of the simplest types of trend model one can use. They have two parameters: the mean level, and the trend rate. The mean level is probably best estimated from local data, but it is not obvious how best to estimate the trend rate: in this study we compare the performance of predictions based on local and global trend rate estimates.
Teaching learning disability to undergraduate medical students
The education of doctors shapes their professional identity: who they are and how they practise. Where does the issue of learning disability fit in? What is it and of what factors should doctors in training be aware?

The training of medical students has been defined by the General Medical Council (