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13 - Modelling non-temperature data

Published online by Cambridge University Press:  22 September 2009

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Summary

In chapters 2 to 12 we have considered how to model and price weather derivatives that depend on temperature as the underlying variable. Such contracts are by far the most common, accounting for about 85 per cent of all contracts traded in 2002 according to the WRMA. However, a number of other weather variables are used too. These include precipitation, snow depth, snow fall, river flow and wind. Of these, the most commonly seen are precipitation and wind, and we focus on these two variables in this chapter. Contracts based on these variables can be priced using the same basic methods as used for temperature-based contracts (burn analysis, index modelling and daily modelling), and as with temperature one may wish to detrend the data before applying any of these methods. Burn analysis works in exactly the same way as for temperature; index modelling may involve using new index distributions to cope with the different distribution shapes that arise; daily modelling may involve new kinds of time series models.

The purpose of this chapter is not to discuss precipitation and wind modelling in the same kind of detail as we have for temperature. Rather, we provide a brief overview of some of the modelling techniques available. In each case we first discuss the most common index types and show some examples of their index distributions. We then look at models for higher-frequency variables.

Precipitation

Figure 13.1 shows the daily precipitation at Chicago O'Hare from 1958 to 2002.

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Chapter
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Weather Derivative Valuation
The Meteorological, Statistical, Financial and Mathematical Foundations
, pp. 282 - 291
Publisher: Cambridge University Press
Print publication year: 2005

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