Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- Acknowledgements
- 1 Weather derivatives and the weather derivatives market
- 2 Data cleaning and trends
- 3 The valuation of single contracts using burn analysis
- 4 The valuation of single contracts using index modelling
- 5 Further topics in the valuation of single contracts
- 6 The valuation of single contracts using daily modelling
- 7 Modelling portfolios
- 8 Managing portfolios
- 9 An introduction to meteorological forecasts
- 10 The use of meteorological forecasts in pricing
- 11 Arbitrage pricing models
- 12 Risk management
- 13 Modelling non-temperature data
- A Trend models
- B Parameter estimation
- C Goodness of fit tests
- D Expected pay-offs for normally distributed indices
- E Pay-off variances for normally distributed indices
- F Greeks for normally distributed indices
- G Exact solutions for the kernel density
- H The beta for a normally distributed index
- I Simulation methods
- J Efficient methods for pricing against a portfolio
- References
- Index
7 - Modelling portfolios
Published online by Cambridge University Press: 22 September 2009
- Frontmatter
- Contents
- List of figures
- List of tables
- Acknowledgements
- 1 Weather derivatives and the weather derivatives market
- 2 Data cleaning and trends
- 3 The valuation of single contracts using burn analysis
- 4 The valuation of single contracts using index modelling
- 5 Further topics in the valuation of single contracts
- 6 The valuation of single contracts using daily modelling
- 7 Modelling portfolios
- 8 Managing portfolios
- 9 An introduction to meteorological forecasts
- 10 The use of meteorological forecasts in pricing
- 11 Arbitrage pricing models
- 12 Risk management
- 13 Modelling non-temperature data
- A Trend models
- B Parameter estimation
- C Goodness of fit tests
- D Expected pay-offs for normally distributed indices
- E Pay-off variances for normally distributed indices
- F Greeks for normally distributed indices
- G Exact solutions for the kernel density
- H The beta for a normally distributed index
- I Simulation methods
- J Efficient methods for pricing against a portfolio
- References
- Index
Summary
Up until now we have looked exclusively at individual weather contracts, and how to model and price them on a stand-alone basis. However, we saw in chapter 3 that, from a speculator's point of view, individual weather contracts are very risky investments. For swaps there is around a 50 per cent chance of losing money while for short options there is typically a 20 per cent to 40 per cent chance, depending on the location of the strike. The addition of risk loading can make these risks a little less severe, but these are still worse risks than even the lowest-rated junk bonds.
There are two ways that speculators can overcome this problem and use weather derivatives to have a favourable impact on their overall levels of risk and return. The first is to view the weather derivative business as part of a larger enterprise. Although the weather business on its own might have a large risk relative to return, it could be that the marginal contribution to the total risk and return of the whole business makes it a good investment. This is possible because of the lack of correlation between weather events and other forms of investment.
- Type
- Chapter
- Information
- Weather Derivative ValuationThe Meteorological, Statistical, Financial and Mathematical Foundations, pp. 148 - 168Publisher: Cambridge University PressPrint publication year: 2005