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
J - Efficient methods for pricing against a portfolio
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
Efficient methods for modelling one extra contract
We now describe two numerical methods for the efficient modelling of one extra contract on a portfolio. For both these methods we make the following assumptions:
n is the original number of indices in the portfolio;
m is the number of years of historical data;
k is the number of simulations;
Xh is the original historical data in an n by m matrix;
Zh is the same data transformed to standard normal distributions;
we have simulated these n indices for k years using the rank correlation method;
Zs is the n by k matrix of the normally distributed simulations;
Xs are the final simulations with correct marginals;
xh is the 1 by m vector of the new historical data;
zh is the same when transformed to a standard normal distribution;
ph is the 1 by m vector of historical pay-offs for the portfolio;
qh is the same when transformed to a standard normal distribution using the empirical CDF;
ps is the 1 by k vector of simulated pay-offs for the portfolio;
qs is the same when transformed to a standard normal distribution using the empirical CDF.
- Type
- Chapter
- Information
- Weather Derivative ValuationThe Meteorological, Statistical, Financial and Mathematical Foundations, pp. 358 - 359Publisher: Cambridge University PressPrint publication year: 2005