
By Kevin Dowd
ISBN-10: 0470847484
ISBN-13: 9780470847480
ISBN-10: 0470855207
ISBN-13: 9780470855201
This ebook offers an advent to price in danger (VaR) and anticipated tail loss (ETL) estimation and is a student-oriented model of Measuring industry Risk (John Wiley & Sons 2002).
An advent to marketplace possibility Measurement comprises assurance of:
- Parametric and non-parametric possibility estimation
- Simulation
- Numerical tools
- Liquidity hazards
- Risk Decomposition and Budgeting
- Backtesting
- Stress checking out
- Model danger
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Additional resources for An introduction to market risk measurement
Example text
645. 645. 645. 645. 645. 645. 645 can then be described as the value at risk (or VaR) of our portfolio at the 95% level of confidence, and we will have more to say about this presently. The assumption that P/L is normally distributed is attractive for three reasons. The first is that it often has some, albeit limited, plausibility in circumstances where we can appeal to the central limit theorem. 2 Normal quantiles and probabilities. 645). , the ‘normsinv’ function in Excel or the ‘norminv’ function in MATLAB).
8 An Introduction to Market Risk Measurement it was becoming increasingly difficult, but also increasingly important, to be able to aggregate their risks, taking account of how they interact with each other, and firms lacked the methodology to do so. The best known of these systems is the RiskMetrics system developed by JP Morgan. According to industry legend, this system is said to have originated when the chairman of JP Morgan, Dennis Weatherstone, asked his staff to give him a daily one-page report indicating risk and potential losses over the next 24 hours, across the bank’s entire trading portfolio.
These are serious criticisms, and they are not easy to counter. Another problem was pointed out by Ju and Pearson (1999): if VaR measures are used to control or remunerate risk taking, traders will have an incentive to seek out positions where risk is over- or underestimated and trade them. They will therefore take on more risk than suggested by VaR estimates — so our VaR estimates will be biased downwards — and their empirical evidence suggests that the magnitude of these underestimates can be very substantial.
An introduction to market risk measurement by Kevin Dowd
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