Get An introduction to market risk measurement PDF

By Kevin Dowd

ISBN-10: 0470847484

ISBN-13: 9780470847480

ISBN-10: 0470855207

ISBN-13: 9780470855201

This ebook presents an creation to worth in danger (VaR) and anticipated tail loss (ETL) estimation and is a student-oriented model of Measuring marketplace Risk (John Wiley & Sons 2002).

An advent to marketplace possibility Measurement contains assurance of:

  • Parametric and non-parametric possibility estimation

  • Simulation

  • Numerical equipment

  • Liquidity dangers

  • Risk Decomposition and Budgeting

  • Backtesting

  • Stress checking out

  • Model threat
Divided into components, half one discusses a number of the threat size options, while half offers a toolkit of the most instruments required to appreciate marketplace danger dimension. A CD is packaged with the booklet, containing a MATLAB folder of chance size capabilities, as well as a few examples in Excel/VBA.

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Extra info for An introduction to market risk measurement

Sample text

3 Criticisms of VaR Most risk practitioners embraced VaR with varying degrees of enthusiasm, and most of the debate over VaR dealt with the relative merits of different VaR systems — the pros and cons of RiskMetrics, of parametric approaches relative to historical simulation approaches, and so on. However, there were also those who warned that VaR had deeper problems and could be dangerous. A key issue was the validity or otherwise of the statistical and other assumptions underlying VaR, and both Nassim Taleb20 (1997a,b) and Richard Hoppe (1998, 1999) were very critical of the na¨ıve transfer of mathematical and statistical models from the physical sciences, where they were well suited, to social systems where they were often invalid.

If you give a pilot an altimeter that is sometimes defective he will crash the plane. Give him nothing and he will look out the window’ (Taleb (1997a, p. 37)). 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.

16–17)). If an investor working on his/her own behalf can easily end up with perverse positions, there is even more scope for mischief where decision-making is decentralised and traders or asset managers are working to VaR-constrained targets or VaR-defined remuneration packages. After all, traders or asset managers will only ‘spike’ their firm if they work to an incentive structure that encourages them to do so. If traders face a VaR-defined risk target, they will often have an incentive to sell out-of-the-money options to increase ‘normal’ profits and hence their bonus; the downside is that the institution takes a bigger hit once in a while, but it is difficult to design systems that force traders to care about these bigger hits: the fact that VaR does not take account of what happens in ‘bad’ states can distort incentives and encourage traders or managers to ‘game’ a VaR target (and/or a VaR-defined remuneration package), and promote their own interests at the expense of the interests of the institutions they are supposed to be serving.

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An introduction to market risk measurement by Kevin Dowd

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