By Kevin Dowd
This booklet offers 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 industry chance Measurement comprises insurance of:
- Parametric and non-parametric probability estimation
- Numerical tools
- Liquidity dangers
- Risk Decomposition and Budgeting
- Stress trying out
- Model chance
Read or Download An Introduction to Market Risk Measurement (The Wiley Finance Series) PDF
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Extra resources for An Introduction to Market Risk Measurement (The Wiley Finance Series)
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.
8 These parameters imply that the VaR will be exceeded in only about one 10-day period in every four years. This should lead to a very low probability of failure, because the capital requirement itself is at least three times the VaR. Our estimated failure probability will then depend on what we assume about the P/L distribution. 25% per year, and less if we have a multiplier of greater than 3. This means that our institutions should be pretty safe — unless, like Barings or LTCM, they have a poor risk measurement model.
In risk management, we want our risk estimates to be unbiased or biased conservatively. If regulators use non-sub-additive risk measures to set capital requirements, a ﬁnancial ﬁrm might be tempted to break itself up to reduce its regulatory capital requirements, because the sum of the capital requirements of the smaller units would be less than the capital requirement of the ﬁrm as a whole. Non-sub-additive risk measures can also tempt agents trading on an organised exchange to break up their accounts, with separate accounts for separate risks, in order to reduce their margin requirements.