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Non-linear Risk Measurement
Company: University of London
Year Of Publication: 2003
Month Of Publication: April
Pages: 131
Download Count: 2162
View Count: 12186
Comment Num: 0
Language: EN
Who Can Read: Free
Date: 2-16-2004
Publisher: Administrator
Several tools exist to assist the modern risk manager in monitoring investments, ranging from institution-wide position reports, through market sensitivity analysis and credit exposure reports, to complex money-at-risk calculations and simulations. The risk manager must choose one or more methodologies to combine this data to provide meaningful measures of the risk. One particularly difficult area has been the risk that arises from positions in options, in circumstances when the risk manager does not want to compromise on speed, accuracy or cost of implementation. This will happen when the institution has significant option positions, requires a measure with credibility, and has limited resources for systems implementations. In this thesis, I look at the popular methodology available to risk managers, RiskMetrics, and assess the level of compromise that the risk manager must make when using the fast techniques within this methodology to measure non-linear risk from option portfolios. The thesis describes the common shortfalls in the RiskMetrics model when applied to a typical portfolio for a financial institution. The thesis goes on to examine the challenges of non-linear risk measurement in more detail. In particular, I examine the measurement of non-linear risk using the RiskMetrics Delta-Gamma-Johnson modelling method. Very few publications in the field of non-linear Value at Risk (VaR) have included a review of the Johnson methodology. I show that it can work effectively for non-linear risk in interest rate options, under some circumstances. I also show an example for which it understates the risk. Organisations may still at this time be adopting the methodology as a component of a RiskMetrics VaR implementation. The thesis presents a framework that risk managers can apply to their own portfolios, to assess the suitability of the Delta-Gamma-Johnson approach.
ODonnell, Jeremy Sign in to follow this author
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