New PDF release: An Introduction to Value-at-Risk

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By Moorad Choudhry

ISBN-10: 111831669X

ISBN-13: 9781118316696

ISBN-10: 1118316703

ISBN-13: 9781118316702

ISBN-10: 1118316711

ISBN-13: 9781118316719

ISBN-10: 111831672X

ISBN-13: 9781118316726

The value-at-risk dimension technique is a widely-used software in monetary marketplace probability administration. The 5th variation of Professor Moorad Choudhry’s benchmark reference textual content An creation to Value-at-Risk deals an available and reader-friendly examine the concept that of VaR and its assorted estimation equipment, and is aimed in particular at rookies to the marketplace or these unusual with sleek hazard administration practices. the writer capitalises on his adventure within the monetary markets to offer this concise but in-depth assurance of VaR, set within the context of threat administration as a whole.

Topics coated include:

  • Defining value-at-risk
  • Variance-covariance methodology
  • Portfolio VaR
  • Credit chance and credits VaR
  • Stressed VaR
  • Critique and VaR in the course of crisis

Topics are illustrated with Bloomberg monitors, labored examples and workouts. comparable concerns reminiscent of records, volatility and correlation also are brought as valuable historical past for college students and practitioners. this can be crucial studying for all those that require an advent to monetary industry hazard administration and possibility dimension techniques.

Foreword by means of Carol Alexander, Professor of Finance, college of Sussex.

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Additional info for An Introduction to Value-at-Risk

Example text

Once this vector of alternative values of the market factors is obtained, the current and alternative values for the portfolio, the changes in portfolio value and the VaR are calculated exactly as in the historical method. Variance–covariance, analytic or parametric method This is similar to the historical method in that historical values of market factors are collected in a database. The next steps are then to: (i) decompose the instruments in the portfolio into the cashequivalent positions in more basic instruments; (ii) specify the exact distributions for the market factors (or ‘returns’); and (iii) calculate the portfolio variance and VaR using standard statistical methods.

In practice, time horizons of 1 day to 1 year have been used. For instance, bank front-office traders are often interested in calculating the amount they might lose in a 1-day period. Regulators and participants in illiquid markets may want to estimate exposures to market risk over a longer period. In any case a time horizon must be specified by the decision-maker. 2. , a 95% degree of confidence in this estimate, or confidence interval) may be sufficient. For regulatory requirements a 99% confidence interval may be more appropriate.

Similarly, a foreign currency bond can be mapped into a set of zero-coupon bonds and a cash foreign exchange amount subject to movement in the spot foreign exchange (FX) rate. Specify distributions The analytic method makes assumptions about the distributions of market factors. For example, the most widely used analytic method, JPMorgan’s RiskMetrics, assumes that the underlying distributions are normal. With normal distributions all the historical information is summarised in the mean and standard deviation of the returns (market factors), so users do not need to keep all the historical data.

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An Introduction to Value-at-Risk by Moorad Choudhry


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