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 size method is a widely-used instrument in monetary marketplace chance administration. The 5th version of Professor Moorad Choudhry’s benchmark reference textual content An advent to Value-at-Risk bargains an available and reader-friendly examine the concept that of VaR and its assorted estimation equipment, and is aimed particularly at beginners to the marketplace or these strange with sleek danger administration practices. the writer capitalises on his event 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 probability and credits VaR
  • Stressed VaR
  • Critique and VaR in the course of crisis

Topics are illustrated with Bloomberg monitors, labored examples and routines. similar concerns resembling data, volatility and correlation also are brought as valuable history for college kids and practitioners. this is often crucial studying for all those that require an creation to monetary marketplace danger administration and probability size techniques.

Foreword via Carol Alexander, Professor of Finance, college of Sussex.

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Extra info for An Introduction to Value-at-Risk

Sample text

Future volatility is the predicted or expected price fluctuation of a period of time until the option has expired. Evidently, this will be affected not only by the calculated implied volatility but also by the expectation of the share’s price trend. 3 Probabilities extracted from the normal distribution table. E F G H I J 8 No. 4 6 C 7 Observation 8 Mean return 9 Target return 10 Standard deviation of return 11 Number of standard deviations 12 Probability Normal distribution illustrated for portfolio return.

This explains the importance of the normal distribution in statistics. If we have large numbers of observations – for example, the change in stock prices, or closing prices in government bonds – it makes calculations straightforward if we assume that they are normally distributed. For both option pricing theory and VaR, it is assumed that the returns from holding an asset are normally distributed. It is often convenient to define the return in logarithmic form as:   Pt ln PtÀ1 where Pt ¼ Price today; PtÀ1 ¼ Previous price.

Although historical volatility can show trends over a greater period of time – for example, 4 years – it can also make distinctly significant and highly variable changes. Therefore, there can be no certainty that a past trend is in any way indicative of a share’s future performance. Implied volatility is a necessary tool to obtain the predicted value of an option which has been obtained from the present value of that option by entering different levels of volatility into an option pricing model, until the current market price is reached.

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An Introduction to Value-at-Risk by Moorad Choudhry


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