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Download An Introduction to Value-at-Risk by Moorad Choudhry PDF

By Moorad Choudhry

The value-at-risk dimension method is a widely-used software in monetary marketplace threat administration. The fourth version of Professor Moorad Choudhry's benchmark reference textual content An creation to Value-at-Risk deals an obtainable and reader-friendly examine the idea that of VaR and its various estimation equipment, and is aimed in particular at newbies to the marketplace or these unexpected with glossy danger administration practices. the writer capitalises on his event within the monetary markets to give this concise but in-depth assurance of VaR, set within the context of chance administration as an entire.

Topics lined contain:

  • Defining value-at-risk
  • Variance-covariance technique
  • Monte Carlo simulation
  • Portfolio VaR
  • Credit hazard and credits VaR

issues are illustrated with Bloomberg monitors, labored examples, workouts and case reviews. similar concerns equivalent to records, volatility and correlation also are brought as valuable heritage for college students and practitioners. this is often crucial studying for all those that require an creation to monetary industry danger administration and value-at-risk.

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Extra resources for An Introduction to Value-at-Risk

Example text

Note that returns are returns of asset prices, rather than the prices themselves; they are calculated from the actual prices by taking the ratio of closing prices. The returns are then calculated as the logarithm of the price relatives. 1(i) D Two-asset portfolio VaR. i. 1(i). i. standard deviations =NORMSINV(H13) Value-at-Risk Value-at-Risk £ =H18*H16 =H20*H12 deviation of the returns are then calculated using standard statistical formulae. This would then give the standard deviation of daily price relatives, which is converted to an annual figure by multiplying it by the square root of the number of days in a year, usually taken to be 250.

3. Create a probability distribution of likely returns for the instrument or portfolio under consideration – several methods may be used. The easiest to understand is a distribution of recent historical returns for the asset or portfolio which often looks like the curve associated with the normal distribution. After determining a time horizon and confidence interval for the estimate, and then collating the history of market price changes in a probability distribution, we can apply the laws of statistics to estimate VaR.

1 we show the calculation of mean, variance and standard deviation as calculated from an Excel spreadsheet. The expectation is the mean of all the observations, while the variance is, as we noted earlier, the sum of squared deviations from the mean. The standard deviation is the square root of the variance. What happens when we have observations that can assume any value within a range, rather than the discrete values we have seen in our example? 1 Dates Calculation of standard deviation. 791 16 AN INTRODUCTION TO VALUE-AT-RISK of any measure between a range of specified values, we have a continuous distribution.

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