By Moorad Choudhry
The value-at-risk size method is a widely-used software in monetary industry threat administration. The 5th 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 diversified estimation tools, and is aimed in particular at rookies to the marketplace or these surprising with smooth chance 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 probability administration as a whole.
Topics lined include:
- Defining value-at-risk
- Variance-covariance methodology
- Portfolio VaR
- Credit threat and credits VaR
- Stressed VaR
- Critique and VaR in the course of crisis
Topics are illustrated with Bloomberg displays, labored examples and routines. similar matters equivalent to records, volatility and correlation also are brought as helpful heritage for college kids and practitioners. this can be crucial interpreting for all those that require an advent to monetary industry probability administration and threat size techniques.
Foreword through Carol Alexander, Professor of Finance, collage of Sussex.
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Additional info for An Introduction to Value-at-Risk
Consider also the price of crude oil to movements in the price of natural gas: if there is a correlation, to what extent is the degree of correlation? VaR requires that the user determine correlations within markets as well as across markets. The mapping procedures used as part of the VaR process also have embedded correlation assumptions. For example, mapping individual stocks into the S&P 500 or ﬁxed interest securities into the swap curve translate into the assumption that individual ﬁnancial instruments move as the market overall.
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 the 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.
VaR measures the volatility of a company’s asset prices, and so the greater the volatility, the higher the probability of loss. Deﬁnition Essentially VaR is a measure of the volatility of a bank trading book. It is the characteristics of volatility that traders, risk managers and others wish to become acquainted with when assessing a bank’s risk exposure. The mathematics behind measuring and estimating volatility is slightly involved, and we do not go into it here. However, by making use of a volatility estimate, a trader or senior manager can gain some idea of the risk exposure of the trading book, using the VaR measure.
An Introduction to Value-at-Risk by Moorad Choudhry