The estimation of potential losses that could arise from adverse changes in market conditions is a key element of risk management. For financial institutions and corporate treasuries across the world, Value at Risk (VaR) is rapidly emerging as the dominant methodology for estimating precisely how much money is at risk each day in the financial markets. However, the communication and application of VaR is a field in which the signal to noise ratio is not high. there is neither a widespread intuitive understanding of VaR in the market, nor an appreciation of the practicalities of its implementation and limitations. Mastering Value at Risk will close that knowledge gap, introducing this potentially powerful methodology to those most in need of its benefits, and helping all those who encounter VaR to use it wisely.
Table of contents
1. An Outline of Value at Risk.
Introduction. What is Value at Risk? Volatility and how to exploit it profitably. Correlation—its role in risk reduction. Conclusion.
2. Value at Risk as a Tool in Supervisory Regulation.
Regulation: what it is and why it's necessary. Capital adequacy and the Basle Accord—what it is trying to achieve. Should regulators recognize diversification? Conclusion.
3. Portfolio Risk Measurement.
A profile of VaR methods. How matrices are used to calculate VaR. Comparison of the variance covariance approach with other methods, or which VaR method is best? Variance covariance with a three-asset portfolio. Constructing the weighting matrix. Mapping. Appendix 3.1. Appendix 3.2.
4. Fixed Income Products.
The range of fixed income products. Interest rate conventions. VaR on forward rate agreements. How swaps work. Conclusion.
5. Measuring the Risk of Complex Derivative Products.
Interest rate sensitivity. Calculating duration and convexity. The unique risk characteristics of convexity. The role of delta gamma in VaR measurement. Conclusion. Appendix 5.1.
6. The Greeks.
The risk sensitivities of options. Reducing the risk of option portfolios. Exploiting volatility smiles profitably. Conclusion.
Which option strategies work? Volatility trading: straddles, strangles, butterflies, and ratio spreads. Time spread strategies. Conclusion.
8. Monte Carlo Simulation.
Monte Carlo simulation and its applications. Generating the share prices. Applying Monte Carlo simulation to VaR. Conclusion.
9. Applying VaR Principles to credit control.
Measuring credit risk more accurately. Reducing credit risk. Using credit derivatives to reduce credit risk. Conclusion.
10. Estimating Volatility for Profitable Trading and Risk Reduction.
Volatility and its measures. Exponentially weighted moving average (EWMA) vs time series. GARCH: changing variance and correlation between current and past events. Conclusion.
11. Real-life Application of Models.
Should we rely on VaR? Over-the-counter options. Criticisms of VaR methods. Conclusion. Appendix 11.1. Appendix 11.2.
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Published by FT Press (October 28th 1998) - Copyright © 1998