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Market Risk Modelling: Applied Statistical Methods for Practitioners - Hardcover

Lewis, Nigel Da Costa

 
9781904339076: Market Risk Modelling: Applied Statistical Methods for Practitioners

Synopsis

Provides the practitioner, consultant and academic with vital quantitative expertise in an authoritative and up-to-date treatment of the most crucial innovations in the application of statistical methods to market risk modelling.

Uniquely written from a practitioner's perspective, this title is sympathetic to the needs of the busy practitioner and is designed to provide rapid and succinct access to useful statistical methods in one handy volume. The use of practical examples and accessible panels will allow the market risk manager to quickly and easily implement, evaluate and extend a wide variety of statistical modelling tools and techniques for more accurate market risk assessment. This timely release illustrates the value to be gained from the statistical analysis of market risk data providing a valuable competitive edge in these times of increased regulation. Key topics such as extreme value theory, volatility modelling, principle components, confidence intervals and fitting probability distributions to real data are covered in sufficient detail so that these methods can be integrated into your own risk management systems.

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About the Author

Dr Nigel Da Costa Lewis has many years work experience as a quantitative analyst and statistician in the City of London, on Wall Street and in academia. His work in market risk management dates back to the early 1990s where he developed stress-testing methodologies for portfolios of derivative securities for Legal & General Investment Management Limited. He now specialises in the application of computational intensive quantitative methods to problems in finance. His experience includes the application of neural networks to trading, Bayesian Belief Networks models for risk management and the application of classical and Bayesian statistical methods to market and credit risk. Nigel has an award-winning PhD in statistics from the University of Cambridge, and four Master's degrees, all from the University of London: statistics, finance, economics and advanced computer science.

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