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Informationen zum Autor NIGEL DA COSTA LEWIS , PHD, is the President of the quantitative research boutique StatMetrics, offering cutting edge quantitative solutions to a sophisticated institutional client base. Dr. Lewis has many years' work experience as a quantitative analyst and statistician in London, on Wall Street, and in academia. His work in quantitative risk management dates back to the early 1990s, when he developed stress-testing methodologies for portfolios of derivative securities for Legal & General Investments. He is the author of a number of books on risk management and quantitative methods and a regular speaker at international conferences. His current research work specializes in the application of computational-intensive quantitative methods to problems in risk management. He received a PhD in statistics from the University of Cambridge, and master's degrees in statistics, finance, economics, and computer science, all from the University of London. Klappentext A valuable reference for understanding operational riskOperational Risk with Excel and VBA is a practical guide that only discusses statistical methods that have been shown to work in an operational risk management context. It brings together a wide variety of statistical methods and models that have proven their worth, and contains a concise treatment of the topic. This book provides readers with clear explanations, relevant information, and comprehensive examples of statistical methods for operational risk management in the real world.Nigel Da Costa Lewis (Stamford, CT) is president and CEO of StatMetrics, a quantitative research boutique. He received his PhD from Cambridge University. Zusammenfassung A valuable reference for understanding operational riskOperational Risk with Excel and VBA is a practical guide that only discusses statistical methods that have been shown to work in an operational risk management context. It brings together a wide variety of statistical methods and models that have proven their worth, and contains a concise treatment of the topic. This book provides readers with clear explanations, relevant information, and comprehensive examples of statistical methods for operational risk management in the real world.Nigel Da Costa Lewis (Stamford, CT) is president and CEO of StatMetrics, a quantitative research boutique. He received his PhD from Cambridge University. Inhaltsverzeichnis Preface. Acknowledgments. CHAPTER 1: Introduction to Operational Risk Management and Modeling. What is Operational Risk? The Regulatory Environment. Why a Statistical Approach to Operational Risk Management? Summary. Review Questions. Further Reading. CHAPTER 2: Random Variables, Risk indicators, and Probability. Random Variables and Operational Risk Indicators. Types of Random Variable. Probability. Frequency and Subjective Probability. Probability Functions. Case Studies. Case Study 2.1: Downtown Investment Bank. Case Study 2.2: Mr. Mondey's OPVaR. Case Study 2.3: Risk in Software Development. Useful Excel Functions. Summary. Review Questions. Further Reading. CHAPTER 3: Expectation, Covariance, Variance, and Correlation. Expected Value of a RandomVariable. Variance and Standard Deviation. Covariance and Correlation. Some Rules for Correlation, Variance, and Covariance. Case Studies. Case Study 3.1: Expected Time to Complete a Complex Transaction. Case Study 3.2: Operational Cost of System Down Time. Summary. Review Questions. Further Reading. CHAPTER 4: Modeling Central Tendency and Variability of Operational Risk Indicators. Empirical Measures of Central Tendency. Measures of Variability. Case Studies. Case Study 4.1: Approximating Busin...
