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Operational Risk with Excel and VBA

Applied Statistical Methods for Risk Management, + Website. 14:B&W 6 x 9 in or 229 x 152 mm Case Laminate on…
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A valuable reference for understanding operational risk Operational 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… weiterlesen
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Produktdetails

Titel: Operational Risk with Excel and VBA
Autor/en: Nigel Da Costa Lewis

ISBN: 0471478873
EAN: 9780471478874
Applied Statistical Methods for Risk Management, + Website.
14:B&W 6 x 9 in or 229 x 152 mm Case Laminate on White w/Gloss Lam.
Sprache: Englisch.
John Wiley & Sons

2. April 2004 - gebunden - 288 Seiten

Beschreibung

A valuable reference for understanding operational risk Operational 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.
CHAPTER 2: Random Variables, Risk indicators, and Probability.
CHAPTER 3: Expectation, Covariance, Variance, and Correlation.
CHAPTER 4: Modeling Central Tendency and Variability of Operational Risk Indicators.
CHAPTER 5: Measuring Skew and Fat Tails of Operational Risk Indicators.
CHAPTER 6: Statistical Testing of Operational Risk Parameters.
CHAPTER 7: Severity of Loss Probability Models.
CHAPTER 8: Frequency of Loss Probability Models.
CHAPTER 10: The Law of Significant Digits and Fraud Risk Identification.
CHAPTER 11: Correlation and Dependence.
CHAPTER 12: Linear Regression in Operational Risk Management.
CHAPTER 13: Logistic Regression in Operational Risk Management.
CHAPTER 14: Mixed Dependent Variable Modeling.
CHAPTER 15: Validating Operational Risk Proxies Using Surrogate Endpoints.
CHAPTER 16: Introduction to Extreme Value Theory.
CHAPTER 17: Managing Operational Risk with Bayesian Belief Networks.
CHAPTER 18: Epilogue.
Bibliography.
About the CD-ROM.
Index.

Portrait

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.
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