{"product_id":"operational-risk-with-excel-and-vba-applied-statistical-methods-for-risk-management-website-hardback-9780471478874","title":"Operational Risk with Excel and VBA; Applied Statistical Methods for Risk Management, + Website (Hardback) 9780471478874","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eOperational Risk with Excel and VBA\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eApplied Statistical Methods for Risk Management, + Website\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eNigel Da Costa Lewis (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780471478874, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 11 May 2004\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e288 pages, Charts: 58 B\u0026amp;W, 0 Color; Tables: 58 B\u0026amp;W, 0 Color\u003cbr\u003e23.4 x 16 x 2.7 cm, 0.508 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cb\u003eA valuable reference for understanding operational risk\u003c\/b\u003e \u003cp\u003e\u003ci\u003eOperational Risk with Excel and VBA\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eNigel Da Costa Lewis\u003c\/b\u003e (Stamford, CT) is president and CEO of StatMetrics, a quantitative research boutique. He received his PhD from Cambridge University.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003ePreface.  \u003cp\u003eAcknowledgments.\u003c\/p\u003e \u003cp\u003eCHAPTER 1: Introduction to Operational Risk Management and Modeling.\u003c\/p\u003e \u003cp\u003eWhat is Operational Risk?\u003c\/p\u003e \u003cp\u003eThe Regulatory Environment.\u003c\/p\u003e \u003cp\u003eWhy a Statistical Approach to Operational Risk Management?\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 2: Random Variables, Risk indicators, and Probability.\u003c\/p\u003e \u003cp\u003eRandom Variables and Operational Risk Indicators.\u003c\/p\u003e \u003cp\u003eTypes of Random Variable.\u003c\/p\u003e \u003cp\u003eProbability.\u003c\/p\u003e \u003cp\u003eFrequency and Subjective Probability.\u003c\/p\u003e \u003cp\u003eProbability Functions.\u003c\/p\u003e \u003cp\u003eCase Studies.\u003c\/p\u003e \u003cp\u003eCase Study 2.1: Downtown Investment Bank.\u003c\/p\u003e \u003cp\u003eCase Study 2.2: Mr. Mondey’s OPVaR.\u003c\/p\u003e \u003cp\u003eCase Study 2.3: Risk in Software Development.\u003c\/p\u003e \u003cp\u003eUseful Excel Functions.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 3: Expectation, Covariance, Variance, and Correlation.\u003c\/p\u003e \u003cp\u003eExpected Value of a RandomVariable.\u003c\/p\u003e \u003cp\u003eVariance and Standard Deviation.\u003c\/p\u003e \u003cp\u003eCovariance and Correlation.\u003c\/p\u003e \u003cp\u003eSome Rules for Correlation, Variance, and Covariance.\u003c\/p\u003e \u003cp\u003eCase Studies.\u003c\/p\u003e \u003cp\u003eCase Study 3.1: Expected Time to Complete a Complex Transaction.\u003c\/p\u003e \u003cp\u003eCase Study 3.2: Operational Cost of System Down Time.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 4: Modeling Central Tendency and Variability of Operational Risk Indicators.\u003c\/p\u003e \u003cp\u003eEmpirical Measures of Central Tendency.\u003c\/p\u003e \u003cp\u003eMeasures of Variability.\u003c\/p\u003e \u003cp\u003eCase Studies.\u003c\/p\u003e \u003cp\u003eCase Study 4.1: Approximating Business Risk.\u003c\/p\u003e \u003cp\u003eExcel Functions.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 5: Measuring Skew and Fat Tails of Operational Risk Indicators.\u003c\/p\u003e \u003cp\u003eMeasuring Skew.\u003c\/p\u003e \u003cp\u003eMeasuring Fat Tails.\u003c\/p\u003e \u003cp\u003eReview of Excel and VBA Functions for Skew and Fat Tails.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 6: Statistical Testing of Operational Risk Parameters.\u003c\/p\u003e \u003cp\u003eObjective and Language of Statistical Hypothesis Testing.\u003c\/p\u003e \u003cp\u003eSteps Involved In Conducting a Hypothesis Test.\u003c\/p\u003e \u003cp\u003eConfidence Intervals.\u003c\/p\u003e \u003cp\u003eCase Study 6.1: Stephan’s Mistake.\u003c\/p\u003e \u003cp\u003eExcel Functions for Hypothesis Testing.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 7: Severity of Loss Probability Models.\u003c\/p\u003e \u003cp\u003eNormal Distribution.\u003c\/p\u003e \u003cp\u003eEstimation of Parameters.\u003c\/p\u003e \u003cp\u003eBeta Distribution.\u003c\/p\u003e \u003cp\u003eErlang Distribution.\u003c\/p\u003e \u003cp\u003eExponential Distribution.\u003c\/p\u003e \u003cp\u003eGamma Distribution.\u003c\/p\u003e \u003cp\u003eLognormal Distribution.\u003c\/p\u003e \u003cp\u003ePareto Distribution.\u003c\/p\u003e \u003cp\u003eWeibull Distribution.\u003c\/p\u003e \u003cp\u003eOther Probability Distributions.\u003c\/p\u003e \u003cp\u003eWhat Distribution Best Fits My Severity of Loss Data?\u003c\/p\u003e \u003cp\u003eCase Study 7.1: Modeling Severity of Loss Legal Liability Losses.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 8: Frequency of Loss Probability Models.\u003c\/p\u003e \u003cp\u003ePopular Frequency of Loss Probability Models.\u003c\/p\u003e \u003cp\u003eOther Frequency of Loss Distributions.\u003c\/p\u003e \u003cp\u003eChi-Squared Goodness of Fit Test.\u003c\/p\u003e \u003cp\u003eCase Study 8.1: Key Personnel Risk.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 9: Modeling Aggregate Loss Distributions.\u003c\/p\u003e \u003cp\u003eAggregating Severity of Loss and Frequency of Loss Distributions.\u003c\/p\u003e \u003cp\u003eCalculating OpVaR.\u003c\/p\u003e \u003cp\u003eCoherent Risk Measures.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 10: The Law of Significant Digits and Fraud Risk Identification.\u003c\/p\u003e \u003cp\u003eThe Law of Significant Digits.\u003c\/p\u003e \u003cp\u003eBenford’s Law in Finance.\u003c\/p\u003e \u003cp\u003eCase Study 10.1: Analysis of Trader’s Profit and Loss Using Benford’s Law.\u003c\/p\u003e \u003cp\u003eA Step Towards Better Statistical Methods of Fraud Detection.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 11: Correlation and Dependence.\u003c\/p\u003e \u003cp\u003eMeasuring Correlation.\u003c\/p\u003e \u003cp\u003eDependence.\u003c\/p\u003e \u003cp\u003eStochastic Dependence.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 12: Linear Regression in Operational Risk Management.\u003c\/p\u003e \u003cp\u003eThe Simple Linear Regression Model.\u003c\/p\u003e \u003cp\u003eMultiple Regression.\u003c\/p\u003e \u003cp\u003ePrediction.\u003c\/p\u003e \u003cp\u003ePolynomial and Other Types of Regression.\u003c\/p\u003e \u003cp\u003eMultivariate Multiple Regression.\u003c\/p\u003e \u003cp\u003eRegime-Switching Regression.\u003c\/p\u003e \u003cp\u003eThe Difference Between Correlation and Regression.\u003c\/p\u003e \u003cp\u003eA Strategy for Regression Model Building in Operational Risk Management.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 13: Logistic Regression in Operational Risk Management.\u003c\/p\u003e \u003cp\u003eBinary Logistic Regression.\u003c\/p\u003e \u003cp\u003eBivariate Logistic Regression.\u003c\/p\u003e \u003cp\u003eCase Study 13.1: Nostro Breaks and Volume in a Bivariate Logistic Regression.\u003c\/p\u003e \u003cp\u003eOther Approaches for Modeling Bivariate Binary Endpoints.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 14: Mixed Dependent Variable Modeling.\u003c\/p\u003e \u003cp\u003eA Model for Mixed Dependent Variables.\u003c\/p\u003e \u003cp\u003eWorking Assumption of Independence.\u003c\/p\u003e \u003cp\u003eUnderstanding the Benefits of Using a WAI.\u003c\/p\u003e \u003cp\u003eCase Study 14.1: Modeling Failure in Compliance.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 15: Validating Operational Risk Proxies Using Surrogate Endpoints.\u003c\/p\u003e \u003cp\u003eThe Need for Surrogate Endpoints in OR Modeling.\u003c\/p\u003e \u003cp\u003eThe Prentice Criterion.\u003c\/p\u003e \u003cp\u003eLimitations of the Prentice Criterion.\u003c\/p\u003e \u003cp\u003eThe Real Value Added of Using Surrogate Variables.\u003c\/p\u003e \u003cp\u003eValidation Via the Proportion Explained.\u003c\/p\u003e \u003cp\u003eLimitations of Surrogate Modelling in Operational Risk Management.\u003c\/p\u003e \u003cp\u003eCase Study 15.1: Legal Experience as a Surrogate Endpoint for Legal Costs for a Business Unit.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 16: Introduction to Extreme Value Theory.\u003c\/p\u003e \u003cp\u003eFisher-Tippet–Gnedenko Theorem.\u003c\/p\u003e \u003cp\u003eMethod of Block Maxima.\u003c\/p\u003e \u003cp\u003ePeaks over Threshold Modeling.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 17: Managing Operational Risk with Bayesian Belief Networks.\u003c\/p\u003e \u003cp\u003eWhat is a Bayesian Belief Network?\u003c\/p\u003e \u003cp\u003eCase Study 17.1: A BBN Model for Software Product Risk.\u003c\/p\u003e \u003cp\u003eCreating a BBN-Based Simulation.\u003c\/p\u003e \u003cp\u003eAssessing the Impact of Different Managerial Strategies.\u003c\/p\u003e \u003cp\u003ePerceived Benefits of Bayesian Belief Network Modeling.\u003c\/p\u003e \u003cp\u003eCommon Myths About BBNs—The Truth for Operational Risk Management.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReview Questions.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eCHAPTER 18: Epilogue.\u003c\/p\u003e \u003cp\u003eWinning the Operational Risk Argument.\u003c\/p\u003e \u003cp\u003eFinal Tips on Applied Operational Risk Modeling.\u003c\/p\u003e \u003cp\u003eFurther Reading.\u003c\/p\u003e \u003cp\u003eAppendix.\u003c\/p\u003e \u003cp\u003eStatistical Tables.\u003c\/p\u003e \u003cp\u003eCumulative Distribution Function of the Standard Normal Distribution.\u003c\/p\u003e \u003cp\u003eChi-Squared Distribution.\u003c\/p\u003e \u003cp\u003eStudent’s \u003ci\u003et\u003c\/i\u003e Distribution.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eF\u003c\/i\u003e Distribution.\u003c\/p\u003e \u003cp\u003eNotes.\u003c\/p\u003e \u003cp\u003eBibliography.\u003c\/p\u003e \u003cp\u003eAbout the CD-ROM.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Finance \u0026amp; accounting [\u003ca title=\"See our other books on Finance \u0026amp; accounting\" 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