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Table of Contents
Intro; Preface; Introduction; Part I: Risk Methodologies and Applications; Part II: Statistical Modeling and Risk Issues in Several Areas; Contents; Part I Risk Methodologies and Applications; Assessment of Maximum A Posteriori Image Estimation Algorithms for Reduced Acquisition Time Medical Positron Emission Tomography Data; 1 Introduction; 2 Statistical Modelling for PET Data; 3 Maximum Likelihood and Maximum a Posteriori Estimation Using an EM Algorithm; 4 Data Description and Assessment Criteria; 5 Experimental Results; 6 Discussion; References; Multifractal Analysis on Cancer Risk.
1 Introduction2 Indication for Shape Analysis Approach for Wilms Tumors; 2.1 Differentiation Between Different tumor Groups; 2.2 4D-Shape Analysis; 2.3 Mixed Distribution Estimation; 2.3.1 4D Shape Analysis; 2.3.2 Checking of Consistency; 2.3.3 Estimation to Differentiate tumors; 3 Conclusion; References; Traditional Versus Alternative Risk Measures in Hedge Fund Investment Efficiency; 1 Introduction; 2 Literature Overview; 3 Problems of Hedge Funds Efficiency Measurement; 4 Basic Hedge Funds Statistics; 5 Maximum Drawdown Measures and Their Definitions.
6 Research Results of the Hedge Fund Risk Return Profile7 Conclusions; Appendix; References; Estimating the Extremal Coefficient: A Simulation Comparison of Methods; 1 Introduction; 2 Examples and Estimators; 3 Simulation Study; 4 Application to Real Data; Appendix; References; On a Business Confidence Index and Its Data Analytics:A Chilean Case; 1 Introduction; 2 Business Intelligence; 3 Methodology of the Chilean Business Confidence Index; 3.1 Target Population and Sample Design; 3.2 Data, Interview and Re-interview; 3.3 Customer Survey; 3.4 Building the CBCI; 4 Case Study I: CBCI on 2016.
5 Case Study II: Regression Modeling of the CBCI6 Conclusions and Future Research; References; On the Application of Sample Coefficient of Variation for Managing Loan Portfolio Risks; 1 Introduction; 2 Properties of Sample Coefficient of Variation; 2.1 Bounds for cv; 2.2 Efficiency of cv; 3 Application of cv for Measuring Concentration Risk in Loan Portfolio; 3.1 Capital Adequacy and Concentration Risk in the Loan Portfolios; 4 An Example; 5 Conclusion; Appendix; References; Acceptance-Sampling Plans for Reducing the Risk Associated with Chemical Compounds; 1 Introduction and Motivation.
2 Modeling Chromatography Measurements with an Inflated Pareto Distribution2.1 A Brief Description of the Problem and the Data Sets; 2.2 Inflated Pareto Model and ML Estimation; 2.3 Inflated Pareto Models Fitted to the Historical Data Sets; 3 Acceptance Sampling Plans for Inflated Pareto Data; 3.1 Some Preliminaries; 3.2 Design of Variables AS Plans; 3.3 Performance of the Previous Sampling Plans; 3.4 Algorithm for the Implementation of Plan I, for Inflated Pareto Data; 4 Conclusions; References; Risk of Return Levels for Spatial Extreme Events; 1 Introduction.
1 Introduction2 Indication for Shape Analysis Approach for Wilms Tumors; 2.1 Differentiation Between Different tumor Groups; 2.2 4D-Shape Analysis; 2.3 Mixed Distribution Estimation; 2.3.1 4D Shape Analysis; 2.3.2 Checking of Consistency; 2.3.3 Estimation to Differentiate tumors; 3 Conclusion; References; Traditional Versus Alternative Risk Measures in Hedge Fund Investment Efficiency; 1 Introduction; 2 Literature Overview; 3 Problems of Hedge Funds Efficiency Measurement; 4 Basic Hedge Funds Statistics; 5 Maximum Drawdown Measures and Their Definitions.
6 Research Results of the Hedge Fund Risk Return Profile7 Conclusions; Appendix; References; Estimating the Extremal Coefficient: A Simulation Comparison of Methods; 1 Introduction; 2 Examples and Estimators; 3 Simulation Study; 4 Application to Real Data; Appendix; References; On a Business Confidence Index and Its Data Analytics:A Chilean Case; 1 Introduction; 2 Business Intelligence; 3 Methodology of the Chilean Business Confidence Index; 3.1 Target Population and Sample Design; 3.2 Data, Interview and Re-interview; 3.3 Customer Survey; 3.4 Building the CBCI; 4 Case Study I: CBCI on 2016.
5 Case Study II: Regression Modeling of the CBCI6 Conclusions and Future Research; References; On the Application of Sample Coefficient of Variation for Managing Loan Portfolio Risks; 1 Introduction; 2 Properties of Sample Coefficient of Variation; 2.1 Bounds for cv; 2.2 Efficiency of cv; 3 Application of cv for Measuring Concentration Risk in Loan Portfolio; 3.1 Capital Adequacy and Concentration Risk in the Loan Portfolios; 4 An Example; 5 Conclusion; Appendix; References; Acceptance-Sampling Plans for Reducing the Risk Associated with Chemical Compounds; 1 Introduction and Motivation.
2 Modeling Chromatography Measurements with an Inflated Pareto Distribution2.1 A Brief Description of the Problem and the Data Sets; 2.2 Inflated Pareto Model and ML Estimation; 2.3 Inflated Pareto Models Fitted to the Historical Data Sets; 3 Acceptance Sampling Plans for Inflated Pareto Data; 3.1 Some Preliminaries; 3.2 Design of Variables AS Plans; 3.3 Performance of the Previous Sampling Plans; 3.4 Algorithm for the Implementation of Plan I, for Inflated Pareto Data; 4 Conclusions; References; Risk of Return Levels for Spatial Extreme Events; 1 Introduction.