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Table of Contents
Intro; Preface; Contents; Part I Risk Management in Finance; 1 Financial Investment, Financial Risk and Risk Management; 1.1 Financial Markets and Financial Investment; 1.2 Main Risks in Financial Markets; 1.3 Risk Countermeasures: Hedging and Diversifying; 1.4 Risk Management by Diversification; 1.5 Outline of Part I; 2 Market Risk Measures in Financial Investments; 2.1 Market Risk and Its Measurement; 2.2 Variance: Fluctuation Is Taken as Risk; 2.2.1 Definition of Variance; 2.2.2 Estimation of Variance; 2.3 Value at Risk: A Likely Loss Is Taken as Risk; 2.3.1 Definition of Value at Risk
2.3.2 Estimation of VaR: Three Methods2.3.2.1 Variance-Covariance Method; 2.3.2.2 Historical Simulation Method; 2.3.2.3 Monte Carlo Simulation Method; 2.4 Conditional VaR: Expected Loss Behind VaR Is Taken as Risk; 2.4.1 Definition of Conditional VaR; 2.4.2 Estimation of CVaR; 2.5 Other Risk Measures: Failure Is Taken as Risk; 2.6 Summary; 3 Market Risk Control in Investment Decisions; 3.1 Portfolio Selection and Its Models; 3.2 MV Model and Its Variations; 3.2.1 The Base MV Model and Its Two Variations; 3.2.2 Solving Methods for MV Based Models
3.2.3 Two MV Based Models with Computational Advantages3.3 M-VaR Model and Its Solving Method; 3.3.1 Methods for Solving M-VaR Models; 3.3.1.1 Minimize VaR Approximately; 3.3.1.2 Minimize VaR Indirectly; 3.3.1.3 Minimize VaR Using Heuristics; 3.3.2 Solving M-VaR Model Using the Soft Optimization Approach; 3.3.2.1 The Ideas of the Soft Optimization Approach; 3.3.2.2 The Algorithm for Solving Model (3.20); 3.4 M-CVaR Model and Its Solving Method; 3.5 Other M-Risk Models and Solving Methods; 3.6 Summary; 4 Market Risk Measures for Flexible Investments; 4.1 Flexible Investments
4.2 Risk Measures for Investments with Uncertain Exit Time4.2.1 Period Value at Risk; 4.2.2 Risk Measures Based on Average Loss in Time Axis; 4.3 Estimation of PVaR with Scenario Simulation; 4.3.1 Monte Carlo Simulation Method for Estimating PVaR; 4.3.2 Historical Simulation Method for Estimating PVaR; 4.4 Estimation of Risk Measures Based on Average Loss; 4.4.1 Estimation of Risk Measures Under Complete Information About the Probabilities of Exit Time; 4.4.2 Estimation of Risk Measures Under Partial Information About the Probabilities of Exit Time; 4.5 Summary
5 Market Risk Control in Flexible Investment Decisions5.1 Evaluation of Investments with Flexible Investment Term; 5.2 Two Kinds of Model for Flexible Investment Decisions; 5.3 M-PVaR Model and Solving Methods; 5.3.1 Solving PVaR Minimization Model by Solving a Mixed Integer Linear Programming; 5.3.2 Solving PVaR Minimization Model Using the Soft Optimization Approach; 5.4 M-Risk Models and Solving Methods; 5.4.1 M-Risk Models with Complete Probability Information Regarding Exit Time; 5.4.2 M-Risk Models with Partial Probability Information Regarding Exit Time
2.3.2 Estimation of VaR: Three Methods2.3.2.1 Variance-Covariance Method; 2.3.2.2 Historical Simulation Method; 2.3.2.3 Monte Carlo Simulation Method; 2.4 Conditional VaR: Expected Loss Behind VaR Is Taken as Risk; 2.4.1 Definition of Conditional VaR; 2.4.2 Estimation of CVaR; 2.5 Other Risk Measures: Failure Is Taken as Risk; 2.6 Summary; 3 Market Risk Control in Investment Decisions; 3.1 Portfolio Selection and Its Models; 3.2 MV Model and Its Variations; 3.2.1 The Base MV Model and Its Two Variations; 3.2.2 Solving Methods for MV Based Models
3.2.3 Two MV Based Models with Computational Advantages3.3 M-VaR Model and Its Solving Method; 3.3.1 Methods for Solving M-VaR Models; 3.3.1.1 Minimize VaR Approximately; 3.3.1.2 Minimize VaR Indirectly; 3.3.1.3 Minimize VaR Using Heuristics; 3.3.2 Solving M-VaR Model Using the Soft Optimization Approach; 3.3.2.1 The Ideas of the Soft Optimization Approach; 3.3.2.2 The Algorithm for Solving Model (3.20); 3.4 M-CVaR Model and Its Solving Method; 3.5 Other M-Risk Models and Solving Methods; 3.6 Summary; 4 Market Risk Measures for Flexible Investments; 4.1 Flexible Investments
4.2 Risk Measures for Investments with Uncertain Exit Time4.2.1 Period Value at Risk; 4.2.2 Risk Measures Based on Average Loss in Time Axis; 4.3 Estimation of PVaR with Scenario Simulation; 4.3.1 Monte Carlo Simulation Method for Estimating PVaR; 4.3.2 Historical Simulation Method for Estimating PVaR; 4.4 Estimation of Risk Measures Based on Average Loss; 4.4.1 Estimation of Risk Measures Under Complete Information About the Probabilities of Exit Time; 4.4.2 Estimation of Risk Measures Under Partial Information About the Probabilities of Exit Time; 4.5 Summary
5 Market Risk Control in Flexible Investment Decisions5.1 Evaluation of Investments with Flexible Investment Term; 5.2 Two Kinds of Model for Flexible Investment Decisions; 5.3 M-PVaR Model and Solving Methods; 5.3.1 Solving PVaR Minimization Model by Solving a Mixed Integer Linear Programming; 5.3.2 Solving PVaR Minimization Model Using the Soft Optimization Approach; 5.4 M-Risk Models and Solving Methods; 5.4.1 M-Risk Models with Complete Probability Information Regarding Exit Time; 5.4.2 M-Risk Models with Partial Probability Information Regarding Exit Time