Enterprise Risk Management. in Finance. Desheng Dash Wu Stockholm Business School, Stockholm University, Sweden RiskLab, University of Toronto, Canada

Transcription

1 Enterprise Risk Management in Finance Desheng Dash Wu Stockholm Business School, Stockholm University, Sweden RiskLab, University of Toronto, Canada and David L. Olson College of Business Administration, University of Nebraska, USA palgrave macmillan

2 Contents List offigures ListofTables Preface Acknowledgements x xii xv xvii 1 Enterprise Risk Management 1 Introduction 1 Definition 2 Accounting perspective 3 The COSO framework 3 Categories 4 Activities 4 Risk appetite 6 ERM process 7 Implementation issues 7 Risk management modeling 9 Book outline 9 2 Enron 11 Risk management 11 California electricity 12 Accounting impact 13 SOX 13 Conclusions 14 3 Financial Risk Management 15 Introduction 15 Investment collars 17 VaR 17 Copulas 20 Tranches 21 Conclusions 22 4 The Real Estate Crash of Introduction 23 Real estate in Mortgage system 26 V

3 vi Contents Northern Rock 26 AIG 29 Risk management 30 5 Financial Risk Forecast Using Machine Learning and Sentiment Analysis 32 Introduction 32 Information volume and volatility 32 Information sentiment and volatility 33 Volatility model and modified non-linear GARCH model 34 Daily volatility model 38 Using GARCH-based SVM to associate Information sentiment with asset price volatility 39 Sentiment analysis of financial news 39 Using GARCH-based SVM to associate Information sentiment and volatility 41 Empirical results and analysis 42 Trading volume volatility forecasting 43 Volatility forecasting with sentiment analysis 44 Conclusions 48 6 Online Stock Forum Sentiment Analysis 49 Introduction 49 Architectural design of GARCH-SVM based on sentiment index 49 Sentiment analysis 50 Data 51 Methodology comparison 53 Sentiment and stock price volatility 54 Conclusions 55 7 DEA Risk Scoring Model of Internet Stocks 57 Introduction 57 Different methods of Performance evaluation 57 Multivariate Statistical analysis 58 Data envelopment analysis 58 Analytic hierarchy process 59 Fuzzy set theory 59 Grey relation analysis 60 Balanced scorecard 60 Financial Statement analysis 60 Basics of data envelopment analysis 61 The proposed approach 63 Variable selection 64 Empirical study 66

4 Contents vii The DEA result 66 Conclusions 70 8 Bank Credit Scoring 72 Introduction 72 Risk modeling 72 Performance Validation in credit rating 74 Case study: credit scorecard Validation 75 Statistical results and discussion 77 Population distributions and stability 80 Conclusions 85 Appendix A8.1: Informal Definitions 86 9 Credit Scoring using Multiobjective Data Mining 87 Introduction 87 TOPSIS for data mining 87 Steps of the TOPSIS data mining method 88 Dataset 90 TOPSIS model over training data 91 Model comparisons 93 Simulation of model results 96 Conclusions Online Banking Efficiency and Risk Evaluation with Principal Component Analysis 99 Introduction 99 Data and variables 100 Results and analysis 101 PCA-DEA analysis 104 Risk factors 106 Conclusions Economic Perspective 108 The traditional economic view 108 The human factor 111 Reality 111 Risk mitigation 114 Risk tolerance 114 Recent events 114 Conclusions British Petroleum Deepwater Horizon 118 Introduction 118 Deepwater horizon 119 The Oil Pollution Act of

5 viii Contents Recovery factors in Macondo 120 Risk management factors 121 Conclusions Bank Efficiency Analysis 124 Introduction 124 Data envelopment analysis (DEA) 126 Neural networks 127 The energy we use 129 Bank branch efficiency analysis 129 Short-term efficiency prediction 133 Conclusions Catastrophe Bond and Risk Modeling 136 Introduction 136 Catastrophe risk Instruments 136 Loss model 138 Demonstration of computation 138 Parameter estimation 140 Error analysis 143 Conclusions Bilevel Programming Merger Analysis in Banking 145 Introduction 145 A conceptual banking chain with constrained resources 146 Mathematical model 148 Merger evaluation 150 A numerical example for incentive incompatibility 151 Case study: banking chain Illustration 152 Post merger 157 Managerial insights 160 Conclusions Sustainability and Risk in Globalization 163 Enterprise sustainability 163 Types of risk 165 Contexts of sustainable risk 166 Globalization 168 Supply chain risk management 170 Global business risks 171 Conclusions Risk from Natural Disasters 175 Introduction 175 Preparing for high-impact, low-probability events 176 Be prepared 177 Risks and emergencies 177

6 Contents ix Technical tools 178 Emergency management 179 Emergency management support systems 180 Conclusions Pricing of Carbon Emission Exchange in the EU ETS 183 Introduction 183 Literature review 184 Price movements 186 Model, data and sample 188 Analysis of EUA logreturns 189 Time series test 191 GARCH effect test 192 Method selection 193 Estimation and forecasting 194 Conclusions Volatility Forecasting of the Crude Oil Market 199 Introduction 199 Volatility models 200 Historical volatility 200 ARMA(R,M) 201 ARMAX(R,M, b) 201 ARCH(q) 201 GARCH(p,q) 202 EGARCH 202 GJR(p,q) 203 Regime-switching models 203 Data 204 Distribution analysis 204 Results 206 GARCH modeling 206 Markov regime-switching modeling 210 Conclusions Confucius Three-stage Learning of Risk Management 215 Introduction 215 Self-cultivation 216 Family regulation 217 State harmonization 218 Conclusions 219 Notes 221 References 238 Index 253