Forecasting and Hedging in the Foreign Exchange Markets

Transcription

1 Christian Ullrich Forecasting and Hedging in the Foreign Exchange Markets 4u Springer

2 Contents Part I Introduction 1 Motivation 3 2 Analytical Outlook Foreign Exchange Market Predictability Exchange Rate Forecasting with Support Vector Machines Exchange Rate Hedging in a Simulation/Optimization Framework 10 Part II Foreign Exchange Market Predictability 3 Equilibrium Relationships Purchasing Power Parity Theorem Absolute PPP Relative PPP Empirical Evidence Explanations for Deviations from PPP Interest Rate Parity (IRP) Theorem Covered Interest Rate Parity (CIP) Uncovered Covered Interest Rate Parity (UIP) Empirical Evidence Explanations for Deviations from IRP 24 4 Market Efficiency Concepts Informational Efficiency Speculative Efficiency 28 5 Views from Complexity Theory Introduction Calculating Fixed Point Market Equilibrium Computational Complexity of Centralized Equilibrium 32 XIII

3 xiv Contents Computational Complexity of Decentralized Equilibrium Adaptive/Inductive Learning of Rational Expectations Equilibria Computational Difficulties with Efficiency Information Interpretation Computational Complexity of Arbitrage 37 6 Conclusions 39 Part III Exchange Rate Forecasting with Support Vector Machines 7 Introduction 43 8 Statistical Analysis of Daily Exchange Rate Data Time Series Predictability Empirical Analysis Stationarity Normal Distribution Linearity Heteroskedasticity Nonlinearity Results 63 9 Support Vector Classification Binary Classification Problem (BCP) On the Computational Complexity of the BCP Supervised Learning Structural Risk Minimization Support Vector Machines Learning in Feature Space Kernel Functions Optimal Separating Hyperplane Generalized Optimal Separating Hyperplane Generalization in High Dimensional Feature Space Description of Empirical Study and Results Explanatory Dataset Phase One: Input Data Selection Phase Two: Dimensionality Reduction SVM Model Sequential Minimization Optimization (SMO) Algorithm Kernel Selection Cross Validation Benchmark Models 95

4 Contents xv 10.7 Evaluation Procedure Statistical Evaluation Operational Evaluation Numerical Results and Discussion 99 Part IV Exchange Rate Hedging in a Simulation/Optimization Framework 11 Introduction Preferences over Probability Distributions Currency Hedging Instruments Forward Plain Vanilla Option Straddle Formal Relationship Between Firm and Capital Market Expectations Specification of Probability Distribution Function Expected Utility Maximization and Three-Moments Ranking Preference Structures over Lotteries Preference Structures over Utility Functions Expected Utility Maximization Increasing Wealth Preference Risk Aversion Preference Ruin Aversion Preference Specification of Utility Function Problem Statement and Computational Complexity Problem Statement Computational Complexity Considerations Complexity of Deterministic Combinatorial Optimization Complexity of Stochastic Combinatorial Optimization Objective Function Characteristics Model Implementation Simulation/Optimization Simulation Model Datasets Component 1: Equilibrium Component 2: Nonlinear Mean Reversion Component 3: Gaussian Random Walk Aggregation of Components Calibration of Parameters Optimization Model Solution Construction Algorithm Scatter Search and Path Relinking 154

5 xvi Contents 15 Simulation/Optimization Experiments Practical Motivation Model Backtesting Overview Data Inputs and Parameters Evaluation Procedure Results Ex Ante Performance Ex Post Performance 176 Part V Contributions of the Dissertation 16 Exchange Rate Forecasting with Support Vector Machines Exchange Rate Hedging in a Simulation/Optimization Framework Part VI References References 191