Forecasting and Hedging in the Foreign Exchange Markets (eBook)

Christian Ullrich (Autor)

eBook Download: PDF

2009 | 2009
XVIII, 207 Seiten
Springer Berlin (Verlag)
978-3-642-00495-7 (ISBN)

Infos

Historical and recent developments at international ?nancial markets show that it is easy to loose money, while it is dif?cult to predict future developments and op- mize decision-making towards maximizing returns and minimizing risk. One of the reasons of our inability to make reliable predictions and to make optimal decisions is the growing complexity of the global economy. This is especially true for the f- eign exchange market (FX market) which is considered as one of the largest and most liquid ?nancial markets. Its grade of ef?ciencyand its complexityis one of the starting points of this volume. From the high complexity of the FX market, Christian Ullrich deduces the - cessity to use tools from machine learning and arti?cial intelligence, e.g., support vector machines, and to combine such methods with sophisticated ?nancial mod- ing techniques. The suitability of this combination of ideas is demonstrated by an empirical study and by simulation. I am pleased to introduce this book to its - dience, hoping that it will provide the reader with interesting ideas to support the understanding of FX markets and to help to improve risk management in dif?cult times. Moreover, I hope that its publication will stimulate further research to contribute to the solution of the many open questions in this area.

Inhalt

Foreword 6
Preface 7
Acknowledgements 9
Contents 10
Acronyms 14
Part I Introduction 16
Chapter 1 Motivation 17
Chapter 2 Analytical Outlook 21
2.1 Foreign Exchange Market Predictability 21
2.2 Exchange Rate Forecasting with Support Vector Machines 22
2.3 Exchange Rate Hedging in a Simulation/Optimization Framework 24
Part II Foreign Exchange Market Predictability 27
Chapter 3 Equilibrium Relationships 28
3.1 Purchasing Power Parity Theorem 28
3.2 Interest Rate Parity (IRP) Theorem 34
Chapter 4 Market Efficiency Concepts 39
4.1 Informational Efficiency 39
4.2 Speculative Efficiency 40
Chapter 5 Views from Complexity Theory 41
5.1 Introduction 41
5.2 Calculating Fixed Point Market Equilibrium 44
5.3 Computational Difficulties with Efficiency 47
Chapter 6 Conclusions 50
Part III Exchange Rate Forecasting with Support Vector Machines 51
Chapter 7 Introduction 52
Chapter 8 Statistical Analysis of Daily Exchange Rate Data 55
8.1 Time Series Predictability 55
8.2 Empirical Analysis 55
Chapter 9 Support Vector Classification 72
9.1 Binary Classification Problem (BCP) 72
9.2 On the Computational Complexity of the BCP 72
9.3 Supervised Learning 74
9.4 Structural Risk Minimization 76
9.5 Support Vector Machines 78
Chapter 10 Description of Empirical Study and Results 90
10.1 Explanatory Dataset 90
10.2 SVM Model 96
10.3 Sequential Minimization Optimization (SMO) Algorithm 96
10.4 Kernel Selection 98
10.5 Cross Validation 101
10.6 Benchmark Models 102
10.7 Evaluation Procedure 104
10.8 Numerical Results and Discussion 106
Part IV Exchange Rate Hedging in a Simulation/Optimization Framework 111
Chapter 11 Introduction 112
Chapter 12 Preferences over Probability Distributions 121
12.1 Currency Hedging Instruments 121
12.2 Formal Relationship Between Firm and Capital Market Expectations 126
12.3 Specification of Probability Distribution Function 127
12.4 Expected Utility Maximization and Three-Moments Ranking 128
12.5 Specification of Utility Function 133
Chapter 13 Problem Statement and Computational Complexity 136
13.1 Problem Statement 136
13.2 Computational Complexity Considerations 138
Chapter 14 Model Implementation 144
14.1 Simulation/Optimization 144
14.2 Simulation Model 145
14.3 Optimization Model 155
Chapter 15 Simulation/Optimization Experiments 165
15.1 Practical Motivation 165
15.2 Model Backtesting 165
15.3 Results 175
Part V Contributions of the Dissertation 182
Chapter 16 Exchange Rate Forecasting with Support Vector Machines 183
Chapter 17 Exchange Rate Hedging in a Simulation/Optimization Framework 185
Part VI References 189
References 190

Produkt-Details

• Erscheint lt. Verlag: 30.5.2009
• Reihe/Serie: Lecture Notes in Economics and Mathematical Systems
• Reihe/Serie: Lecture Notes in Economics and Mathematical Systems
• Zusatzinfo: XVIII, 207 p. 43 illus.
• Verlagsort: Berlin
• Sprache: englisch
• Themenwelt: Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
• Themenwelt: Mathematik / Informatik ► Mathematik
• Themenwelt: Technik
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Finanzierung
• Themenwelt: Wirtschaft ► Betriebswirtschaft / Management ► Wirtschaftsinformatik
• Themenwelt: Wirtschaft ► Volkswirtschaftslehre
• Schlagworte: Analysis • Artificial Intelligence • classification • Complexity • Complexity theory • Computational Finance • Decision-Making • Distribution • Finance • financial modeling • Foreign Exchange Market Complexity • Hedging • machine learning • Modeling • Motivation • Optimization • Quantitative Finance • Simulation • Statistical Analysis
• ISBN-10: 3-642-00495-4 / 3642004954
• ISBN-13: 978-3-642-00495-7 / 9783642004957