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Forecasting and Hedging in the Foreign Exchange Markets

  • Book
  • © 2009

Overview

Authors:
  1. Christian Ullrich
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Part of the book series: Lecture Notes in Economics and Mathematical Systems (LNE, volume 623)

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Table of contents (17 chapters)

  1. Front Matter

    Pages 1-14
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  2. Introduction

    1. Front Matter

      Pages 1-1
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    2. Motivation

      • Christian Ullrich
      Pages 3-6

    3. Analytical Outlook

      • Christian Ullrich
      Pages 7-12

  3. Foreign Exchange Market Predictability

    1. Front Matter

      Pages 14-14
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    2. Equilibrium Relationships

      • Christian Ullrich
      Pages 15-25

    3. Market Efficiency Concepts

      • Christian Ullrich
      Pages 27-28

    4. Views from Complexity Theory

      • Christian Ullrich
      Pages 29-37

    5. Conclusions

      • Christian Ullrich
      Pages 39-39

  4. Exchange Rate Forecasting with Support Vector Machines

    1. Front Matter

      Pages 42-42
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    2. Introduction

      • Christian Ullrich
      Pages 43-45

    3. Statistical Analysis of Daily Exchange Rate Data.

      • Christian Ullrich
      Pages 47-63

    4. Support Vector Classification

      • Christian Ullrich
      Pages 65-82

    5. Description of Empirical Study and Results

      • Christian Ullrich
      Pages 83-103

  5. Exchange Rate Hedging in a Simulation/Optimization Framework

    1. Front Matter

      Pages 106-106
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    2. Introduction

      • Christian Ullrich
      Pages 107-115

    3. Preferences over Probability Distributions

      • Christian Ullrich
      Pages 117-131

    4. Problem Statement and Computational Complexity

      • Christian Ullrich
      Pages 133-140

    5. Model Implementation

      • Christian Ullrich
      Pages 141-161

    6. Simulation/Optimization Experiments

      • Christian Ullrich
      Pages 163-179
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Keywords

About this book

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.

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