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Simulation in Computational Finance and Economics

Book Description

Simulation has become a tool difficult to substitute in many scientific areas like manufacturing, medicine, telecommunications, games, etc. Finance is one of such areas where simulation is a commonly used tool; for example, we can find Monte Carlo simulation in many financial applications like market risk analysis, portfolio optimization, credit risk related applications, etc. Simulation in Computational Finance and Economics: Tools and Emerging Applications presents a thorough collection of works, covering several rich and highly productive areas of research including Risk Management, Agent-Based Simulation, and Payment Methods and Systems, topics that have found new motivations after the strong recession experienced in the last few years. Despite the fact that simulation is widely accepted as a prominent tool, dealing with a simulation-based project requires specific management abilities of the researchers. Economic researchers will find an excellent reference to introduce them to the computational simulation models. The works presented in this book can be used as an inspiration for economic researchers interested in creating their own computational models in their respective fields.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
  5. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  6. Foreword
  7. Foreword
  8. Preface
    1. MOTIVATION
    2. SECTION ONE: PAYMENT SYSTEMS AND METHODS
    3. SECTION TWO: RISK MANAGEMENT
    4. SECTION THREE: AGENT-BASED SIMULATIONS IN ECONOMICS AND FINANCE
  9. Section 1: Payment Systems and Methods
    1. Chapter 1: The Adoption Process of Payment Cards
      1. ABSTRACT
      2. INTRODUCTION
      3. 1. ECONOMIC LITERATURE ON PAYMENT CARD SYSTEMS
      4. 2. AGENT-BASED MODELING: THE ALTERNATIVE APPROACH
      5. 3. THE ELEMENTS OF THE INTRANETWORK COMPETITION MODEL
      6. 4. DECISION-MAKING OF MARKET PARTICIPANTS
      7. 5. EXPERIMENTAL SETTING
      8. 6. RESULTS
      9. 7. CONCLUSION
      10. APPENDIX
    2. Chapter 2: The Use of Simulations as an Analytical Tool for Payment Systems
      1. ABSTRACT
      2. 1. BASIC FEATURES OF PAYMENT SYSTEMS
      3. 2. EPISTEMOLOGICAL ASSESSMENT OF SIMULATIONS AS ANALYTICAL TOOL
      4. 3. SIMULATIONS FOR THE FUNCTIONAL DEVELOPMENT OF PAYMENT SYSTEMS
      5. 4. SIMULATIONS OF RISKS IN PAYMENT SYSTEMS (SIMULATIONS FROM THE OVERSIGHT PERSPECTIVE)
      6. 5. EXAMPLES FOR SIMULATION TOOLS AND DIRECTIONS FOR FUTURE SIMULATIONS
    3. Chapter 3: Preparing Simulations in Large Value Payment Systems using Historical Data
      1. ABSTRACT
      2. INTRODUCTION
      3. SIMULATION LITERATURE
      4. PREPARING THE SIMULATION
      5. SETTING UP THE SIMULATION
      6. SOLUTIONS AND RECOMMENDATIONS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    4. Chapter 4: Simulation Approaches to Risk, Efficiency, and Liquidity Usage in Payment Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. SIMULATION IN PAYMENT SYSTEMS
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
    5. Chapter 5: Liquidity Management in the Large Value Payment Systems
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. A GLANCE AT LARGE VALUE PAYMENT SYSTEM LITERATURE
      4. 3. SIMULATING PAYMENT SYSTEMS BY AGENT BASED MODELING
      5. 4. AGENT BASED MODELING IN MARKETS AND PAYMENT SYSTEMS: WHICH WAY FORWARD?
      6. 5. CONCLUSION
    6. Chapter 6: Liquidity Saving Mechanisms and Bank Behavior in Payment Systems
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. SIMULATION MODEL
      5. RESULTS
      6. CONCLUSION
    7. Chapter 7: Liquidity Saving in CHAPS
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND AND LITERATURE REVIEW
      4. OVERVIEW OF METHODOLOGY
      5. MAIN RESULTS
      6. ROBUSTNESS CHECKS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    8. Chapter 8: Managing Intraday Liquidity
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LITERATURE REVIEW
      4. 3. MOTIVATION OF THE STUDY AND NOTATION
      5. 4. INTRADAY LIQUIDITY MANAGEMENT FROM THE PERSPECTIVE OF THE PARTICIPANTS
      6. 5. INTRADAY LIQUIDITY MANAGEMENT FROM THE PERSPECTIVE OF THE SYSTEM AS A WHOLE
      7. 6. CONCLUSION
    9. Chapter 12: Multi-Agent Financial Network (MAFN) Model of US Collateralized Debt Obligations (CDO)
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE REGULATORY AND MARKET CLIMATE (2005-2007)
      4. 3. SIMULATION MODEL FOR REGULATORY CAPITAL REQUIREMENTS WITH CDS CREDIT RISK MITIGANT
      5. 4. DATA USED FOR SIMULATION
      6. 5. AGENT-BASED SIMULATION RESULTS
      7. 6. CONCLUSION
      8. APPENDIX
    10. Chapter 13: Improving Long-Term Financial Risk Forecasts using High-Frequency Data and Scaling Laws
      1. ABSTRACT
      2. INTRODUCTION
      3. HIGH-FREQUENCY DATA AND PRICE COASTLINES
      4. METHOD
      5. FUTURE RESEARCH DIRECTIONS
      6. CONCLUSION
  10. Section 2: Risk Management
    1. Chapter 9: Measuring and Charging for Banks’ Systemic Interconnectedness
      1. ABSTRACT
      2. INTRODUCTION AND LITERATURE REVIEW
      3. MEASURING SYSTEMIC INTERCONNECTEDNESS
      4. CAPITAL SURCHARGES BASED ON SYSTEMIC INTERCONNECTEDNESS
      5. REFINEMENTS AND OTHER CONSIDERATIONS
      6. POLICY REFLECTIONS
    2. Chapter 10: Systemic Risk, Stress Testing, and Financial Contagion
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. RELATED LITERATURE
      4. 3. SIMULATION OF JOINT LOSSES FOR THE BANKING SYSTEM
      5. 4. RESULTS
      6. 5. CONCLUSION AND FURTHER WORK
      7. APPENDIX A: GENERATION OF CONSISTENT SCENARIOS
    3. Chapter 11: What Matters in Determining Capital Surcharge for Systemically Important Financial Institutions?
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. LITERATURE REVIEW
      4. 3. MEASUREMENT OF SYSTEMIC RISK AND SYSTEMIC IMPORTANCE
      5. 4. RESULTS
      6. 5. CONCLUSION AND FUTURE WORK
  11. Section 3: Agent-Based and Other Simulation Approaches
    1. Chapter 14: Optimal Patent Design
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. EXPERIMENTAL DESIGN
      5. 4. RESULTS
      6. 5. CONCLUSION
    2. Chapter 15: Modeling the FX Market Traders’ Behavior
      1. ABSTRACT
      2. 1 INTRODUCTION
      3. 2 BACKGROUND
      4. 3 DESIGN ROUTES WITH REGARD TO ABM
      5. 4. HIGH-FREQUENCY DATA
      6. 5. DATA DESCRIPTION
      7. 6. STYLIZED FACTS OF TRADERS’ BEHAVIOUR
      8. 7. MODEL OF FX MARKET TRADING ACTIVITY
      9. 8. ORIGIN OF THE TRADERS COLLECTIVE BEHAVIOUR STYLIZED FACTS
      10. 9. SOLUTIONS AND RECOMMENDATIONS
      11. 10. FUTURE RESEARCH DIRECTIONS
      12. 11. CONCLUSION
    3. Chapter 16: Predicting Volatile Consumer Markets using Multi-Agent Methods
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. MODEL
      5. VALIDATION METHODOLOGY
      6. DATA
      7. SIMULATION SETUP
      8. RESULTS
      9. CONCLUSION
      10. APPENDIX A: FIGURES
      11. APPENDIX B: TABLES
    4. Chapter 17: Agent-Based Modeling of the El Farol Bar Problem
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. PREVIOUS LITERATURE
      4. 3. THE MODEL
      5. 4. SIMULATIONS’ RESULTS
      6. 5. CONCLUSION
    5. Chapter 18: Simulation Analysis as a Way to Assess the Performance of Important Unit Root and Change in Persistence Tests
      1. ABSTRACT
      2. INTRODUCTION
      3. SPURIOUS REGRESSION
      4. UNIT ROOT AND CHANGE IN PERSISTENCE TESTS
      5. DATA GENERATING PROCESSES ANALYZED
      6. SIMULATION PROCEDURE
      7. SIMULATION RESULTS
      8. TESTING EMPIRICAL ECONOMICS TIME SERIES
      9. CONCLUSION
  12. Compilation of References
  13. About the Contributors