Simulation in Computational Finance and Economics: Tools and Emerging Applications

Simulation in Computational Finance and Economics: Tools and Emerging Applications

Biliana Alexandrova-Kabadjova (Banco de Mexico, Mexico), Serafin Martinez-Jaramillo (Banco de Mexico, Mexico), Alma Lilia Garcia-Almanza (Banco de Mexico, Mexico) and Edward Tsang (University of Essex, UK)
Release Date: August, 2012|Copyright: © 2013 |Pages: 378
ISBN13: 9781466620117|ISBN10: 1466620110|EISBN13: 9781466620124|DOI: 10.4018/978-1-4666-2011-7


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.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Agent Based Simulations in Economics and Finance
  • Computational risk analysis and modeling
  • Financial Markets
  • Game Theory
  • High frequency trading
  • Simulations payment systems and methods
  • Systemic risk models

Reviews and Testimonials

Computer scientists at the Bank of Mexico hope to promote computational simulation techniques as fundamental tools for modeling financial and economic problems by motivating young researchers to develop their own simulation-based methods to study various problems. The opening section of the collection analyzes the complex economic dynamics of payment systems and introduces agent-based modeling as a powerful simulation method for understanding participants' behavior in payment systems. Banking risk management is addressed in the second part, and examples of agent-based models in action are presented in the final section. Topics of the 18 papers include liquidity management in large value payment systems, measuring and charging for banks' systemic interconnectedness, a multi-agent financial network model of U.S. collateralized debt obligations, optimal patent design, and predicting volatile consumer markets.

– Book News Inc. Portland, OR

Table of Contents and List of Contributors

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Editorial Advisory Board
Table of Contents
Manfred Gilli
Thomas Lux
Alma Lilia Garcia-Almanza, Biliana Alexandrova-Kabadjova, Serafin Martinez-Jaramillo, Edward Tsang
Chapter 1
Biliana Alexandrova-Kabadjova, Sara G. Castellanos Pascacio, Alma L. García-Almanza
The authors investigate the payment adoption rate under consumers’ and merchants’ awareness of network externalities, given two levels of... Sample PDF
The Adoption Process of Payment Cards: An Agent-Based Approach
Chapter 2
Martin Diehl
Simulations are among the analytical tools in payment systems analysis. They can be used to overcome epistemological weaknesses of models and... Sample PDF
The Use of Simulations as an Analytical Tool for Payment Systems
Chapter 3
Ronald Heijmans, Richard Heuver
Simulations in large value payment systems have become a common tool for stress scenario analyses, often using historical data. The reason for... Sample PDF
Preparing Simulations in Large Value Payment Systems using Historical Data
Chapter 4
Tatu Laine, Kasperi Korpinen, Matti Hellqvist
Payment systems constitute a critical aspect of modern economic infrastructure; yet understanding the payment system mechanisms remains elusive in... Sample PDF
Simulation Approaches to Risk, Efficiency, and Liquidity Usage in Payment Systems
Chapter 5
Luca Arciero, Cristina Picillo
With the advent of Large Value Interbank Fund Transfer Systems operating on an RTGS basis, the bank liquidity management problem has become a... Sample PDF
Liquidity Management in the Large Value Payment Systems: Need for an Agent-Based Model’s Complex Approach
Chapter 6
Marco Galbiati, Kimmo Soramäki
Interbank payment systems form the backbone of the financial architecture. Banks need to hold costly funds at the central bank to process interbank... Sample PDF
Liquidity Saving Mechanisms and Bank Behavior in Payment Systems
Chapter 7
Joanna McLafferty, Edward Denbee
This study uses a simulation methodology and real payment data to quantify the liquidity efficiency that could be obtained in CHAPS, the UK’s... Sample PDF
Liquidity Saving in CHAPS: A Simulation Study
Chapter 8
Biliana Alexandrova-Kabadjova, Francisco Solís-Robleda
The present chapter calculates the liquidity usage of the Mexican Real Time Settlement Payment System, SPEI, during a one month period. In... Sample PDF
Managing Intraday Liquidity: The Mexican Experience
Chapter 9
Marco A. Espinosa-Vega, Juan Solé
Generalized calls for more and higher quality capital for systemic institutions were the first natural reaction to the recent global financial... Sample PDF
Measuring and Charging for Banks’ Systemic Interconnectedness
Chapter 10
Serafin Martinez-Jaramillo, Calixto Lopez-Castañon, Fabrizio Lopez-Gallo
By using the proposed framework, it is also possible to perform stress testing in a coherent way, including second round effects like contagion... Sample PDF
Systemic Risk, Stress Testing, and Financial Contagion: Their Interaction and Measurement
Chapter 11
Céline Gauthier, Toni Gravelle, Xuezhi Liu, Moez Souissi
One way of internalising the externalities each individual bank imposes on the rest of the financial system is to impose capital surcharges (KS) on... Sample PDF
What Matters in Determining Capital Surcharge for Systemically Important Financial Institutions?
Chapter 12
Sheri M. Markose, Bewaji Oluwasegun, Simone Giansante
A database driven multi-agent model has been developed with automated access to US bank level FDIC Call Reports that yield data on balance sheet and... Sample PDF
Multi-Agent Financial Network (MAFN) Model of US Collateralized Debt Obligations (CDO): Regulatory Capital Arbitrage, Negative CDS Carry Trade, and Systemic Risk Analysis
Chapter 13
Wing Lon Ng
This chapter uses the abundance of high frequency data to estimate scaling law models and then apply appropriately scaled measures to provide... Sample PDF
Improving Long-Term Financial Risk Forecasts using High-Frequency Data and Scaling Laws
Chapter 14
Anthony Brabazon
Patents provide a patentee with a degree of monopoly power over a region of product space. The “breadth” and “duration” of patents are policy... Sample PDF
Optimal Patent Design: An Agent-Based Modeling Approach
Chapter 15
Monira Aloud, Edward Tsang, Richard Olsen
In this chapter, the authors use an Agent-Based Modeling (ABM) approach to model trading behavior in the Foreign Exchange (FX) market. They... Sample PDF
Modeling the FX Market Traders’ Behavior: An Agent-Based Approach
Chapter 16
Abhijit Sengupta, Stephen E. Glavin
A behavioral model incorporating utility-based rational choice enhanced with psychological drivers is presented to study a consumer goods market... Sample PDF
Predicting Volatile Consumer Markets using Multi-Agent Methods: Theory and Validation
Chapter 17
Shu-Heng Chen, Umberto Gostoli
In this chapter, the authors study the self-coordination problem as demonstrated by the well-known El Farol problem (Arthur, 1994), which has become... Sample PDF
Agent-Based Modeling of the El Farol Bar Problem
Chapter 18
Raúl O. Fernández, J. Eduardo Vera-Valdés
This chapter shows a way to, using simulation analysis, assess the performance of some of the most popular unit root and change in persistence... Sample PDF
Simulation Analysis as a Way to Assess the Performance of Important Unit Root and Change in Persistence Tests
About the Contributors

Author(s)/Editor(s) Biography

Biliana Alexandrova-Kabadjova obtained her Ph.D. and Master degree in Computational Finance from the Centre for Computational Finance and Economic Agents and the Department of Computer Science in the University of Essex, UK (2007, 2003). She works in the Mexican Central Bank as a payment analyst. Nowadays she is permanent member of the Mexican System of Researchers and she is a Visiting Fellow for the University of Essex. Her main contribution has been built the most advanced model (in terms of complexity and realism) of the payment card market. She has developed a framework under which one can learn regulatory strategies and individual agent can learn business strategies. She has published several refereed journal papers, book chapters and conference papers. She currently is co-editing a book and her main research interests are in retail payments, large value payment systems and in agent-based computational economics.
Serafin Martinez-Jaramillo is a senior financial researcher at the financial stability general directorate of Banco de México. He currently works on Financial Stability, Systemic Risk and Financial Networks at Banco de México but he also works on bankruptcy prediction using evolutionary computation techniques. He previously developed an agent based-financial market to study the link between agent behavior and the stylized facts in the financial market prices. Serafin has published several book chapters, encyclopedia entries and papers in high impact international journals. Serafin holds an MSc in Computer Science and a PhD in Computational Finance from the University of Essex where he is currently a visiting fellow. He belongs to the Mexican National Researchers System from 2009.
Alma Lilia Garcia-Almanza obtained her Ph.D. and Master degree in Computer Science from the University of Essex, UK (2008, 2004). She works in the Mexican Central Bank as a System Analyst. Nowadays she is Member of the Mexican Researchers System and she has an Award of Title as a Visiting Fellow for the University of Essex. Her research has been focused on financial forecasting; she has created different methods based on Evolutionary Algorithms to deal with rare cases in extremely imbalance datasets by means of the extraction of patterns. She has published her research in numerous articles in international scientific journals and chapters in books.
Edward Tsang has a first degree in Business Administration (Major in Finance) and a PhD in Computer Science. He has broad interest in applied artificial intelligence, in particularly computational finance, heuristic search, constraint satisfaction and scheduling. He is currently a Professor in the Department of Computing and Electronic Systems at the University of Essex where he leads the Computational Finance Group and Constraint Satisfaction and Optimization Group. He is the Director of the Centre for Computational Finance and Economic Agents (CCFEA), an interdisciplinary centre which he co-founded in 2002. He chaired the Technical Committee for Computational Finance under the IEEE Computational Intelligence Society in 2004-2005.