Agent-Based Modeling The Santa Fe Institute Artificial Stock Market
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Norman Ehrentreich
Agent-Based Modeling The Santa Fe Institute Artificial Stock Market Model Revisited
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Dr. Norman Ehrentreich RiverSource Investments, LLC 262 Ameriprise Financial Center Minneapolis, MN 55474 USA [email protected]
ISBN 978-3-540-73878-7
e-ISBN 978-3-540-73879-4
DOI 10.1007/978-3-540-73878-7 Lecture Notes in Economics and Mathematical Systems ISSN 0075-8442 Library of Congress Control Number: 2007937522 c 2008 Springer-Verlag Berlin Heidelberg This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Production: LE-TEX Jelonek, Schmidt & Vöckler GbR, Leipzig Cover-design: WMX Design GmbH, Heidelberg Printed on acid-free paper 987654321 springer.com
Meinen Eltern gewidmet.
Foreword
When the original Santa Fe Institute (SFI) artificial stock market was created in the early 1990’s, the creators realized that it contained many interesting new technologies that had never been tested in economic modeling. The authors kept to a very specific finance message in their papers, but the hope was that others would pick up where these papers left off and put these important issues to the test. Tackling the complexities involved in implementation has held many people back from this, and many parts of the SFI market remain unexplored. Ehrentreich’s book is an important and careful study of some of the issues involved in the workings of the SFI stock market. As Ehrentreich’s book points out in its historical perspective, the SFI market was intended as a computational test bed for a market with boundedly rational learning agents replacing the standard setup of perfectly rational equilibrium modeling common in economics and finance. These agents exhibit reasonable, purposeful behavior, but they are not able to completely process every aspect of the world around them. This can be viewed much more as a function of the complexity of the world, rather than the computational limitations of agents. In a financial world out of equilibrium, optimal behavior would require knowledge of strategies being used by all the other agents, an information and computational task which seems well out of reach of any trader. The SFI market’s main conclusion was that markets where agents were learning might not converge to traditional sim
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