1.

Record Nr.

UNINA9910784744003321

Autore

Ehrentreich Norman

Titolo

Agent-Based Modeling [[electronic resource] ] : The Santa Fe Institute Artificial Stock Market Model Revisited / / by Norman Ehrentreich

Pubbl/distr/stampa

Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2008

ISBN

1-281-10808-1

9786611108083

3-540-73879-7

Edizione

[1st ed. 2008.]

Descrizione fisica

1 online resource (244 p.)

Collana

Lecture Notes in Economics and Mathematical Systems, , 2196-9957 ; ; 602

Disciplina

330.1

Soggetti

Macroeconomics

Econometrics

Artificial intelligence

Operations research

Economics - History

Macroeconomics and Monetary Economics

Quantitative Economics

Artificial Intelligence

Operations Research and Decision Theory

History of Economic Thought and Methodology

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. [195]-225) and index.

Nota di contenuto

Agent-Based Modeling in Economics -- The Rationale for Agent-Based Modeling -- The Concept of Minimal Rationality -- Learning in Economics -- Replicating the Stylized Facts of Financial Markets -- The Santa Fe Institute Artificial Stock Market Model Revisited -- The Original Santa Fe Institute Artificial Stock Market -- A Suggested Modification to the SFI-ASM -- An Analysis of Wealth Levels -- Selection, Genetic Drift, and Technical Trading -- Summary and Future Research.

Sommario/riassunto

This book reconciles the existence of technical trading with the



Efficient Market Hypothesis. By analyzing a well-known agent-based model, the Santa Fe Institute Artificial Stock Market (SFI-ASM), it finds that when selective forces are weak, financial evolution cannot guarantee that only the fittest trading rules will survive.Its main contribution lies in the application of standard results from population genetics which have widely been neglected in the agent-based community. This has led to various misinterpretations of previous simulation results. The book is able to finally establish the