By Norman Ehrentreich
From the reviews:
"The booklet lower than evaluate is a vital and cautious research of a few of the problems serious about the workings of the SFI inventory marketplace. … for my part, Ehrentreich’s booklet is a wonderful connection with either the training, and empirical literature in finance." (Krzysztof Piasecki, Zentralblatt MATH, Vol. 1141, 2008)
"Norman Ehrentreich used to be one of many bold few to tackle the version, and he has summarized his paintings and findings during this very good e-book. … it really is worthy primer for someone attracted to getting all started within the quarter of agent-based finance. … it truly is crucial interpreting for someone drawn to the dynamics of the SFI industry specifically, yet I additionally suggest it for others as an invaluable source on agent-based monetary industry layout as well." (Blake LeBaron, magazine of man-made Societies and Social Simulation, Vol. 12 (2), March, 2009)
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Extra info for Agent-Based Modeling: The Santa Fe Institute Artificial Stock Market Model Revisited
Adaptation could then be visualized as a process of “hill-climbing” through minor modiﬁcations towards “peaks” of high ﬁtness on this ﬁtness landscape . 21 18 19 20 21 Gray codes are named after Frank Gray, who developed them in 1953 for use in shaft encoders. More on the history and the use of Gray codes can be found in [173, 144, 343]. An overview of diﬀerent encoding and decoding functions for GAs is given in . More information on ﬁtness scaling and possible mappings of objective values into ﬁtness functions can be found in .
In the limit, only the most rational type of ﬁrm in the initial population survives. , if ﬁtness is independent of the frequency distribution in the population and not otherwise inﬂuenced by a changing environment. 2 should be rewritten as xi (t + 1) = xi (t) fi (x, t) f (x, t) , i = 1, . . , n. 3) In this case, multiple equilibria are possible, and the mean ﬁtness of the population may or may not increase . 11 Replicator equations are often used to model social learning in which agents learn from others by imitating other, more successful agents [377, 378].
Unfortunately, Rubinstein does not explicitly state whether he subsumes models with lesser degrees of rationality into the group of rational models or not. However, since he deﬁnes rationality as the adherence to the Savage axioms , it is implied that investors maximize expected utility using unbiased subjective probabilities. Rubinstein’s insistence on the maximization principle thus implies that he does not not need to know the underlying market equilibrium equations. They only need to have beliefs which turn out to be consistent with actual observations.
Agent-Based Modeling: The Santa Fe Institute Artificial Stock Market Model Revisited by Norman Ehrentreich