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An Application of Evolutionary Finance to Firms Listed in the Swiss Market Index Author info | Abstract | Publisher info | Download info | Related research | Statistics Thorsten Hens
Klaus Reiner Schenk-Hoppé
Martin Stalder
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This paper presents an application of evolutionary portfolio theory to stocks listed in the Swiss Market Index (SMI). We study numerically the long-run outcome of the competition of rebalancing rules for market shares in a stock market with actual dividends taken from firms listed in the SMI. Returns are endogenous because prices are determined by supply and demand stemming from the rebalancing rules. Our simulations show that in competition with rebalancing rules derived from Mean-Variance Optimization, Maximum Growth Theory and Behavioral Finance, the evolutionary portfolio rule discovered in Hens and Schenk-Hoppé (2001) will eventually hold total market wealth. According to this simple rule the portfolio weights should be proportional to the expected relative dividends of the assets.
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Paper provided by Institute for Empirical Research in Economics - IEW in its series IEW - Working Papers with number
iewwp128.
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Keywords: Evolutionary Finance ; Behavioral Finance ; CAPM ; Rebalancing Rules ; Growth Optimal Portfolio. ; Other versions of this item:
Find related papers by JEL classification: D52 - Microeconomics - - General Equilibrium and Disequilibrium - - - Incomplete Markets D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
Brock, W.A. & Hommes, C.H. & Wagener, F.O.O., 2002.
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