Tactical Asset Allocation mit genetischen Algorithmen
Journal
Schweizerische Zeitschrift für Volkswirtschaft und Statistik
ISSN
0303-9692
Type
journal article
Date Issued
2003
Author(s)
Abstract (De)
In this study of tactical asset allocation, we use a genetic algorithm to implement a market timing strategy. The algorithm makes a daily decision whether to invest in the market index or in a riskless asset. The market index is represented by the S&P500 Composite Index, the riskless asset by a 3-month T-Bill. The decision of the genetic algorithm is based on fundamental macroeconomic variables. The association of fundamental variables with a set of operators creates a space of possible strategies from which the genetic algorithm attempts to select the optimal solution. To test its performance, we apply the genetic algorithm to different time periods of in-sample and out-of-sample data using rolling return estimates. In total, 39 different timing strategies are tested over the time period of 1980-2000. On a risk-adjusted basis, we observe a moderate outperformance for the timing strategy suggested by the algorithm compared to a passive index strategy. The forecasting power of the algorithm is higher during times of high volatility and pronounced changes in the return series. Moreover, the algorithm is more successful in forecasting long-term return patterns than short-term fluctuations.
Language
German
HSG Classification
not classified
Refereed
Yes
Publisher
Helbing & Lichtenhahn
Publisher place
Basel
Volume
139
Number
1
Start page
1
End page
40
Pages
40
Subject(s)
Division(s)
Eprints ID
12589
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Name
PubsAmmann2003GenetischeAlgorithmenSZVS.pdf
Size
243.08 KB
Format
Adobe PDF
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