Universal portfolio algorithm: Difference between revisions
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The algorithm rebalances the portfolio at the beginning of each trading period. At the beginning of the first trading period it starts with a naive diversification. In the following trading periods the portfolio composition depends on the historical total return of all possible constant-rebalanced portfolios. |
The algorithm rebalances the portfolio at the beginning of each trading period. At the beginning of the first trading period it starts with a naive diversification. In the following trading periods the portfolio composition depends on the historical total return of all possible constant-rebalanced portfolios.<ref> |
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{{cite book |
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|last1=Dochow|first1=Robert |
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|title=Online Algorithms for the Portfolio Selection Problem |
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|date=2016 |
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|publisher=Springer Gabler |
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|url=https://www.springer.com/de/book/9783658135270| |
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}} |
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</ref> |
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==References== |
==References== |
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Revision as of 12:49, 16 September 2019
The universal portfolio algorithm is a portfolio selection algorithm from the field of machine learning and information theory. The algorithm learns adaptively from historical data and maximizes the log-optimal growth rate in the long run. It was introduced by the late Stanford University information theorist Thomas M. Cover.[1]
The algorithm rebalances the portfolio at the beginning of each trading period. At the beginning of the first trading period it starts with a naive diversification. In the following trading periods the portfolio composition depends on the historical total return of all possible constant-rebalanced portfolios.[2]
References
- ^ Cover, Thomas M. (1991). "Universal Portfolios". Mathematical Finance. 1 (1): 1–29. doi:10.1111/j.1467-9965.1991.tb00002.x.
- ^
Dochow, Robert (2016). Online Algorithms for the Portfolio Selection Problem. Springer Gabler.
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