universal portfolio algorithm

{{Short description|Portfolio selection algorithm}}

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.{{cite journal |title=Universal Portfolios |first=Thomas M.|last=Cover |journal=Mathematical Finance |volume=1 |issue=1 |pages=1–29 |year=1991 |doi=10.1111/j.1467-9965.1991.tb00002.x |s2cid=219967240}}

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.{{cite book |last1=Dochow |first1=Robert |title=Online Algorithms for the Portfolio Selection Problem |date=2016 |publisher=Springer Gabler |isbn=9783658135270 |url=https://www.springer.com/de/book/9783658135270 }}