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Nonstationary Optimization Approach for Finding Universal Portfolios

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  • Gaivoronski, A
  • Stella, F

Abstract

The definition of universal portfolio was introduced in the nancial literature in order to describe the class of portfolios which are constructed directly from the available observations of the stocks behavior without any assumptions about their statistical properties. Cover has shown that one can construct such portfolio using only observations of the past stock prices which generates the same asymptotic wealth growth as the best constant rebalanced portfolio which is constructed with the full knowledge of the future stock market behavior. In this paper we construct universal portfolios using totally different set of ideas drawn from nonstationary stochastic optimization. Also our portfolios yield the same asymptotic growth of wealth as the best constant rebalanced portfolio constructed with the perfect knowledge of the future, but they are less demanding computationally. Besides theoretical study, we present computational evidence using data from New York Stock Exchange which shows, among other things, superior performance of portfolios which explicitly take into account possible nonstationary market behavior.

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File URL: http://mpra.ub.uni-muenchen.de/21913/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 21913.

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Date of creation: 2000
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Handle: RePEc:pra:mprapa:21913

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Related research

Keywords: universal portfolios; constant rebalanced portfolios; portfolio selection;

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References

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  1. John M. Mulvey & Hercules Vladimirou, 1992. "Stochastic Network Programming for Financial Planning Problems," Management Science, INFORMS, vol. 38(11), pages 1642-1664, November.
  2. Farshid Jamshidian, 1992. "Asymptotically Optimal Portfolios," Mathematical Finance, Wiley Blackwell, vol. 2(2), pages 131-150.
  3. Kjetil Høyland & Stein W. Wallace, 2001. "Generating Scenario Trees for Multistage Decision Problems," Management Science, INFORMS, vol. 47(2), pages 295-307, February.
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Cited by:
  1. Sjur Flåm, 2010. "Portfolio management without probabilities or statistics," Annals of Finance, Springer, vol. 6(3), pages 357-368, July.
  2. Stella, Fabio & Ventura, Alfonso, 2010. "Defensive online portfolio selection," MPRA Paper 33279, University Library of Munich, Germany.
  3. Bin Li & Steven C. H. Hoi, 2012. "Online Portfolio Selection: A Survey," Papers 1212.2129, arXiv.org, revised May 2013.
  4. Bin Li & Steven C. H. Hoi, 2012. "On-Line Portfolio Selection with Moving Average Reversion," Papers 1206.4626, arXiv.org.

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