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On-line portfolio selection strategy with prediction in the presence of transaction costs

Author

Listed:
  • Sergio Albeverio
  • LanJun Lao
  • XueLei Zhao

Abstract

An on-line portfolio selection strategy with transaction costs is presented. It ensures investors to achieve at least the same exponential growth rate of wealth as the best stock for a long term. This equipped with a new prediction method based on “cross rates” for price relative sequences yields a profitable algorithm, which has been tested on real data from the London Stock Exchange. Copyright Springer-Verlag Berlin Heidelberg 2001

Suggested Citation

  • Sergio Albeverio & LanJun Lao & XueLei Zhao, 2001. "On-line portfolio selection strategy with prediction in the presence of transaction costs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 54(1), pages 133-161, October.
    • Handle: RePEc:spr:mathme:v:54:y:2001:i:1:p:133-161
    DOI: 10.1007/s001860100142
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    Citations

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    Cited by:

    1. Panpan Ren & Jiang-Lun Wu, 2017. "Foreign exchange market modelling and an on-line portfolio selection algorithm," Papers 1707.00203, arXiv.org.
    2. Jin’an He & Shicheng Yin & Fangping Peng, 2024. "Weak aggregating specialist algorithm for online portfolio selection," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2405-2434, June.
    3. Xingyu Yang & Jin’an He & Hong Lin & Yong Zhang, 2020. "Boosting Exponential Gradient Strategy for Online Portfolio Selection: An Aggregating Experts’ Advice Method," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 231-251, January.
    4. Yong Zhang & Xingyu Yang, 2017. "Online Portfolio Selection Strategy Based on Combining Experts’ Advice," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 141-159, June.

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