Journal of East China Normal University(Natural Sc ›› 2019, Vol. 2019 ›› Issue (4): 72-82.doi: 10.3969/j.issn.1000-5641.2019.04.008

• Computer Science • Previous Articles     Next Articles

Second-order online portfolio selection strategy with transaction costs

QU Jing-jing1, YU Shun-chang1, HUANG Ding-jiang1,2   

  1. 1. School of Science, East China University of Science and Technology, Shanghai 200237, China;
    2. School of Data Science and Engineering, East China Normal University, Shanghai 200062, China
  • Received:2018-08-07 Online:2019-07-25 Published:2019-07-18

Abstract: Existing portfolio selection strategies based on the online Newton step (ONS) algorithm ignore the role of transaction costs, an indispensable factor in real markets. This paper proposes a new online portfolio selection strategy, the online Newton step transaction cost (ONSC) method, to address this issue. First, we constructed the optimal function by combining second order information of a portfolio with the transaction cost penalty term, and the portfolio was subsequently updated. Then, the sublinear regret bound O(log(T)) was achieved by theoretical analysis. Empirical research on the data sets of four real markets-namely, SP500, NYSE(O), NYSE(N) and TSE-showed that in comparison to semiconstant rebalanced portfolios (SCRP) and other strategies with transaction costs, ONSC achieves the highest accumulated wealth and the smallest turnover. Hence, the research demonstrates the efiectiveness of the algorithm.

Key words: portfolio selection, online Newton step, transaction costs

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