ABSTRACT
We propose a feasible selection method of market window size for four state-of-the-art portfolio strategies. Market window size is a common parameter in the machine learning strategy for portfolio selection. However, in previous researches, the selection of market window size often lacks the guidance of scientific theories. In this paper, we analyze the sensitivity of market window size for four strategies on six benchmark data sets respectively. We study the distribution rule of the best market window sizes, which bring the peak total wealth, and then present the market window size selection method that is effective whether there is ample history data or not. What's more, to appraise the result of our method, we divide the benchmark data sets into two parts. We select the appropriate window size in the first part by our method, while the second part is used to test. By comparing with the wealth achieved in the second part using original method, we find that our selection method can effectively optimize the final results.
- Borodin, R. El-Yaniv, and V. Gogan, "Can we learn to beat the best stock", J. Artif. Intell. Res., vol. 21, no. 1, pp. 579--594, Jan. 2004. Google ScholarDigital Library
- B. Li, S. C. H. Hoi, and V. Gopalkrishnan, "Corn: Correlation-driven nonparametric learning approach for portfolio selection", ACM Trans. Intell. Syst. Technol., vol. 2, no. 3, Apr. 2011, Art. no. 21. Google ScholarDigital Library
- B. Li, S. C. H. Hoi, D. Sahoo, and Z.-Y. Liu, "Moving average reversion strategy for on-line portfolio selection", Artif. Intell., vol. 222, pp. 104--123, May. 2015. Google ScholarDigital Library
- D. Huang, J. Zhou, B. Li, S. C. H. Hoi, and S. Zhou, "Robust median reversion strategy for on-line portfolio selection" in Proc. 23rd Int. Joint Conf. Artif. Intell. (IJCAI), pp. 2006--2012, 2013. Google ScholarDigital Library
- J. Kelly Jr., "A new interpretation of information rate", Bell Syst. Tech. J., vol. 35, no. 4, pp. 917--926, Jul. 1956.Google ScholarCross Ref
- T. M. Cover, "Universal portfolios," Math. Finance, vol. 1, no. 1, pp. 1--29, 1991.Google ScholarCross Ref
- L. Györfi, G. Lugosi, and F. Udina, "Nonparametric kernel-based sequential investment strategies", Math. Finance, vol. 16, no. 2, pp. 337--357, Apr. 2006.Google ScholarCross Ref
- B. Li, P. Zhao, S.C.H. Hoi, and V. Gopalkrishnan, "Pamr: passive aggressive mean reversion strategy for portfolio selection", Mach. Learn, vol. 87, no. 2, pp. 221--258, May. 2012. Google ScholarDigital Library
- L. Gu, L. Zhang, and Y. Zhao, "An Euclidean Distance based on the Weighted Self-information Related Data Transformation for Nominal Data Clustering", CIKM '17. ACM, pp. 2083--2086, Nov. 2017. Google ScholarDigital Library
- J. L. Rodgers, and W. A. Nicewander, "Thirteen Ways to Look at the Correlation Coefficient", Amer. Statist., vol. 42, no. 1, pp. 59--66, Feb. 1988.Google ScholarCross Ref
- R. C. Merton., "On Estimating the Expected Return on the Market: An Exploratory Investigation", J. Financial Econ., vol. 8, no. 4, pp. 323--361, Dec. 1980Google ScholarCross Ref
Index Terms
- Selection of Market Window Size in Portfolio Strategies
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