On-Line Portfolio Selection Strategy Based on Weighted Moving Average Asymmetric Mean Reversion

Zijin PENG

Abstract


Mean reversion is an important property for constructing efficient on-line portfolio selection strategy. The existing strategies mostly suppose that the mean reversion is multi-period symmetric or single-period asymmetric. However, the mean reversion is multi-period and asymmetric in the real market. Taking this into account, on-line strategies based on multi-period asymmetric mean reversion is proposed. With designing multi-piecewise loss function and imitating passive aggressive algorithm, we propose a new on-line strategy WMAAMR. This strategy runs in linear time, and thus is suitable for large-scale trading applications. Empirical results on four real markets show that WMAAMR can achieve better results and bear higher transaction cost rate.

Keywords


Mean reversion; Weighted moving average; Multi-period; Asymmetry; Passive aggressive algorithm; On-line portfolio selection strategy

Full Text:

PDF

References


Blum, A., & Kalai, A. (1999). Universal portfolios with and without transaction costs. Machine Learning, 35, 193-205.

Borodin, A., El-Yaniv, R., & Gogan, V. (2004). Can we learn to beat the best stock. Journal of Artificial Intelligence Research, 21(1), 579-594.

Bruce, N. L. (1990). Fads, martingales, and market efficiency. Quarterly Journal of Economics, 105(1), 1-28.

Cover, T. M. (1991). Universal portfolio. Mathematics Finance, 1(1), 1-29.

Cover, T. M., & Ordentlich, E. (1996). Universal portfolios with side information. IEEE Transactions on Information Theory, 42(2), 348-363.

Helmbold, D. P., Schapir, R. E., & Singer, Y., et al. (1997). A comparison of new and old algorithm for a mixture estimation problem. Machine Learning, 27, 97-119.

Helmbold, D. P., Singer, Y., & Schapir, R. E., et al. (1998). On-line portfolio selection using multiplicative updates. Mathematics Finance, 8(4), 325-347.

Kelly, J. L. (1956). A new interpretation of information rate. Bell Systems Technical Journal, 35(4), 917-926.

Kiseok, N., & Chong, S. P. (2003). Is asymmetric mean-reverting pattern in stock returns systematic? Evidence from Pacific-basin markets in the short-horizon. Journal of International Financial Markets, Institutions and Money, 13(5), 481-502.

Kiseok, N., Chong, S. P., & Stephen, L. A. (2001). Asymmetric reverting behavior of short-horizon stock returns: An evidence of stock market overreaction. Journal of Banking & Finance, 25(4), 807-824.

Li, B., & Hoi, S. C. H. (2012). On-line portfolio selection with moving average reversion. In Proceedings of the 29th International Conference on Machine Learning, Edinburgh, Scotland, UK.

Li, B., Zhao, P. L, & Hoi, S. C. H. (2012). PAMR: Passive aggressive mean reversion strategy for portfolio selection. Machine Learning, 87, 221-258.

Markowitz, H. W. (1952). Portfolio selection. Journal of Finance, 7, 77-91.

Pang, J. S. (1980). A new efficient algorithm for a class of portfolio selection problem. Operational Research, 28, 754-767.

Perold, A. F. (1984). Large-scale portfolio optimization. Management Science, 30, 1143-1160.

Werner, F. M., & Richard, T. (1985). Does the stock market overreact? Journal of Finance, 40(3), 793-805.

Zhang, W. G. (2007). Possibilistic mean-standard deviation models to portfolio selection for bounded assets. Applied Mathematics and Computation, 189, 1614-1623.

Zhang, W. G., & Wang, Y. L. (2008). An analytic derivation of admissible efficient frontier with borrowing. European Journal of Operation Research, 184, 229-243.

Zhang, W. G., Wang, Y. L., & Chen, Z. P., et al. (2007). Possibilistic mean-variance models and efficient frontiers for portfolio selection problem. Information Sciences, 177, 2787-2801.




DOI: http://dx.doi.org/10.3968/n

Refbacks

  • There are currently no refbacks.


Copyright (c) 2016 Management Science and Engineering



Share us to:   

Reminder

  • We are currently accepting submissions via email only.

    The registration and online submission functions have been disabled.

    Please send your manuscripts to mse@cscanada.net，or mse@cscanada.org  for consideration.

    We look forward to receiving your work.

 


We only use three mailboxes as follows to deal with issues about paper acceptance, payment and submission of electronic versions of our journals to databases:
caooc@hotmail.com; mse@cscanada.net; mse@cscanada.org

 Articles published in Management Science and Engineering are licensed under Creative Commons Attribution 4.0 (CC-BY).

 MANAGEMENT SCIENCE AND ENGINEERING Editorial Office

Address:1055 Rue Lucien-L'Allier, Unit #772, Montreal, QC H3G 3C4, Canada.

Telephone: 1-514-558 6138
Http://www.cscanada.net Http://www.cscanada.org

Copyright © 2010 Canadian Research & Development Centre of Sciences and Cultures