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A new online portfolio selection algorithm based on Kalman Filter and anti-correlation

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  • Chu, Gang
  • Zhang, Wei
  • Sun, Guofeng
  • Zhang, Xiaotao

Abstract

In this paper, we consider both momentum and reversal in the original Anticor algorithm and propose a new online portfolio selection algorithm named the Wavelet de-noise Kalman Momentum anti-correlation algorithm (W-KACM), which can fully exploit the property of the price fluctuation. Our new strategy also employs a improved measure of the cyclically adjusted price relative called the Wavelet de-noise Kalman Filter price relative (WKFPR). WKFPR, unlike the raw price relative that measures only how much the price moves from one period to the next, measures how far the price deviates from the inherent trend value. To demonstrate the effectiveness of our strategy, we extensively simulate on previously untested real market datasets, including Chinese stock market datasets, and make comparison with AC and KACM algorithms. The results of these experiments indicate that our strategy significantly outperforms the Anticor and KACM algorithms without any additional model or computational complexity.

Suggested Citation

  • Chu, Gang & Zhang, Wei & Sun, Guofeng & Zhang, Xiaotao, 2019. "A new online portfolio selection algorithm based on Kalman Filter and anti-correlation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    • Handle: RePEc:eee:phsmap:v:536:y:2019:i:c:s0378437119305412
    DOI: 10.1016/j.physa.2019.04.185
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    as
    1. Gong, Xu & Lin, Boqiang, 2018. "The incremental information content of investor fear gauge for volatility forecasting in the crude oil futures market," Energy Economics, Elsevier, vol. 74(C), pages 370-386.
    2. Tiwari, Aviral Kumar & Mutascu, Mihai Ioan & Albulescu, Claudiu Tiberiu, 2013. "The influence of the international oil prices on the real effective exchange rate in Romania in a wavelet transform framework," Energy Economics, Elsevier, vol. 40(C), pages 714-733.
    3. Wen, Fenghua & Gong, Xu & Cai, Shenghua, 2016. "Forecasting the volatility of crude oil futures using HAR-type models with structural breaks," Energy Economics, Elsevier, vol. 59(C), pages 400-413.
    4. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    5. Bin Li & Steven C. H. Hoi, 2012. "On-Line Portfolio Selection with Moving Average Reversion," Papers 1206.4626, arXiv.org.
    6. Conrad, Jennifer & Kaul, Gautam, 1998. "An Anatomy of Trading Strategies," The Review of Financial Studies, Society for Financial Studies, vol. 11(3), pages 489-519.
    7. Wen, Fenghua & Ye, Zhengke & Yang, Huaidong & Li, Ke, 2018. "Exploring the rebound effect from the perspective of household: An analysis of China's provincial level," Energy Economics, Elsevier, vol. 75(C), pages 345-356.
    8. Wang, Juan & Zhang, Dongxiang & Zhang, Jian, 2015. "Mean reversion in stock prices of seven Asian stock markets: Unit root test and stationary test with Fourier functions," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 157-164.
    9. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    10. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    11. Xu Gong & Boqiang Lin, 2018. "Structural breaks and volatility forecasting in the copper futures market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(3), pages 290-339, March.
    12. Han, Yufeng & Zhou, Guofu & Zhu, Yingzi, 2016. "A trend factor: Any economic gains from using information over investment horizons?," Journal of Financial Economics, Elsevier, vol. 122(2), pages 352-375.
    13. He, Xue-Zhong & Li, Kai & Li, Youwei, 2018. "Asset allocation with time series momentum and reversal," Journal of Economic Dynamics and Control, Elsevier, vol. 91(C), pages 441-457.
    14. Merton, Robert C., 1980. "On estimating the expected return on the market : An exploratory investigation," Journal of Financial Economics, Elsevier, vol. 8(4), pages 323-361, December.
    15. Gong, Xu & Lin, Boqiang, 2017. "Forecasting the good and bad uncertainties of crude oil prices using a HAR framework," Energy Economics, Elsevier, vol. 67(C), pages 315-327.
    16. A. Borodin & R. El-Yaniv & V. Gogan, 2011. "Can We Learn to Beat the Best Stock," Papers 1107.0036, arXiv.org.
    17. Dai, Zhifeng & Wen, Fenghua, 2018. "Some improved sparse and stable portfolio optimization problems," Finance Research Letters, Elsevier, vol. 27(C), pages 46-52.
    18. Carlos Eduardo de Moura & Adrian Pizzinga & Jorge Zubelli, 2016. "A pairs trading strategy based on linear state space models and the Kalman filter," Quantitative Finance, Taylor & Francis Journals, vol. 16(10), pages 1559-1573, October.
    19. David P. Helmbold & Robert E. Schapire & Yoram Singer & Manfred K. Warmuth, 1998. "On‐Line Portfolio Selection Using Multiplicative Updates," Mathematical Finance, Wiley Blackwell, vol. 8(4), pages 325-347, October.
    20. Alain Kabundi & Raphael Nkomo, 2013. "Kalman Filtering and Online Learning Algorithms for Portfolio Selection," Working Papers 394, Economic Research Southern Africa.
    21. Xiao, Jihong & Zhou, Min & Wen, Fengming & Wen, Fenghua, 2018. "Asymmetric impacts of oil price uncertainty on Chinese stock returns under different market conditions: Evidence from oil volatility index," Energy Economics, Elsevier, vol. 74(C), pages 777-786.
    22. Thomas M. Cover, 1991. "Universal Portfolios," Mathematical Finance, Wiley Blackwell, vol. 1(1), pages 1-29, January.
    23. Ftiti, Zied & Fatnassi, Ibrahim & Tiwari, Aviral Kumar, 2016. "Neoclassical finance, behavioral finance and noise traders: Assessment of gold–oil markets," Finance Research Letters, Elsevier, vol. 17(C), pages 33-40.
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    Cited by:

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    3. Vera Ivanyuk, 2021. "Formulating the Concept of an Investment Strategy Adaptable to Changes in the Market Situation," Economies, MDPI, vol. 9(3), pages 1-19, June.
    4. Yong Zhang & Hong Lin & Lina Zheng & Xingyu Yang, 2022. "Adaptive online portfolio strategy based on exponential gradient updates," Journal of Combinatorial Optimization, Springer, vol. 43(3), pages 672-696, April.

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