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Dynamic Portfolio Strategy Using Clustering Approach

Author

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  • Fei Ren
  • Ya-Nan Lu
  • Sai-Ping Li
  • Xiong-Fei Jiang
  • Li-Xin Zhong
  • Tian Qiu

Abstract

The problem of portfolio optimization is one of the most important issues in asset management. We here propose a new dynamic portfolio strategy based on the time-varying structures of MST networks in Chinese stock markets, where the market condition is further considered when using the optimal portfolios for investment. A portfolio strategy comprises two stages: First, select the portfolios by choosing central and peripheral stocks in the selection horizon using five topological parameters, namely degree, betweenness centrality, distance on degree criterion, distance on correlation criterion and distance on distance criterion. Second, use the portfolios for investment in the investment horizon. The optimal portfolio is chosen by comparing central and peripheral portfolios under different combinations of market conditions in the selection and investment horizons. Market conditions in our paper are identified by the ratios of the number of trading days with rising index to the total number of trading days, or the sum of the amplitudes of the trading days with rising index to the sum of the amplitudes of the total trading days. We find that central portfolios outperform peripheral portfolios when the market is under a drawup condition, or when the market is stable or drawup in the selection horizon and is under a stable condition in the investment horizon. We also find that peripheral portfolios gain more than central portfolios when the market is stable in the selection horizon and is drawdown in the investment horizon. Empirical tests are carried out based on the optimal portfolio strategy. Among all possible optimal portfolio strategies based on different parameters to select portfolios and different criteria to identify market conditions, 65% of our optimal portfolio strategies outperform the random strategy for the Shanghai A-Share market while the proportion is 70% for the Shenzhen A-Share market.

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  • Fei Ren & Ya-Nan Lu & Sai-Ping Li & Xiong-Fei Jiang & Li-Xin Zhong & Tian Qiu, 2017. "Dynamic Portfolio Strategy Using Clustering Approach," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.
    • Handle: RePEc:plo:pone00:0169299
    DOI: 10.1371/journal.pone.0169299
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    as
    1. Ledoit, Olivier & Wolf, Michael, 2004. "A well-conditioned estimator for large-dimensional covariance matrices," Journal of Multivariate Analysis, Elsevier, vol. 88(2), pages 365-411, February.
    2. Vladimir Boginski & Sergiy Butenko & Oleg Shirokikh & Svyatoslav Trukhanov & Jaime Gil Lafuente, 2014. "A network-based data mining approach to portfolio selection via weighted clique relaxations," Annals of Operations Research, Springer, vol. 216(1), pages 23-34, May.
    3. Miccichè, Salvatore & Bonanno, Giovanni & Lillo, Fabrizio & N. Mantegna, Rosario, 2003. "Degree stability of a minimum spanning tree of price return and volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 66-73.
    4. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    5. Ravi Jagannathan & Tongshu Ma, 2003. "Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraints Helps," Journal of Finance, American Finance Association, vol. 58(4), pages 1651-1683, August.
    6. R. Mantegna, 1999. "Hierarchical structure in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 11(1), pages 193-197, September.
    7. M. Tumminello & T. Di Matteo & T. Aste & R. N. Mantegna, 2007. "Correlation based networks of equity returns sampled at different time horizons," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(2), pages 209-217, January.
    8. Crama, Y. & Schyns, M., 2003. "Simulated annealing for complex portfolio selection problems," European Journal of Operational Research, Elsevier, vol. 150(3), pages 546-571, November.
    9. Ferreira, Miguel A. & Gama, Paulo M., 2007. "Does sovereign debt ratings news spill over to international stock markets?," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3162-3182, October.
    10. Yang, Chunxia & Zhu, Xueshuai & Li, Qian & Chen, Yanhua & Deng, Qiangqiang, 2014. "Research on the evolution of stock correlation based on maximal spanning trees," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 1-18.
    11. X. F. Jiang & T. T. Chen & B. Zheng, 2014. "Structure of local interactions in complex financial dynamics," Papers 1406.0070, arXiv.org.
    12. Zhi-Qiang Jiang & Wei-Xing Zhou, 2011. "Multifractal detrending moving average cross-correlation analysis," Papers 1103.2577, arXiv.org, revised Mar 2011.
    13. Bradford Case & Yawei Yang & Yildiray Yildirim, 2012. "Dynamic Correlations Among Asset Classes: REIT and Stock Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 44(3), pages 298-318, April.
    14. Juan Gabriel Brida & Wiston Adrian Risso, 2007. "Dynamics And Structure Of The Main Italian Companies," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 18(11), pages 1783-1793.
    15. Fei Ren & Wei-Xing Zhou, 2014. "Dynamic Evolution of Cross-Correlations in the Chinese Stock Market," PLOS ONE, Public Library of Science, vol. 9(5), pages 1-15, May.
    16. Yue-Hua Dai & Wen-Jie Xie & Zhi-Qiang Jiang & George J. Jiang & Wei-Xing Zhou, 2016. "Correlation structure and principal components in the global crude oil market," Empirical Economics, Springer, vol. 51(4), pages 1501-1519, December.
    17. Dror Y Kenett & Matthias Raddant & Thomas Lux & Eshel Ben-Jacob, 2012. "Evolvement of Uniformity and Volatility in the Stressed Global Financial Village," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-8, February.
    18. Thorbecke, Willem, 1997. "On Stock Market Returns and Monetary Policy," Journal of Finance, American Finance Association, vol. 52(2), pages 635-654, June.
    19. repec:bla:jfinan:v:58:y:2003:i:4:p:1651-1684 is not listed on IDEAS
    20. Dror Y Kenett & Michele Tumminello & Asaf Madi & Gitit Gur-Gershgoren & Rosario N Mantegna & Eshel Ben-Jacob, 2010. "Dominating Clasp of the Financial Sector Revealed by Partial Correlation Analysis of the Stock Market," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-14, December.
    21. Wei-Xing Zhou, 2008. "Multifractal detrended cross-correlation analysis for two nonstationary signals," Papers 0803.2773, arXiv.org.
    22. Daniel J. Fenn & Mason A. Porter & Stacy Williams & Mark McDonald & Neil F. Johnson & Nick S. Jones, 2010. "Temporal Evolution of Financial Market Correlations," Papers 1011.3225, arXiv.org, revised May 2011.
    23. Daly, J. & Crane, M. & Ruskin, H.J., 2008. "Random matrix theory filters in portfolio optimisation: A stability and risk assessment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(16), pages 4248-4260.
    24. Drożdż, S & Grümmer, F & Górski, A.Z & Ruf, F & Speth, J, 2000. "Dynamics of competition between collectivity and noise in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 440-449.
    25. Miralles-Marcelo, José Luis & Miralles-Quirós, María del Mar & Miralles-Quirós, José Luis, 2015. "Improving international diversification benefits for US investors," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 64-76.
    26. Kotkatvuori-Örnberg, Juha & Nikkinen, Jussi & Äijö, Janne, 2013. "Stock market correlations during the financial crisis of 2008–2009: Evidence from 50 equity markets," International Review of Financial Analysis, Elsevier, vol. 28(C), pages 70-78.
    27. Hendrik Scholz, 2007. "Refinements to the Sharpe ratio: Comparing alternatives for bear markets," Journal of Asset Management, Palgrave Macmillan, vol. 7(5), pages 347-357, January.
    28. Dong-Ming Song & Michele Tumminello & Wei-Xing Zhou & Rosario N. Mantegna, 2011. "Evolution of worldwide stock markets, correlation structure and correlation based graphs," Papers 1103.5555, arXiv.org.
    29. Steven H. Strogatz, 2001. "Exploring complex networks," Nature, Nature, vol. 410(6825), pages 268-276, March.
    30. Tang, Yong & Luo, Yong & Xiong, Jie & Zhao, Fei & Zhang, Yi-Cheng, 2013. "Impact of monetary policy changes on the Chinese monetary and stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4435-4449.
    31. J.-P. Onnela & K. Kaski & J. Kertész, 2004. "Clustering and information in correlation based financial networks," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 353-362, March.
    32. N.C. Suganya & G.A. Pai, 2012. "Wavelet evolutionary network for complex-constrained portfolio rebalancing," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(7), pages 1367-1385.
    33. Kasman, Saadet & Vardar, Gülin & Tunç, Gökçe, 2011. "The impact of interest rate and exchange rate volatility on banks' stock returns and volatility: Evidence from Turkey," Economic Modelling, Elsevier, vol. 28(3), pages 1328-1334, May.
    34. Bomfim, Antulio N., 2003. "Pre-announcement effects, news effects, and volatility: Monetary policy and the stock market," Journal of Banking & Finance, Elsevier, vol. 27(1), pages 133-151, January.
    35. Sun, Xuelian & Liu, Zixian, 2016. "Optimal portfolio strategy with cross-correlation matrix composed by DCCA coefficients: Evidence from the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 667-679.
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