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Stock Selection as a Problem in Phylogenetics -- Evidence from the ASX

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  • Hannah Cheng
  • Juan Zhan
  • William Rea
  • Alethea Rea

Abstract

We report the results of fifteen sets of portfolio selection simulations using stocks in the ASX200 index for the period May 2000 to December 2013. We investigated five portfolio selection methods, randomly and from within industrial groups, and three based on neighbor-Net phylogenetic networks. We report that using random, industrial groups, or neighbor-Net phylogenetic networks alone rarely produced statistically significant reduction in risk, though in four out of the five cases in which it did so, the portfolios selected using the phylogenetic networks had the lowest risk. However, we report that when using the neighbor-Net phylogenetic networks in combination with industry group selection that substantial reductions in portfolio return spread were achieved.

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  • Hannah Cheng & Juan Zhan & William Rea & Alethea Rea, 2016. "Stock Selection as a Problem in Phylogenetics -- Evidence from the ASX," Papers 1603.02354, arXiv.org.
    • Handle: RePEc:arx:papers:1603.02354
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    1. Turan G. Bali & Nusret Cakici & Xuemin (Sterling) Yan & Zhe Zhang, 2005. "Does Idiosyncratic Risk Really Matter?," Journal of Finance, American Finance Association, vol. 60(2), pages 905-929, April.
    2. Luca Benzoni & Pierre Collin‐Dufresne & Robert S. Goldstein, 2007. "Portfolio Choice over the Life‐Cycle when the Stock and Labor Markets Are Cointegrated," Journal of Finance, American Finance Association, vol. 62(5), pages 2123-2167, October.
    3. 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.
    4. Bai, Ye & Green, Christopher J., 2010. "International diversification strategies: Revisited from the risk perspective," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 236-245, January.
    5. 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.
    6. repec:bla:jfinan:v:58:y:2003:i:3:p:975-1008 is not listed on IDEAS
    7. Djauhari, Maman A., 2012. "A robust filter in stock networks analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5049-5057.
    8. Rea, Alethea & Rea, William, 2014. "Visualization of a stock market correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 400(C), pages 109-123.
    9. Naylor, Michael J. & Rose, Lawrence C. & Moyle, Brendan J., 2007. "Topology of foreign exchange markets using hierarchical structure methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 199-208.
    10. Dale L. Domian & David A. Louton & Marie D. Racine, 2007. "Diversification in Portfolios of Individual Stocks: 100 Stocks Are Not Enough," The Financial Review, Eastern Finance Association, vol. 42(4), pages 557-570, November.
    11. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    12. John L. Evans & Stephen H. Archer, 1968. "Diversification And The Reduction Of Dispersion: An Empirical Analysis," Journal of Finance, American Finance Association, vol. 23(5), pages 761-767, December.
    13. G. Bonanno & G. Caldarelli & F. Lillo & S. Micciché & N. Vandewalle & R. Mantegna, 2004. "Networks of equities in financial markets," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 38(2), pages 363-371, March.
    14. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    15. Jorion, Philippe, 1985. "International Portfolio Diversification with Estimation Risk," The Journal of Business, University of Chicago Press, vol. 58(3), pages 259-278, July.
    16. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    17. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    18. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
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    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G2 - Financial Economics - - Financial Institutions and Services
    • G3 - Financial Economics - - Corporate Finance and Governance
    • F2 - International Economics - - International Factor Movements and International Business
    • F3 - International Economics - - International Finance
    • F41 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - Open Economy Macroeconomics
    • F42 - International Economics - - Macroeconomic Aspects of International Trade and Finance - - - International Policy Coordination and Transmission

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