IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1512.01905.html
   My bibliography  Save this paper

A Comparision of Three Network Portfolio Selection Methods -- Evidence from the Dow Jones

Author

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

Abstract

We compare three network portfolio selection methods; hierarchical clustering trees, minimum spanning trees and neighbor-Nets, with random and industry group selection methods on twelve years of data from the 30 Dow Jones Industrial Average stocks from 2001 to 2013 for very small private investor sized portfolios. We find that the three network methods perform on par with randomly selected portfolios.

Suggested Citation

  • Hannah Cheng Juan Zhan & William Rea & Alethea Rea, 2015. "A Comparision of Three Network Portfolio Selection Methods -- Evidence from the Dow Jones," Papers 1512.01905, arXiv.org.
    • Handle: RePEc:arx:papers:1512.01905
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1512.01905
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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?," 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. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    14. Jorion, Philippe, 1985. "International Portfolio Diversification with Estimation Risk," The Journal of Business, University of Chicago Press, vol. 58(3), pages 259-278, July.
    15. 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.
    16. 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.
    17. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2019. "Smart network based portfolios," Papers 1907.01274, arXiv.org.
    2. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2022. "Smart network based portfolios," Annals of Operations Research, Springer, vol. 316(2), pages 1519-1541, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cheng Juan Zhan & William Rea & Alethea Rea, 2016. "Stock Selection as a Problem in Phylogenetics—Evidence from the ASX," IJFS, MDPI, vol. 4(4), pages 1-19, September.
    2. Hannah Cheng Juan Zhan & William Rea & Alethea Rea, 2014. "An Application of Correlation Clustering to Portfolio Diversification," Working Papers in Economics 14/11, University of Canterbury, Department of Economics and Finance.
    3. Tienyu Hwang & Simon Gao & Heather Owen, 2012. "A two‐pass model study of the CAPM: evidence from the UK stock market," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 29(2), pages 89-104, June.
    4. de Carvalho, Pablo Jose Campos & Gupta, Aparna, 2018. "A network approach to unravel asset price comovement using minimal dependence structure," Journal of Banking & Finance, Elsevier, vol. 91(C), pages 119-132.
    5. Miffre, Joëlle & Brooks, Chris & Li, Xiafei, 2013. "Idiosyncratic volatility and the pricing of poorly-diversified portfolios," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 78-85.
    6. Gautier Marti & Frank Nielsen & Miko{l}aj Bi'nkowski & Philippe Donnat, 2017. "A review of two decades of correlations, hierarchies, networks and clustering in financial markets," Papers 1703.00485, arXiv.org, revised Nov 2020.
    7. Evangelos Ioannidis & Iordanis Sarikeisoglou & Georgios Angelidis, 2023. "Portfolio Construction: A Network Approach," Mathematics, MDPI, vol. 11(22), pages 1-24, November.
    8. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    9. Haensly, Paul J., 2020. "Risk decomposition, estimation error, and naïve diversification," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    10. Constantinos Antoniou & John A. Doukas & Avanidhar Subrahmanyam, 2016. "Investor Sentiment, Beta, and the Cost of Equity Capital," Management Science, INFORMS, vol. 62(2), pages 347-367, February.
    11. David E. Allen & Michael McAleer & Abhay K. Singh, 2019. "Daily market news sentiment and stock prices," Applied Economics, Taylor & Francis Journals, vol. 51(30), pages 3212-3235, June.
    12. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    13. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    14. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, November.
    15. Tienyu Hwang & Simon Gao & Heather Owen, 2014. "Markowitz efficiency and size effect: evidence from the UK stock market," Review of Quantitative Finance and Accounting, Springer, vol. 43(4), pages 721-750, November.
    16. Matthias Raddant & Friedrich Wagner, 2017. "Transitions in the stock markets of the US, UK and Germany," Quantitative Finance, Taylor & Francis Journals, vol. 17(2), pages 289-297, February.
    17. Hassen Raîs, 2016. "Idiosyncratic Risk and the Cross-Section of European Insurance Equity Returns," Post-Print hal-01764088, HAL.
    18. Marcin Wk{a}torek & Stanis{l}aw Dro.zd.z & Jaros{l}aw Kwapie'n & Ludovico Minati & Pawe{l} O'swik{e}cimka & Marek Stanuszek, 2020. "Multiscale characteristics of the emerging global cryptocurrency market," Papers 2010.15403, arXiv.org, revised Mar 2021.
    19. Philipp Stephan & Rüdiger Nitzsch, 2013. "Do individual investors’ stock recommendations in online communities contain investment value?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 27(2), pages 149-186, June.
    20. Bin Liu & Amalia Di Iorio, 2016. "The pricing of idiosyncratic volatility: An Australian study," Australian Journal of Management, Australian School of Business, vol. 41(2), pages 353-375, May.

    More about this item

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1512.01905. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.