IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1907.01274.html
   My bibliography  Save this paper

Smart network based portfolios

Author

Listed:
  • Gian Paolo Clemente
  • Rosanna Grassi
  • Asmerilda Hitaj

Abstract

In this article we deal with the problem of portfolio allocation by enhancing network theory tools. We use the dependence structure of the correlations network in constructing some well-known risk-based models in which the estimation of correlation matrix is a building block in the portfolio optimization. We formulate and solve all these portfolio allocation problems using both the standard approach and the network-based approach. Moreover, in constructing the network-based portfolios we propose the use of two different estimators for the covariance matrix: the sample estimator and the shrinkage toward constant correlation one. All the strategies under analysis are implemented on two high-dimensional portfolios having different characteristics, covering the period from January $2001$ to December $2017$. We find that the network-based portfolio consistently better performs and has lower risk compared to the corresponding standard portfolio in an out-of-sample perspective.

Suggested Citation

  • Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2019. "Smart network based portfolios," Papers 1907.01274, arXiv.org.
    • Handle: RePEc:arx:papers:1907.01274
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1907.01274
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jorion, Philippe, 1985. "International Portfolio Diversification with Estimation Risk," The Journal of Business, University of Chicago Press, vol. 58(3), pages 259-278, July.
    2. Bongini, Paola & Clemente, Gian Paolo & Grassi, Rosanna, 2018. "Interconnectedness, G-SIBs and network dynamics of global banking," Finance Research Letters, Elsevier, vol. 27(C), pages 185-192.
    3. Mcassey, Michael P. & Bijma, Fetsje, 2015. "A clustering coefficient for complete weighted networks," Network Science, Cambridge University Press, vol. 3(2), pages 183-195, June.
    4. Jorion, Philippe, 1986. "Bayes-Stein Estimation for Portfolio Analysis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(3), pages 279-292, September.
    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. Hitaj, Asmerilda & Zambruno, Giovanni, 2016. "Are Smart Beta strategies suitable for hedge fund portfolios?," Review of Financial Economics, Elsevier, vol. 29(C), pages 37-51.
    7. repec:dau:papers:123456789/4688 is not listed on IDEAS
    8. Asmerilda Hitaj & Giovanni Zambruno, 2018. "Portfolio Optimization Using Modified Herfindahl Constraint," International Series in Operations Research & Management Science, in: Giorgio Consigli & Silvana Stefani & Giovanni Zambruno (ed.), Handbook of Recent Advances in Commodity and Financial Modeling, chapter 0, pages 211-239, Springer.
    9. Vijay K. Chopra & William T. Ziemba, 2013. "The Effect of Errors in Means, Variances, and Covariances on Optimal Portfolio Choice," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 21, pages 365-373, World Scientific Publishing Co. Pte. Ltd..
    10. 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.
    11. P. Giudici & A. Spelta, 2016. "Graphical Network Models for International Financial Flows," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(1), pages 128-138, January.
    12. Minoiu, Camelia & Reyes, Javier A., 2013. "A network analysis of global banking: 1978–2010," Journal of Financial Stability, Elsevier, vol. 9(2), pages 168-184.
    13. Elton, Edwin J & Gruber, Martin J, 1973. "Estimating the Dependence Structure of Share Prices-Implications for Portfolio Selection," Journal of Finance, American Finance Association, vol. 28(5), pages 1203-1232, December.
    14. Li, Yan & Jiang, Xiong-Fei & Tian, Yue & Li, Sai-Ping & Zheng, Bo, 2019. "Portfolio optimization based on network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 671-681.
    15. Behr, Patrick & Guettler, Andre & Miebs, Felix, 2013. "On portfolio optimization: Imposing the right constraints," Journal of Banking & Finance, Elsevier, vol. 37(4), pages 1232-1242.
    16. Lionel Martellini & Volker Ziemann, 2010. "Improved Estimates of Higher-Order Comoments and Implications for Portfolio Selection," The Review of Financial Studies, Society for Financial Studies, vol. 23(4), pages 1467-1502, April.
    17. Clemente, G.P. & Grassi, R., 2018. "Directed clustering in weighted networks: A new perspective," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 26-38.
    18. M. J. Brennan, 1998. "The Role of Learning in Dynamic Portfolio Decisions," Review of Finance, European Finance Association, vol. 1(3), pages 295-306.
    19. repec:bla:jfinan:v:58:y:2003:i:4:p:1651-1684 is not listed on IDEAS
    20. Peralta, Gustavo & Zareei, Abalfazl, 2016. "A network approach to portfolio selection," Journal of Empirical Finance, Elsevier, vol. 38(PA), pages 157-180.
    21. 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.
    22. David Bauder & Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2021. "Bayesian mean–variance analysis: optimal portfolio selection under parameter uncertainty," Quantitative Finance, Taylor & Francis Journals, vol. 21(2), pages 221-242, February.
    23. Hannah Cheng Juan Zhan & William Rea & Alethea Rea, 2015. "A Comparison of Three Network Portfolio Selection Methods -- Evidence from the Dow Jones," Working Papers in Economics 15/02, University of Canterbury, Department of Economics and Finance.
    24. Giorgio Consigli & Silvana Stefani & Giovanni Zambruno (ed.), 2018. "Handbook of Recent Advances in Commodity and Financial Modeling," International Series in Operations Research and Management Science, Springer, number 978-3-319-61320-8, April.
    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. Christophe Chorro & Emmanuelle Jay & Philippe de Peretti & Thibault Soler, 2021. "Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03216938, HAL.
    2. Christophe Chorro & Emmanuelle Jay & Philippe de Peretti & Thibault Soler, 2021. "Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems," Post-Print halshs-03216938, HAL.
    3. Deev, Oleg & Lyócsa, Štefan, 2020. "Connectedness of financial institutions in Europe: A network approach across quantiles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 550(C).
    4. Christophe Chorro & Emmanuelle Jay & Philippe De Peretti & Thibault Soler, 2021. "Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems," Documents de travail du Centre d'Economie de la Sorbonne 21013, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    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. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2022. "Smart network based portfolios," Annals of Operations Research, Springer, vol. 316(2), pages 1519-1541, September.
    2. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2021. "Asset allocation: new evidence through network approaches," Annals of Operations Research, Springer, vol. 299(1), pages 61-80, April.
    3. Gian Paolo Clemente & Rosanna Grassi & Asmerilda Hitaj, 2018. "Asset allocation: new evidence through network approaches," Papers 1810.09825, arXiv.org.
    4. Guillaume Coqueret, 2015. "Diversified minimum-variance portfolios," Annals of Finance, Springer, vol. 11(2), pages 221-241, May.
    5. Victor DeMiguel & Lorenzo Garlappi & Francisco J. Nogales & Raman Uppal, 2009. "A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms," Management Science, INFORMS, vol. 55(5), pages 798-812, May.
    6. Candelon, B. & Hurlin, C. & Tokpavi, S., 2012. "Sampling error and double shrinkage estimation of minimum variance portfolios," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 511-527.
    7. Mishra, Anil V., 2016. "Foreign bias in Australian-domiciled mutual fund holdings," Pacific-Basin Finance Journal, Elsevier, vol. 39(C), pages 101-123.
    8. Christophe Chorro & Emmanuelle Jay & Philippe De Peretti & Thibault Soler, 2021. "Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems," Documents de travail du Centre d'Economie de la Sorbonne 21013, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    9. Lassance, Nathan & Vrins, Frédéric, 2021. "Portfolio selection with parsimonious higher comoments estimation," Journal of Banking & Finance, Elsevier, vol. 126(C).
    10. Francisco Peñaranda & Enrique Sentana, 2024. "Portfolio management with big data," Working Papers wp2024_2411, CEMFI.
    11. Michael Curran & Patrick O'Sullivan & Ryan Zalla, 2020. "Can Volatility Solve the Naive Portfolio Puzzle?," Papers 2005.03204, arXiv.org, revised Feb 2022.
    12. Mishra, Anil V., 2015. "Measures of equity home bias puzzle," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 293-312.
    13. Christophe Chorro & Emmanuelle Jay & Philippe de Peretti & Thibault Soler, 2021. "Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems," Post-Print halshs-03216938, HAL.
    14. Frahm, Gabriel & Memmel, Christoph, 2008. "Dominating estimators for the global minimum variance portfolio," Discussion Papers in Econometrics and Statistics 2/08, University of Cologne, Institute of Econometrics and Statistics.
    15. Carroll, Rachael & Conlon, Thomas & Cotter, John & Salvador, Enrique, 2017. "Asset allocation with correlation: A composite trade-off," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1164-1180.
    16. Penaranda, Francisco, 2007. "Portfolio choice beyond the traditional approach," LSE Research Online Documents on Economics 24481, London School of Economics and Political Science, LSE Library.
    17. Lorenzo Garlappi & Raman Uppal & Tan Wang, 2007. "Portfolio Selection with Parameter and Model Uncertainty: A Multi-Prior Approach," The Review of Financial Studies, Society for Financial Studies, vol. 20(1), pages 41-81, January.
    18. Dangl, Thomas & Randl, Otto & Zechner, Josef, 2016. "Risk control in asset management: Motives and concepts," CFS Working Paper Series 546, Center for Financial Studies (CFS).
    19. Christophe Chorro & Emmanuelle Jay & Philippe de Peretti & Thibault Soler, 2021. "Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03216938, HAL.
    20. Lassance, Nathan & Vanderveken, Rodolphe & Vrins, Frédéric, 2022. "On the optimal combination of naive and mean-variance portfolio strategies," LIDAM Discussion Papers LFIN 2022006, Université catholique de Louvain, Louvain Finance (LFIN).

    More about this item

    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:1907.01274. 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.