IDEAS home Printed from https://ideas.repec.org/a/eee/ememar/v16y2013icp145-169.html
   My bibliography  Save this article

Separating the wheat from the chaff: Understanding portfolio returns in an emerging market

Author

Listed:
  • Eterovic, Nicolas A.
  • Eterovic, Dalibor S.

Abstract

In this paper we apply Random Matrix Theory (RMT) to study daily return correlations of 83 companies that are part of the Chilean stock market during the period 2000 to 2011. We find that using RMT to identify statistically significant correlations within our sample of stocks significantly improves the efficiency of a family of Markowitz Portfolios. Moreover, by using Vector Autoregressive analysis we identify global risk aversion as the main driver of the Chilean equity market returns followed in importance by shocks to the monthly rate of inflation and the country's monetary policy rate. By studying the effects of macroeconomic variables on the constructed portfolio returns we reach a better understanding of the true risks involved in an emerging market portfolio.

Suggested Citation

  • Eterovic, Nicolas A. & Eterovic, Dalibor S., 2013. "Separating the wheat from the chaff: Understanding portfolio returns in an emerging market," Emerging Markets Review, Elsevier, vol. 16(C), pages 145-169.
    • Handle: RePEc:eee:ememar:v:16:y:2013:i:c:p:145-169
    DOI: 10.1016/j.ememar.2013.05.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S156601411300037X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ememar.2013.05.001?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Plerou, V & Gopikrishnan, P & Rosenow, B & Amaral, L.A.N & Stanley, H.E, 2000. "A random matrix theory approach to financial cross-correlations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 287(3), pages 374-382.
    3. Burda, Z. & Görlich, A. & Jarosz, A. & Jurkiewicz, J., 2004. "Signal and noise in correlation matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 295-310.
    4. Vasiliki Plerou & Parameswaran Gopikrishnan & Bernd Rosenow & Luis A. Nunes Amaral & H. Eugene Stanley, 1999. "Universal and non-universal properties of cross-correlations in financial time series," Papers cond-mat/9902283, arXiv.org.
    5. Varga-Haszonits, I. & Kondor, I., 2007. "Noise sensitivity of portfolio selection in constant conditional correlation GARCH models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 307-318.
    6. 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.
    7. Plerou, V. & Gopikrishnan, P. & Rosenow, B. & Amaral, L.A.N. & Stanley, H.E., 2001. "Collective behavior of stock price movements—a random matrix theory approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(1), pages 175-180.
    8. Malevergne, Y. & Sornette, D., 2004. "Collective origin of the coexistence of apparent random matrix theory noise and of factors in large sample correlation matrices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 331(3), pages 660-668.
    9. Plerou, Vasiliki & Gopikrishnan, Parameswaran & Rosenow, Bernd & Amaral, Luis A.N. & Stanley, H.Eugene, 2000. "Econophysics: financial time series from a statistical physics point of view," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 279(1), pages 443-456.
    10. Bunda, Irina & Hamann, A. Javier & Lall, Subir, 2009. "Correlations in emerging market bonds: The role of local and global factors," Emerging Markets Review, Elsevier, vol. 10(2), pages 67-96, June.
    11. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    12. Raj Kumar Pan & Sitabhra Sinha, 2007. "Collective behavior of stock price movements in an emerging market," Papers 0704.0773, arXiv.org, revised Nov 2007.
    13. Nilantha, K.G.D.R. & Ranasinghe, & Malmini, P.K.C., 2007. "Eigenvalue density of cross-correlations in Sri Lankan financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(2), pages 345-356.
    14. Varsha Kulkarni & Nivedita Deo, 2007. "Correlation and volatility in an Indian stock market: A random matrix approach," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 60(1), pages 101-109, November.
    15. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    16. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    17. Wilcox, Diane & Gebbie, Tim, 2007. "An analysis of cross-correlations in an emerging market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 375(2), pages 584-598.
    18. Rosenow, Bernd, 2008. "Determining the optimal dimensionality of multivariate volatility models with tools from random matrix theory," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 279-302, January.
    19. Carol Alexander, 2002. "Principal Component Models for Generating Large GARCH Covariance Matrices," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 31(2), pages 337-359, July.
    20. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    21. Zdzislaw Burda & Jerzy Jurkiewicz, 2003. "Signal and Noise in Financial Correlation Matrices," Papers cond-mat/0312496, arXiv.org, revised Feb 2004.
    22. Burda, Zdzisław & Jurkiewicz, Jerzy, 2004. "Signal and noise in financial correlation matrices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 67-72.
    23. 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.
    24. Rosenow, Bernd & Gopikrishnan, Parameswaran & Plerou, Vasiliki & Eugene Stanley, H, 2003. "Dynamics of cross-correlations in the stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 241-246.
    25. Wilcox, Diane & Gebbie, Tim, 2004. "On the analysis of cross-correlations in South African market data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 344(1), pages 294-298.
    26. 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.
    27. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    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. Narayan, Paresh Kumar & Narayan, Seema & Thuraisamy, Kannan Sivananthan, 2014. "Can institutions and macroeconomic factors predict stock returns in emerging markets?," Emerging Markets Review, Elsevier, vol. 19(C), pages 77-95.
    2. Eterovic, Dalibor & Sweet, Cassandra & Eterovic, Nicolas, 2022. "Asymmetric spillovers in emerging market monetary policy," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 650-662.
    3. Silahli, Baykar & Dingec, Kemal Dincer & Cifter, Atilla & Aydin, Nezir, 2021. "Portfolio value-at-risk with two-sided Weibull distribution: Evidence from cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).

    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. Dalibor Eterovic & Nicolas Eterovic, 2012. "Separating the Wheat from the Chaff: Understanding Portfolio Returns in an Emerging Market," Working Papers wp_025, Adolfo Ibáñez University, School of Government.
    2. Sandoval, Leonidas & Franca, Italo De Paula, 2012. "Correlation of financial markets in times of crisis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 187-208.
    3. Juan Pineiro-Chousa & Marcos Vizcaíno-González & Jérôme Caby, 2016. "Analysing voting behaviour in the United States banking sector through eigenvalue decomposition," Applied Economics Letters, Taylor & Francis Journals, vol. 23(12), pages 840-843, August.
    4. Wang, Gang-Jin & Xie, Chi & Chen, Shou & Yang, Jiao-Jiao & Yang, Ming-Yan, 2013. "Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(17), pages 3715-3730.
    5. Conlon, T. & Ruskin, H.J. & Crane, M., 2009. "Cross-correlation dynamics in financial time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 705-714.
    6. Martins, André C.R., 2007. "Non-stationary correlation matrices and noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 379(2), pages 552-558.
    7. Conlon, T. & Ruskin, H.J. & Crane, M., 2007. "Random matrix theory and fund of funds portfolio optimisation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(2), pages 565-576.
    8. James, Nick & Menzies, Max & Gottwald, Georg A., 2022. "On financial market correlation structures and diversification benefits across and within equity sectors," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    9. Yin, Yi & Shang, Pengjian, 2013. "Modified DFA and DCCA approach for quantifying the multiscale correlation structure of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6442-6457.
    10. Leonidas Sandoval Junior & Italo De Paula Franca, 2011. "Correlation of financial markets in times of crisis," Papers 1102.1339, arXiv.org, revised Mar 2011.
    11. Cai, Yumei & Cui, Xiaomei & Huang, Qianyun & Sun, Jianqiang, 2017. "Hierarchy, cluster, and time-stable information structure of correlations between international financial markets," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 562-573.
    12. Kuper, Gerard H. & Lestano, 2007. "Dynamic conditional correlation analysis of financial market interdependence: An application to Thailand and Indonesia," Journal of Asian Economics, Elsevier, vol. 18(4), pages 670-684, August.
    13. Stosic, Darko & Stosic, Dusan & Ludermir, Teresa B. & Stosic, Tatijana, 2018. "Collective behavior of cryptocurrency price changes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 499-509.
    14. Roy, Rudra Prosad & Sinha Roy, Saikat, 2017. "Financial contagion and volatility spillover: An exploration into Indian commodity derivative market," Economic Modelling, Elsevier, vol. 67(C), pages 368-380.
    15. Siburg, Karl Friedrich & Stoimenov, Pavel & Weiß, Gregor N.F., 2015. "Forecasting portfolio-Value-at-Risk with nonparametric lower tail dependence estimates," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 129-140.
    16. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    17. Li, Lihui & Wen, Tao, 2013. "Estimation of C-MGARCH models based on the MBP method," Statistics & Probability Letters, Elsevier, vol. 83(2), pages 665-673.
    18. Hasanov, Akram Shavkatovich & Do, Hung Xuan & Shaiban, Mohammed Sharaf, 2016. "Fossil fuel price uncertainty and feedstock edible oil prices: Evidence from MGARCH-M and VIRF analysis," Energy Economics, Elsevier, vol. 57(C), pages 16-27.
    19. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    20. Garcia, René & Tsafack, Georges, 2011. "Dependence structure and extreme comovements in international equity and bond markets," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1954-1970, August.

    More about this item

    Keywords

    Random Matrix Theory; Portfolio optimization; Financial markets and the macroeconomy;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    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:eee:ememar:v:16:y:2013:i:c:p:145-169. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620356 .

    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.