IDEAS home Printed from https://ideas.repec.org/a/vrs/crebss/v5y2019i1p9-20n2.html
   My bibliography  Save this article

Application of semi-deviation as a proxy for the expected return estimation in the Croatian equity market

Author

Listed:
  • Dolinar Denis

    (University of Zagreb, Faculty of Economics & Business, Croatia)

  • Zoričić Davor

    (University of Zagreb, Faculty of Economics & Business, Croatia)

  • Golubić Zrinka Lovretin

    (University of Zagreb, Faculty of Economics & Business, Croatia)

Abstract

In the field of portfolio management the focus has been on the out-of-sample estimation of the covariance matrix mainly because the estimation of expected return is much more challenging. However, recent research efforts have not only tried to improve the estimation of risk parameters by expanding the analysis beyond the mean-variance setting but also by testing whether risk measures can be used as proxies for the expected return in the stock market. In this research, we test the standard deviation (measure of total volatility) and the semi-deviation (measure of downside risk) as proxies for the expected market return in the illiquid and undeveloped Croatian stock market in the period from January 2005 until November 2017. In such an environment, the application of the proposed methodology yielded poor results, which helps explain the failure of the out-of-sample estimation of the maximum Sharpe ratio portfolio in earlier research in the Croatian equity market.

Suggested Citation

  • Dolinar Denis & Zoričić Davor & Golubić Zrinka Lovretin, 2019. "Application of semi-deviation as a proxy for the expected return estimation in the Croatian equity market," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 5(1), pages 9-20, May.
  • Handle: RePEc:vrs:crebss:v:5:y:2019:i:1:p:9-20:n:2
    DOI: 10.2478/crebss-2019-0002
    as

    Download full text from publisher

    File URL: https://doi.org/10.2478/crebss-2019-0002
    Download Restriction: no

    File URL: https://libkey.io/10.2478/crebss-2019-0002?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
    ---><---

    References listed on IDEAS

    as
    1. Škrinjarić Tihana & Šego Boško, 2016. "Dynamic Portfolio Selection on Croatian Financial Markets: MGARCH Approach," Business Systems Research, Sciendo, vol. 7(2), pages 78-90, September.
    2. repec:oup:rfinst:v:25:y::i:12:p:3711-3751 is not listed on IDEAS
    3. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    4. repec:dau:papers:123456789/4688 is not listed on IDEAS
    5. Dolinar, Denis, 2013. "Test Of The Fama-French Three-Factor Model In Croatia," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 4(2), pages 101-112.
    6. Bali, Turan G. & Demirtas, K. Ozgur & Levy, Haim, 2009. "Is There an Intertemporal Relation between Downside Risk and Expected Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(4), pages 883-909, August.
    7. Bruno Feunou & Ricardo Lopez Aliouchkin & Roméo Tedongap & Lai Xi, 2017. "Variance Premium, Downside Risk and Expected Stock Returns," Staff Working Papers 17-58, Bank of Canada.
    8. Davor Kunovac, 2011. "Asymmetric correlations on the Croatian equity market," Financial Theory and Practice, Institute of Public Finance, vol. 35(1), pages 1-24.
    9. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    10. Benaković Dubravka & Posedel Petra, 2010. "Do macroeconomic factors matter for stock returns? Evidence from estimating a multifactor model on the Croatian market," Business Systems Research, Sciendo, vol. 1(1-2), pages 39-46, January.
    11. Peter Christoffersen & Vihang Errunza & Kris Jacobs & Hugues Langlois, 2012. "Is the Potential for International Diversification Disappearing? A Dynamic Copula Approach," Review of Financial Studies, Society for Financial Studies, vol. 25(12), pages 3711-3751.
    12. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    13. Thanos Verousis & Nikolaos Voukelatos, 2018. "Cross-sectional dispersion and expected returns," Quantitative Finance, Taylor & Francis Journals, vol. 18(5), pages 813-826, May.
    14. 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.
    15. Huang, Wei & Liu, Qianqiu & Ghon Rhee, S. & Wu, Feng, 2012. "Extreme downside risk and expected stock returns," Journal of Banking & Finance, Elsevier, vol. 36(5), pages 1492-1502.
    16. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    Full references (including those not matched with items on IDEAS)

    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. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    2. Harris, Richard D.F. & Nguyen, Linh H. & Stoja, Evarist, 2019. "Systematic extreme downside risk," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 128-142.
    3. Peterburgsky, Stanley, 2021. "Aggregate volatility risk: International evidence," Global Finance Journal, Elsevier, vol. 47(C).
    4. Christoffersen, Peter & Fournier, Mathieu & Jacobs, Kris & Karoui, Mehdi, 2021. "Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(1), pages 65-91, February.
    5. Roh, Tai-Yong & Byun, Suk Joon & Xu, Yahua, 2020. "Downside uncertainty shocks in the oil and gold markets," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 291-307.
    6. Huang, Huichou & MacDonald, Ronald & Zhao, Yang, 2012. "Global Currency Misalignments, Crash Sensitivity, and Downside Insurance Costs," MPRA Paper 53745, University Library of Munich, Germany, revised 18 Nov 2013.
    7. Atilgan, Yigit & Bali, Turan G. & Demirtas, K. Ozgur & Gunaydin, A. Doruk, 2020. "Left-tail momentum: Underreaction to bad news, costly arbitrage and equity returns," Journal of Financial Economics, Elsevier, vol. 135(3), pages 725-753.
    8. Chabi-Yo, Fousseni & Huggenberger, Markus & Weigert, Florian, 2022. "Multivariate crash risk," Journal of Financial Economics, Elsevier, vol. 145(1), pages 129-153.
    9. Stoja, Evarist & Polanski, Arnold & Nguyen, Linh H. & Pereverzin, Aleksandr, 2023. "Does systematic tail risk matter?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    10. Eom, Cheoljun & Eom, Yunsung & Park, Jong Won, 2023. "Left-tail momentum and tail properties of return distributions: A case of Korea," International Review of Financial Analysis, Elsevier, vol. 87(C).
    11. Long, Huaigang & Zhu, Yanjian & Chen, Lifang & Jiang, Yuexiang, 2019. "Tail risk and expected stock returns around the world," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 162-178.
    12. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, September.
    13. Chang, Bo Young & Christoffersen, Peter & Jacobs, Kris, 2013. "Market skewness risk and the cross section of stock returns," Journal of Financial Economics, Elsevier, vol. 107(1), pages 46-68.
    14. Jain, Ajeet & Strobl, Sascha, 2017. "The effect of volatility persistence on excess returns," Review of Financial Economics, Elsevier, vol. 32(C), pages 58-63.
    15. Sirio Aramonte & Mohammad R. Jahan-Parvar & Samuel Rosen & John W. Schindler, 2022. "Firm-Specific Risk-Neutral Distributions with Options and CDS," Management Science, INFORMS, vol. 68(9), pages 7018-7033, September.
    16. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    17. Charlotte Christiansen & Maik Schmeling & Andreas Schrimpf, 2012. "A comprehensive look at financial volatility prediction by economic variables," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 27(6), pages 956-977, September.
    18. Chabi-Yo, Fousseni, 2011. "Explaining the idiosyncratic volatility puzzle using Stochastic Discount Factors," Journal of Banking & Finance, Elsevier, vol. 35(8), pages 1971-1983, August.
    19. Agarwal, Vikas & Arisoy, Y. Eser & Naik, Narayan Y., 2017. "Volatility of aggregate volatility and hedge fund returns," Journal of Financial Economics, Elsevier, vol. 125(3), pages 491-510.
    20. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2018. "Crash Sensitivity and the Cross Section of Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1059-1100, June.

    More about this item

    Keywords

    expected return estimation; illiquid and undeveloped equity market; semi-deviation;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:vrs:crebss:v:5:y:2019:i:1:p:9-20:n:2. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.com .

    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.