IDEAS home Printed from https://ideas.repec.org/a/eee/riibaf/v34y2015icp397-411.html
   My bibliography  Save this article

Performance of risk-based portfolios under different market conditions: Evidence from India

Author

Listed:
  • Sharma, Prateek
  • Vipul,

Abstract

This study evaluates the performance of risk-based portfolios under different market conditions. We compare four strategies, namely, the equally weighted portfolio (EW), the global minimum variance portfolio (GMV), the most diversified portfolio (MDP) and the equal risk contribution portfolio (ERC). No single strategy consistently dominates the others, under different market conditions. As expected, the GMV has the least downside risk. Although there is no clear winner among the risk-based portfolios, there is evidence that they generally outperform the market capitalization based portfolio.

Suggested Citation

  • Sharma, Prateek & Vipul,, 2015. "Performance of risk-based portfolios under different market conditions: Evidence from India," Research in International Business and Finance, Elsevier, vol. 34(C), pages 397-411.
  • Handle: RePEc:eee:riibaf:v:34:y:2015:i:c:p:397-411
    DOI: 10.1016/j.ribaf.2015.03.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0275531915000318
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ribaf.2015.03.006?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. 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.
    2. Sebastian Krimm & Hendrik Scholz & Marco Wilkens, 2012. "The Sharpe ratio's market climate bias: Theoretical and empirical evidence from US equity mutual funds," Journal of Asset Management, Palgrave Macmillan, vol. 13(4), pages 227-242, August.
    3. Qianqiu Liu, 2009. "On portfolio optimization: How and when do we benefit from high-frequency data?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(4), pages 560-582.
    4. Brière, Marie & Signori, Ombretta, 2013. "Hedging inflation risk in a developing economy: The case of Brazil," Research in International Business and Finance, Elsevier, vol. 27(1), pages 209-222.
    5. Jansen, Dennis W & de Vries, Casper G, 1991. "On the Frequency of Large Stock Returns: Putting Booms and Busts into Perspective," The Review of Economics and Statistics, MIT Press, vol. 73(1), pages 18-24, February.
    6. Karyl Leggio & Donald Lien, 2003. "An empirical examination of the effectiveness of dollar-cost averaging using downside risk performance measures," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 27(2), pages 211-223, June.
    7. Christian Pedersen & Stephen Satchell, 2002. "On the foundation of performance measures under asymmetric returns," Quantitative Finance, Taylor & Francis Journals, vol. 2(3), pages 217-223.
    8. Ledoit, Oliver & Wolf, Michael, 2008. "Robust performance hypothesis testing with the Sharpe ratio," Journal of Empirical Finance, Elsevier, vol. 15(5), pages 850-859, December.
    9. Sharpe, William F, 1991. "Capital Asset Prices with and without Negative Holdings," Journal of Finance, American Finance Association, vol. 46(2), pages 489-509, June.
    10. Michiel de Pooter & Martin Martens & Dick van Dijk, 2008. "Predicting the Daily Covariance Matrix for S&P 100 Stocks Using Intraday Data—But Which Frequency to Use?," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 199-229.
    11. repec:dau:papers:123456789/7873 is not listed on IDEAS
    12. 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.
    13. Eling, Martin & Schuhmacher, Frank, 2007. "Does the choice of performance measure influence the evaluation of hedge funds?," Journal of Banking & Finance, Elsevier, vol. 31(9), pages 2632-2647, September.
    14. Marie Brière & Ombretta Signori, 2013. "Hedging Inflation Risk in a Developing Economy : The case of Brazil," Post-Print hal-01492983, HAL.
    15. Vortelinos, Dimitrios I., 2013. "Portfolio analysis of intraday covariance matrix in the Greek equity market," Research in International Business and Finance, Elsevier, vol. 27(1), pages 66-79.
    16. repec:dau:papers:123456789/4688 is not listed on IDEAS
    17. Hendrik Scholz, 2007. "Refinements to the Sharpe ratio: Comparing alternatives for bear markets," Journal of Asset Management, Palgrave Macmillan, vol. 7(5), pages 347-357, January.
    18. Jobson, J. D. & Korkie, Bob, 1989. "A Performance Interpretation of Multivariate Tests of Asset Set Intersection, Spanning, and Mean-Variance Efficiency," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 24(2), pages 185-204, June.
    19. Craig Israelsen, 2005. "A refinement to the Sharpe ratio and information ratio," Journal of Asset Management, Palgrave Macmillan, vol. 5(6), pages 423-427, April.
    20. Gordon Gemmill & Soosung Hwang & Mark Salmon, 2006. "Performance measurement with loss aversion," Journal of Asset Management, Palgrave Macmillan, vol. 7(3), pages 190-207, September.
    21. Best, Michael J & Grauer, Robert R, 1991. "On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results," Review of Financial Studies, Society for Financial Studies, vol. 4(2), pages 315-342.
    22. Fleming, Jeff & Kirby, Chris & Ostdiek, Barbara, 2003. "The economic value of volatility timing using "realized" volatility," Journal of Financial Economics, Elsevier, vol. 67(3), pages 473-509, March.
    23. Arnold, Tom & Nail, Lance & Nixon, Terry D., 2004. "Do ADRs enhance portfolio performance for a domestic portfolio? Evidence from the 1990s," Research in International Business and Finance, Elsevier, vol. 18(3), pages 341-359, September.
    24. Scherer, Bernd, 2011. "A note on the returns from minimum variance investing," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 652-660, September.
    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. Arezoo Mohammadi & Mehrzad Minnoei & Zadollah Fathi & Mohamamd Ali Keramati & Hossein Baktiari, 2022. "Optimal allocation of bank resources and risk reduction through portfolio decentralization," International Journal of Economic Sciences, European Research Center, vol. 11(2), pages 92-143, November.

    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. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    2. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2016. "Portfolio Choice with High Frequency Data: CRRA Preferences and the Liquidity Effect," GEMF Working Papers 2016-13, GEMF, Faculty of Economics, University of Coimbra.
    3. Grose, Chris & Dasilas, Apostolos & Alexakis, Christos, 2014. "Performance persistence in fixed interest funds: With an eye on the post-debt crisis period," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 155-182.
    4. Santos, André Alves Portela & Ferreira, Alexandre R., 2017. "On the choice of covariance specifications for portfolio selection problems," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 37(1), May.
    5. Miralles-Marcelo, José Luis & Miralles-Quirós, María del Mar & Miralles-Quirós, José Luis, 2015. "Improving international diversification benefits for US investors," The North American Journal of Economics and Finance, Elsevier, vol. 32(C), pages 64-76.
    6. Rui Pedro Brito & Hélder Sebastião & Pedro Godinho, 2017. "On the gains of using high frequency data and higher moments in Portfolio Selection," CeBER Working Papers 2017-02, Centre for Business and Economics Research (CeBER), University of Coimbra.
    7. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    8. R. P. Brito & H. Sebastião & P. Godinho, 2017. "Portfolio choice with high frequency data: CRRA preferences and the liquidity effect," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 16(2), pages 65-86, August.
    9. Du, Jiangze & Wang, Jying-Nan & Hsu, Yuan-Teng & Lai, Kin Keung, 2018. "The importance of hedging currency risk: Evidence from CNY and CNH," Economic Modelling, Elsevier, vol. 75(C), pages 81-92.
    10. 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.
    11. Thomas Trier Bjerring & Omri Ross & Alex Weissensteiner, 2017. "Feature selection for portfolio optimization," Annals of Operations Research, Springer, vol. 256(1), pages 21-40, September.
    12. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2018. "Modeling and forecasting (un)reliable realized covariances for more reliable financial decisions," Journal of Econometrics, Elsevier, vol. 207(1), pages 71-91.
    13. 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.
    14. Hongseon Kim & Soonbong Lee & Seung Bum Soh & Seongmoon Kim, 2022. "Improving portfolio investment performance with distance‐based portfolio‐combining algorithms," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 45(4), pages 941-959, December.
    15. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    16. Matthias M. M. Buehlmaier & Kit Pong Wong, 2020. "Should investors join the index revolution? Evidence from around the world," Journal of Asset Management, Palgrave Macmillan, vol. 21(3), pages 192-218, May.
    17. Meade, N. & Beasley, J.E. & Adcock, C.J., 2021. "Quantitative portfolio selection: Using density forecasting to find consistent portfolios," European Journal of Operational Research, Elsevier, vol. 288(3), pages 1053-1067.
    18. Golosnoy, Vasyl & Gribisch, Bastian & Seifert, Miriam Isabel, 2019. "Exponential smoothing of realized portfolio weights," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 222-237.
    19. Stadtmüller, Immo & Auer, Benjamin R. & Schuhmacher, Frank, 2022. "On the benefits of active stock selection strategies for diversified investors," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 342-354.
    20. Seyoung Park & Eun Ryung Lee & Sungchul Lee & Geonwoo Kim, 2019. "Dantzig Type Optimization Method with Applications to Portfolio Selection," Sustainability, MDPI, vol. 11(11), pages 1-32, June.

    More about this item

    Keywords

    Risk-based portfolios; Most diversified portfolio; Equal risk contribution; Minimum variance portfolio; Sharpe ratio; India;
    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

    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:riibaf:v:34:y:2015:i:c:p:397-411. 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/ribaf .

    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.