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Does Marginal VaR Lead to Improved Performance of Managed Portfolios: A Study of S&P BSE 100 and S&P BSE 200

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  • Shrey Jain

    (Indian Institute of Technology Guwahati)

  • Siddhartha P. Chakrabarty

    (Indian Institute of Technology Guwahati)

Abstract

In order to improve upon the performance of a managed portfolio, we propose the use of Marginal Value-at-Risk (MVaR) to ascertain the desirability of assets for inclusion in the managed portfolio, prior to obtaining the optimal managed portfolio. In particular, this is applied on a larger index which comprises of a greater number of assets than a benchmark index and the larger index includes all the assets from the benchmark index. The resulting MVaR index includes exactly the same number of assets as the benchmark index. An empirical study with S&P BSE 100 as the benchmark index, with the MVaR index being derived from S&P BSE 200, with five different optimization problems shows outperformance by the MVaR portfolio over the benchmark portfolio. This highlights the advantage of the inclusion of MVaR resulting in improved performance of the managed portfolio.

Suggested Citation

  • Shrey Jain & Siddhartha P. Chakrabarty, 2020. "Does Marginal VaR Lead to Improved Performance of Managed Portfolios: A Study of S&P BSE 100 and S&P BSE 200," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(2), pages 291-323, June.
  • Handle: RePEc:kap:apfinm:v:27:y:2020:i:2:d:10.1007_s10690-019-09294-0
    DOI: 10.1007/s10690-019-09294-0
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    References listed on IDEAS

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    1. Thomas J. Linsmeier & Neil D. Pearson, 1996. "Risk Measurement: An Introduction to Value at Risk," Finance 9609004, University Library of Munich, Germany.
    2. Winfried G. Hallerbach, 1999. "Decomposing Portfolio Value-at-Risk: A General Analysis," Tinbergen Institute Discussion Papers 99-034/2, Tinbergen Institute.
    3. Xiaoqiang Cai & Kok-Lay Teo & Xiaoqi Yang & Xun Yu Zhou, 2000. "Portfolio Optimization Under a Minimax Rule," Management Science, INFORMS, vol. 46(7), pages 957-972, July.
    4. Wojtek Michalowski & Włodzimierz Ogryczak, 2001. "Extending the MAD portfolio optimization model to incorporate downside risk aversion," Naval Research Logistics (NRL), John Wiley & Sons, vol. 48(3), pages 185-200, April.
    5. Hiroshi Konno & Hiroaki Yamazaki, 1991. "Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market," Management Science, INFORMS, vol. 37(5), pages 519-531, May.
    6. Johannes Leitner, 2005. "A Short Note On Second‐Order Stochastic Dominance Preserving Coherent Risk Measures," Mathematical Finance, Wiley Blackwell, vol. 15(4), pages 649-651, October.
    7. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    8. Gotoh, Jun-ya & Takano, Yuichi, 2007. "Newsvendor solutions via conditional value-at-risk minimization," European Journal of Operational Research, Elsevier, vol. 179(1), pages 80-96, May.
    9. Dentcheva, Darinka & Ruszczynski, Andrzej, 2006. "Portfolio optimization with stochastic dominance constraints," Journal of Banking & Finance, Elsevier, vol. 30(2), pages 433-451, February.
    10. Ogryczak, Wlodzimierz & Ruszczynski, Andrzej, 1999. "From stochastic dominance to mean-risk models: Semideviations as risk measures," European Journal of Operational Research, Elsevier, vol. 116(1), pages 33-50, July.
    11. K.L. Teo & X.Q. Yang, 2001. "Portfolio Selection Problem with Minimax Type Risk Function," Annals of Operations Research, Springer, vol. 101(1), pages 333-349, January.
    12. Martin R. Young, 1998. "A Minimax Portfolio Selection Rule with Linear Programming Solution," Management Science, INFORMS, vol. 44(5), pages 673-683, May.
    13. Linsmeier, Thomas J. & Pearson, Neil D., 1996. "Risk measurement: an introduction to value at risk," ACE Reports 14796, University of Illinois at Urbana-Champaign, Department of Agricultural and Consumer Economics.
    14. Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2014. "Recent Developments in Robust Portfolios with a Worst-Case Approach," Journal of Optimization Theory and Applications, Springer, vol. 161(1), pages 103-121, April.
    15. Polak, George G. & Rogers, David F. & Sweeney, Dennis J., 2010. "Risk management strategies via minimax portfolio optimization," European Journal of Operational Research, Elsevier, vol. 207(1), pages 409-419, November.
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    Cited by:

    1. Eyden Samunderu & Yvonne T. Murahwa, 2021. "Return Based Risk Measures for Non-Normally Distributed Returns: An Alternative Modelling Approach," JRFM, MDPI, vol. 14(11), pages 1-48, November.

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