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Applicability of Portfolio Theory in Nepali Stock Market

Author

Listed:
  • Sujan Adhikari

    (Kathmandu University School of Management)

  • Pawan Kumar Jha, Ph.D.

    (Kathmandu University School of Management)

Abstract

In the rapidly growing stock market of Nepal, this study tests the applicability of the portfolio creation model and attempts to aware investors about the potential portfolio alternatives they can make to achieve their peculiar risk-return need, through a robust optimization model. A portfolio model using Markowitz mean-variance method is applied to calculate the optimal portfolio and portfolios fitting the investor specific needs, from a sample of 20 Group "A" listed companies on NEPSE. The monthly stock prices between April 2010 and December 2014 of sample companies are used as training data. And, the applicability of the model is tested based on their prices on April 2015. From the analysis it is concluded that such mean-variance optimization is applicable in Nepal. Furthermore, most of the stocks, even from different sectors, are highly correlated to each other illustrating the lack of diversification opportunity at NEPSE. Additionally, the significantly high volatility even at global minimum variance level illustrated the risky nature of business environment in the country. There is an opportunity for high return, but the investor's willingness to gain this is tested through the high magnitude of minimum risk. These findings call for the policy makers’ immediate attention in creating a favorable environment to bring the real sector companies in the public trading realm and enhancing the commodities and derivatives market in the country, thereby helping stimulate the investment environment in Nepal.

Suggested Citation

  • Sujan Adhikari & Pawan Kumar Jha, Ph.D., 2016. "Applicability of Portfolio Theory in Nepali Stock Market," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 28(1), pages 65-92, April.
  • Handle: RePEc:nrb:journl:v:28:y:2016:i:1:p:65
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    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?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    2. repec:dau:papers:123456789/4688 is not listed on IDEAS
    3. John H. Cochrane, 1999. "Portfolio advice of a multifactor world," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 59-78.
    4. Narayan Prasad Paudel, 2002. "Investing in Shares of Commercial Banks in Nepal: An Assessment of Return and Risk Elements," NRB Economic Review, Nepal Rastra Bank, Research Department, vol. 14, pages 1-16, April.
    5. Edwin J. Elton & Martin J. Gruber, 1997. "Modern Portfolio Theory, 1950 to Date," New York University, Leonard N. Stern School Finance Department Working Paper Seires 97-3, New York University, Leonard N. Stern School of Business-.
    6. Elton, Edwin J & Gruber, Martin J, 1974. "Portfolio Theory when Investment Relatives are Lognormally Distributed," Journal of Finance, American Finance Association, vol. 29(4), pages 1265-1273, September.
    7. Bali, Turan G. & Cakici, Nusret, 2008. "Idiosyncratic Volatility and the Cross Section of Expected Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(1), pages 29-58, March.
    8. David Disatnik & Saggi Katz, 2012. "Portfolio Optimization Using a Block Structure for the Covariance Matrix," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 39(5-6), pages 806-843, June.
    9. Elton, Edwin J. & Gruber, Martin J., 1997. "Modern portfolio theory, 1950 to date," Journal of Banking & Finance, Elsevier, vol. 21(11-12), pages 1743-1759, December.
    10. Amy V. Puelz, 2002. "A Stochastic Convergence Model for Portfolio Selection," Operations Research, INFORMS, vol. 50(3), pages 462-476, June.
    11. Fang, Yong & Lai, K.K. & Wang, Shou-Yang, 2006. "Portfolio rebalancing model with transaction costs based on fuzzy decision theory," European Journal of Operational Research, Elsevier, vol. 175(2), pages 879-893, December.
    12. Tze Leung Lai & Haipeng Xing & Zehao Chen, 2011. "Mean--variance portfolio optimization when means and covariances are unknown," Papers 1108.0996, arXiv.org.
    13. 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.
    14. 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.
    15. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    16. Kraus, Alan & Litzenberger, Robert H, 1976. "Skewness Preference and the Valuation of Risk Assets," Journal of Finance, American Finance Association, vol. 31(4), pages 1085-1100, September.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Investment Decisions; Portfolio Choice; Portfolio Optimization; Markowitz Frontier;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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