Economic Analysis: Theory and Practice

Building a portfolio based on different risk measures and investor's risk perception

Vol. 16, Iss. 8, AUGUST 2017

Received: 9 June 2017

Received in revised form: 30 June 2017

Accepted: 7 July 2017

Available online: 29 August 2017


JEL Classification: C61, C65, D53, E44, G11

Pages: 1583–1596

Kolyasnikova E.R. Bashkir State University, Ufa, Republic of Bashkortostan, Russian Federation

Importance Investors have individual perception of and attitude to risk when making their decisions. The article offers a model to build a portfolio considering the indicator of its efficiency and investor's attitude to risk. The following measures of risk are taken into account: Value at Risk, semideviation, standard deviation. It is possible to apply the proposed models in practice.
Objectives The aim is to offer a suitable model to an investor on the basis of portfolio performance and investor's attitude to risk.
Methods The study rests on statistical and portfolio analysis, using optimization methods.
Results I offer modifications of the Rubinstein's function, consisting of mathematical expectation and dispersion of return on assets, compare the offered functions with the Rubinstein's function on the basis of performance indicator of created portfolios, which takes into account expected return, value at risk, semideviation and standard deviation of the portfolio return. The findings may be useful for economists, analysts, investors wishing to build an optimal portfolio based on various measures of and attitude to risk.
Conclusions and Relevance The paper suggests a suitable model for an investor and recommends the use a model, which is based on a modified function or a model with the Rubinstein's function, depending on risk aversion. Comparing the models, using the portfolio performance indicator, enables to make recommendations for the portfolio structure.

Keywords: optimal portfolio, standard deviation, semideviation, Value at Risk, VaR


  1. Markowitz H. Portfolio Selection. The Journal of Finance, 1952, vol. 7, no. 1, pp. 77–91. doi: 10.2307/2975974
  2. Liang B., Park H. Risk Measures for Hedge Funds: A Cross-Sectional Approach. European Financial Management, 2007, vol. 13, iss. 2, pp. 333–370. doi: 10.1111/j.1468-036X.2006.00357.x
  3. Artzner P., Delbaen F., Eber J.M., Heath D. Coherent Measures of Risk. Mathematical Finance, 1999, vol. 9, iss. 3, pp. 203–228. doi: 10.1111/1467-9965.00068
  4. Demkin I.V. [Investment risk management using real options]. Problemy analiza riska = Issues of Risk Analysis, 2005, vol. 2, no. 1, pp. 56–71. (In Russ.)
  5. Demkin I.V. [Integrated Innovative Risk Assessment using the Value At Risk Approach]. Problemy analiza riska = Issues of Risk Analysis, 2006, vol. 3, no. 4, pp. 362–378. (In Russ.)
  6. Men'shikov I.S., Shelagin D.A. Rynochnye riski: modeli i metody [Market risks: Models and methods]. Moscow, Vychislitel'nyi tsentr RAN Publ., 2006, 55 p.
  7. Bronshtein E.M., Vainer A.G. [Security portfolio forming on the base of complex index risk measures]. Upravlenie riskom = Risk Management, 2010, no. 1, pp. 52–59. (In Russ.)
  8. Kritskii O.L., Ul'yanova M.K. [Assessment of Multivariate Financial Risks of a Stock Share Portfolio]. Prikladnaya ekonometrika = Applied Econometrics, 2007, vol. 2, no. 4, pp. 3–18. (In Russ.)
  9. Lobanov A.A. [A problem of the method for Value at Risk calculation]. Rynok tsennykh bumag = Securities Market, 2000, no. 21, pp. 54–58. (In Russ.)
  10. Tkachenko T.S. [Using the simulation modeling techniques to evaluate foreign exchange risk]. Region: Ekonomika i Sotsiologiya = Region: Economics and Sociology, 2007, no. 2, pp. 80–89. (In Russ.)
  11. Ufimtsev A.A. [Currency risk measurement under the Value at Risk methodology]. Vestnik Chelyabinskogo gosudarstvennogo universiteta = CSU Bulletin, 2012, no. 8, pp. 137–142. (In Russ.)
  12. Lobanov A., Porokh A. [Analyzing the applicability of different models of VaR calculation in the Russian equity market]. Rynok tsennykh bumag = Securities Market, 2001, no. 2, pp. 65–70. (In Russ.)
  13. Nikonov O.I., Firsov A.A. [Regressive model of an estimation of share risk in commercial bank, based on GARCH process for two time lines]. Vestnik UGTU – UPI. Ser.: Ekonomika i upravlenie = Bulletin of Ural State Technical University. Series Economics and Management, 2007, no. 4, pp. 70–75. (In Russ.)
  14. Kadnikov A.A. [VaR of the portfolio containing tools with a short history of trading]. Vestnik Novosibirskogo gosudarstvennogo universiteta. Ser.: Sotsial'no-ekonomicheskie nauki = Vestnik of Novosibirsk State University. Series: Social and Economics Sciences, 2009, vol. 9, no. 3, pp. 39–52. (In Russ.)
  15. Kir'yanov I.V. [Methodology for non-parametric portfolio formation]. Sibirskaya finansovaya shkola = Siberian Financial School, 2011, no. 2, pp. 78–83. (In Russ.)
  16. Vorob'ev O.Yu., Martynova T.A., Novoselov A.A. [Modified coherent risk measures (for Euclidean norm)]. Vestnik Krasnoyarskogo gosudarstvennogo universiteta. Gumanitarnye nauki = Bulletin of Krasnoyarsk State University. Humanitarian Sciences, 2005, no. 4, pp. 183–188. (In Russ.)
  17. Osechkina T.A. [Investment Portfolio Optimization Using Utility Function]. Nauka i biznes = Science and Business, 2012, no. 10, pp. 97–99. (In Russ.)
  18. Teplova T.V. [Dynamics of risk in financial markets and non-standard models to substantiate the cost of equity]. Finansovyi menedzhment = Financial Management, 2005, no. 6, pp. 45–57. (In Russ.)
  19. Burenin A.N. Upravlenie portfelem tsennykh bumag [Securities portfolio management]. Moscow, Nauchno-tekhnicheskoe obshchestvo im. S.I. Vavilova Publ., 2008, 440 p.
  20. Chetyrkin E.M. Finansovye riski [Financial risks]. Moscow, Delo Publ., 2008, 176 p.

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Vol. 16, Iss. 8
August 2017