MODELING OF STOCK RETURNS OF COMPANIES BELONGING TO DIFFERENT INDUSTRIES AND COUNTRIES

Dmitriy V Kandaurov

Abstract


The article considers a method of modeling of a stock portfolio’s returns, involving separation of industrial and systematic risk at the global and national levels. Various types of risk get distinguished by introduction of industrial and country stock indices into the structure of the pair copula. The proposed method allows combining advantages of the traditional CAPM and pair-copula structures. In the frameworks of solving the problem of a stock portfolio optimization, two methods of formation of the structure made of pair copulas have been tested: the traditional one that ensures the maximum of the sum of Kendall’s correlation ratios between return on assets, and the method of structuring based on industrial and country principle featuring introduction of stock indices into the model. The minimum of risk and the maximum of the Sharpe ratio were considered as optimality criteria of the stock portfolio. The model, structured by the industrial and country principles, showed a greater capital gain for the both indices. The proposed method of accounting the industrial and systematic risk can be useful for professional managers when forming an investment portfolio and improving its returns.

Keywords


risk and return management of stock portfolio; industrial and systematic risk; international diversification.

References


Aas K., Czado C., Frigessi, A., Bakken H. Pair-сopula constructions of multiple dependence. Insurance: Mathematics and Economics, 2009, no. 2(44), pp. 182–198. DOI: 10.1016/j.insmatheco.2007.02.001

Bedford T., Cooke R. M. Probability density decomposition for conditionally dependent random variables modeled by vines. Annals of Mathematics and Artificial Intelligence. – 2001, vol. 32, pp. 245–268.

Bedford T., Cooke R. M. Vines – a new graphical model for dependent random variables. Annals of Statistics, 2002, vol. 30, pp. 1031–1068. DOI: 10.1214/aos/1031689016

Brechmann E.C., Czado C. Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50. Statistics and Risk Modeling, 2013, vol. 30, iss. 4, pp. 307–342. DOI: 10.1524/strm.2013.2002

Christoffersen P., Errunza V., Jacobs K., Langlois H. Is the potential for international diversification disappearing? A dynamic copula approach. Review of financial studies, 2012, vol. 25, no. 12, pp. 3711–3751. DOI: 10.1093/rfs/hhs104

Dissman J., Brechmann E. C., Czado C., Kurowicka D. Selecting and estimating regular vine copulae and application to financial returns. Computational Statistics and Data Analysis, 2013, no. 59, pp. 52–69. DOI: 10.1016/j.csda.2012.08.010

Joe H. Families of m-variate distributions with given margins and m(m-1)/2 bivariate dependence parameters. Institute of Mathematical Statistics Lecture Notes – Monograph Series. Distributions with fixed marginals and related topics. Institute of Mathematical Statistics, Hayward, CA., 1996, pp. 120–141. DOI: 10.1214/lnms/1215452614

Lintner J. The valuation of risky assets and the selection of risky investments in stock portfolios and capital budgets. Review of Economics and Statistics, 1965, vol. 47, pp. 13–37. DOI: 10.2307/1924119

Nelsen R.B. An introduction to copulas. Lecture Notes in Statistics. 2nd ed. Springer-Verlag, New York, 2006.

Patton A. Modelling asymmetric exchange rate dependence. International Economic Review, 2006, vol. 47, iss. 2, pp. 527–556. DOI: 10.1111/j.1468-2354.2006.00387.x

Sharpe W.F. Capital asset prices: a theory of market equilibrium under conditions of risk. Journal of Finance, 1964, vol. 45, pp. 425–442. DOI: 10.1111/j.1540-6261.1964.tb02865.x

Schepsmeier U., Stoeber J., Brechmann E.C., Graeler B., Nagler T., Erhardt T. VineCopula: Statistical Inference of Vine Copulas. R package version 2.1.5. Available at: https://CRAN.R-project.org/ package=VineCopula (accessed 2 October 2018).


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