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2018 | 19 | 4 | 355-365

Article title

THE PORTFOLIO OF FINANCIAL ASSETS OPTIMIZATION. DIFFERENT APPROACHES TO ASSESS RISK

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EN

Abstracts

EN
Modern research has led to the rejection of the hypothesis of a normal distribution for financial asset returns. Under these conditions, the portfolio variance loses part of its informativity and can not serve as a good risk measure. The central aim of this work is the development and justification of a new technique of portfolio risk measure. We analyzed weekly stock returns of four largest German concerns: Deutsche Telekom, Siemens AG, Bayer AG and BMW. It is shown that asset returns are not normally distributed, but with good precision follow Laplace distribution (double exponential distribution). Using Laplace distribution function, we obtained the analytical expressions for VaR and CVaR risk measures and made calculations of risk measure using these approaches. Using modified Markowitz model the efficient frontiers of portfolios were constructed.

Contributors

  • Institute of Economics and Management, The National University of Water and Environmental Engineering, Rivne, Ukraine

References

  • Alexander G. J., Baptista M. A. (2004) A Comparison of VaR and CVaR Constraints on Portfolio Selection with the Mean-Variance Model. Management Science, 50(9), 1261-1273.
  • Baumol W. J. (1963) An Expected Gain-Confidence Limit Criterion for Portfolio Selection. Management Science, 10, 174-182.
  • Bazylevych V. D., Sheludko V. M., Kovtun N. V. (2011) Securities. Knowledge. Kiev.
  • Bollerslev T. (1990) Modeling the Coherence in Short-Run Nominal Exchange Rates: a Multivariate Generalized ARCH Model. The Review of Economics and Statistics, 72, 498-505.
  • Engle R. F. (1995) ARCH: Selected Readings. Oxford University Press.
  • Hohlov V. Yu. (2012) VaR and the Problem of ""Large Tails"" of the Profitability Distribution. Risk Management in a Credit Institution, 2, 35-49.
  • Lapach S. N., Chubenko A. V., Babych P. N. (2002) Statistics in Science and Business. Morion, Kiev.
  • Markowitz H. (1991) Foundations of Portfolio Theory. Journal of Finance, 7, 469-477.
  • Markowitz H. M. (1952) Portfolio Selection. Journal of Finance, 7(1), 77-91.
  • Pflug G. Ch. (2000) Some Remarks on the Value-at-Risk and Conditional Value-at-Risk. [in:] Uryasev S. (Ed.) Probabilistic Constrained Optimization: Methodology and Applications, Kluwer, 272-281.
  • Vitlinskyy V. V. (1996) Analysis, Evaluation and Modeling of Economic Risk. Demiur, Kiev.
  • Sharpe W. F., Alexander G. J., Bailey J. V. (1995) Investments. Prentice Hall.
  • Zabolotskyy T. (2016) Estimation of Confidence Level for Value-at-Risk: Statistical Analysis. Economic Annals – XXI, 158(3-4(2)), 83-87.
  • Zabolotskyy T. (2016) Modeling in the Management of the Portfolio of Financial Assets. Monograph, Lviv.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.desklight-2eddb785-3518-4699-b029-64554b607c38
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