Fundamental Portfolio Construction Based on Semi-Variance

Anna Rutkowska-Ziarko

Department of Quantitative Methods, University of Warmia and Mazury in Olsztyn


Resumen

In models for creating a fundamental portfolio, based on the classical Markowitz model, the variance is usually used as a risk measure. However, equal treatment of negative and positive deviations from the expected rate of return is a slight shortcoming of variance as the risk measure. Markowitz defined semi-variance to measure the negative deviations only. However, finding the fundamental portfolio with minimum semi-variance is not possible with the existing methods.The aim of the article is to propose and verify a method which allows to find a fundamental portfolio with the minimum semi-variance. A synthetic indicator is constructed for each company, describing its economic and financial situation. The method of constructing fundamental portfolios using semi-variance as the risk measure is presented. The differences between the semi-variance fundamental portfolios and variance fundamental portfolios are analysed on example of companies listed on the Warsaw Stock Exchange. 


Palabras clave:

Markowitz model, fundamental portfolio, semi-variance, Mahalanobis distance


Adcock C.J., Shutes K. 2005. An analysis of skewness and skewness persistence in three emerging markets. Emerging Markets Review, 6: 396-418.

Balicki A. 2009. Statystyczna analiza wielowymiarowa i jej zastosowania społeczno- ekonomiczne. Wydawnictwo Uniwersytetu Gdańskiego, Gdańsk.

Basu S. 1977. Investment performance of common stocks In relation to their price-earnings ratios: a test of the efficient market hypothesis. Journal of Finance, 3: 663- 682

Galagedera U.A., Brooks R.D. 2007. Is co-skewness a better measure of risk in the downside than downside beta? Evidence in emerging market data. Journal of Multinational Financial Management, 17: 214-230.

Harlow W.V., Rao R.K.S. 1989. Asset pricing in a generalized mean-lower partial moment framework: theory and evidence. Journal of Financial and Quantitative Analysis, 24: 285-311.

Hellwig Z. 1968. Zastosowanie metody taksonomicznej do typologicznego podziału krajów ze względu na poziom ich rozwoju oraz zasoby i strukturę wykwalifikowanych kadr. Przegląd Statystyczny, 4: 323-326.

Elton E.J., Gruber M.J. 1998. Nowoczesna teoria portfelowa i analiza papierów wartościowych. WIG PRESS.

Łuniewska M. 2005. Evaluation of Selected Methods of Classification for the Warsaw Stock Exchange. International Advances in Economic Research, 11: 469-481.

Mandelbrot B., Fisher A., Calvet L. 1997. A Multifractal Model of Asset Returns. Working Papers-Yale School of Management's Economics Research Network, 1997: 1-33.

Mahalanobis P.C. 1936. On the Generalized Distance in Statistics. Proceedings of the National Institute of Science. India, 12: 49-55.

Markowitz H. 1952. Portfolio selection. Journal of Finance, 7: 77-91.

Markowitz H. 1959. Portfolio selection: efficient diversification of investments. John Wiley and Sons, New York.

Markowitz H. 1991. Portfolio selection: efficient diversification of investments. Blackwell, Malden, Massachusetts.

Post T., van Vliet P. 2006. Downside risk and asset pricing. Journal of Banking and Finance, 30: 823-849.

Rutkowska-Ziarko A, 2005. Metody znajdowania portfela efektywnego dla semiwariancji. Badania operacyjne i decyzyjne, 3-4: 63- 83.

Rutkowska-Ziarko A. 2007. Wykorzystanie wariancji i semiwariancji do budowy portfela akcji przy normalności rozkładów stóp zwrotu. Przegląd Statystyczny, 4: 105-116.

Rutkowska-Ziarko A. 2011. Alternatywna metoda budowy fundamentalnego portfela papierów wartościowych. Taksonomia 18 - Klasyfikacja i analiza danych - teoria i zastosowania: p. 551-559.

Rutkowska-Ziarko A. 2013. Fundamental portfolio construction based on Mahalanobis distance. Studies in Classification. Data Analysis and Knowledge Organization: in press.

Tarczyński W. 2002. Fundamentalny portfel papierów wartościowych. PWE, Warszawa.

Tarczyński W. 1995. O pewnym sposobie wyznaczania składu portfela papierów wartościowych. Przegląd Statystyczny, 1: 91-106.

Walesiak M., Dudek A. 2010. Finding Groups in Ordinal Data: An Examination of Some Clustering Procedures. Studies in Classification. Data Analysis. and Knowledge Organization. Part 2: p. 185-192.

Publicado
2013-06-30

##plugins.themes.libcom.cytowania##

Rutkowska-Ziarko, A. (2013). Fundamental Portfolio Construction Based on Semi-Variance. Olsztyn Economic Journal, 8(2), 151–162. https://doi.org/10.31648/oej.3226

Anna Rutkowska-Ziarko 
Department of Quantitative Methods, University of Warmia and Mazury in Olsztyn



Licencia

An Author declares that his paper has not been published before (under the same or another title, or is a part of another publication) and does not infringe copyrights of other persons**. At the same time, the Author transfers to the Publisher the exclusive right to publish and to circulate this work in print in the form of a non-serial journal publication and in a form of an electronic publication.

Author's statement

The journal is available on Creative Common license CC-BY-NC-ND