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High-Dividend Portfolios with Filters on the Financial Performance and an Optimization of Assets Weights in a Portfolio

Author

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  • Dubova Ekaterina

    (Department of Finance, Faculty of Economic Sciences, National Research University Higher School of Economics (HSE), Russian Federation)

  • Volodin Sergey

    (Department of Finance, Faculty of Economic Sciences, National Research University Higher School of Economics (HSE), Russian Federation)

  • Borenko Irina

    (Department of Finance, Faculty of Economic Sciences, National Research University Higher School of Economics (HSE), Russian Federation)

Abstract

This paper is dedicated to the investigation of the strategies related to the high-dividend portfolio investment. The aim of this research is to increase the high-dividend portfolio efficiency by adding some filters and optimization weights of the assets in the portfolio. In order to achieve this goal, the authors complement the classical version of the «Dogs of the Dow» strategy with financial indicators ROA and P/E with equal and optimized weights of the assets in each portfolio. Two additional parameters are also used in the process of testing: the number of stocks and the month of the annual portfolio rebalancing. Thus, the obtained models have high-quality advantages in comparison with the traditional concept of high-dividend investing, eliminating its inherent disadvantages and providing higher rates of return.

Suggested Citation

  • Dubova Ekaterina & Volodin Sergey & Borenko Irina, 2018. "High-Dividend Portfolios with Filters on the Financial Performance and an Optimization of Assets Weights in a Portfolio," Scientific Annals of Economics and Business, Sciendo, vol. 65(3), pages 347-363, September.
  • Handle: RePEc:vrs:aicuec:v:65:y:2018:i:3:p:347-363:n:1
    DOI: 10.2478/saeb-2018-0015
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    Keywords

    high-dividend models; «Dogs of the Dow»; portfolio investment;
    All these keywords.

    JEL classification:

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

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