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

Dubova Ekaterina (), Volodin Sergey () and Borenko Irina ()
Additional contact information
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

Scientific Annals of Economics and Business, 2018, vol. 65, issue 3, 347-363

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.

Keywords: high-dividend models; «Dogs of the Dow»; portfolio investment (search for similar items in EconPapers)
JEL-codes: G11 (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/saeb-2018-0015 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:aicuec:v:65:y:2018:i:3:p:347-363:n:1

DOI: 10.2478/saeb-2018-0015

Access Statistics for this article

Scientific Annals of Economics and Business is currently edited by Ovidiu Stoica

More articles in Scientific Annals of Economics and Business from Sciendo
Bibliographic data for series maintained by Peter Golla ().