Modeling simple and mixed stock portfolios over different time periods

Articles in Press

Document Type : Original Article

Authors

Fatemeh Kark Abadi ¹

Omid Adeli ²

ُSeyed Abbas Borhani ¹

Mojgan Safa ¹

¹ Department of Accounting, Qom Branch, Islamic Azad University, Qom, Iran

² Department of EcobomicsDepartment of Economics, Faculty of Economic and Administrative Sciences, University of Qom, Qom, Iran/ University of Qom

https://doi.org/10.22067/mfe.2025.95440.1615

Abstract

There are various strategies in the field of portfolio formation. In the present study, simple (momentum and inverse) and combined (quantertum and quantrian) approaches have been used to form stock portfolios. The most important factor in the difference between these two types of portfolios is their holding period and ranking. Accordingly, in the present study, after modeling investment strategies, the change in the returns of these strategies over time was examined. Accordingly, the main goal of the present study is to model simple and mixed stock portfolios in different time periods. The present study is applied. The research period is 1390 to 1401. Data from 171 listed companies were used to estimate the model. Nonlinear Bayesian averaging approaches and panel time-varying parameter models were used to model the four stock return strategies. The results indicate that internal factors (within the company) have a positive impact on all four portfolio formation strategies, and external factors (macro factors) have a negative impact on the return of the portfolio composed of the strategies under study. Based on the results, the Quantrian approach provides higher returns for investors compared to other approaches in terms of average short-term, medium-term, and long-term coefficients. Also, based on the results, the momentum approach has been more profitable in the short term and the Quantrian approach in the medium and long term than other strategies.

Keywords

Momentum

Quantertum

Quantrian

Inverse

Stock Portfolio

Subjects

• Financial econometrics

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