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Information Journal Paper

Title

Analysis of The Relationship Between Dupont Ratio and Dividend Policy (Tobit and Logit Regression Analysis Approach)

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Abstract

 Purpose: The purpose of this paper is to investigate and analyze the information content of DuPont ratios in relation to corporate dividend policy and also seek to answer the question of whether the components of DuPont ratio are significantly related to management decisions in dividend? Methodology: To achieve the answer to the above question, 84 companies in the capital market of Tehran were selected as statistical samples. The data collected in a 10-year period between 2010 and 2019 have been considered and the hypothesis test has been performed by considering the dependent variable of dividend in different forms through Tobit and logit regression analysis. Findings: The results show that the net return on assets (RONA) and its components, ie Asset turnover (ATO) and Profit margin (PM), in relation to dividend policy in all models except the model of one-year-ahead change in dividend had informational content. Originality/Value: This study showed that managers and analysts could analyze how dividend decisions are made through information content obtained through DuPont ratios.

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    APA: Copy

    Nozohoor, Neda, & KAVIANI, MEYSAM. (2020). Analysis of The Relationship Between Dupont Ratio and Dividend Policy (Tobit and Logit Regression Analysis Approach). INNOVATION MANAGEMENT AND OPERATIONAL STRATEGIES, 1(2 ), 0-0. SID. https://sid.ir/paper/369366/en

    Vancouver: Copy

    Nozohoor Neda, KAVIANI MEYSAM. Analysis of The Relationship Between Dupont Ratio and Dividend Policy (Tobit and Logit Regression Analysis Approach). INNOVATION MANAGEMENT AND OPERATIONAL STRATEGIES[Internet]. 2020;1(2 ):0-0. Available from: https://sid.ir/paper/369366/en

    IEEE: Copy

    Neda Nozohoor, and MEYSAM KAVIANI, “Analysis of The Relationship Between Dupont Ratio and Dividend Policy (Tobit and Logit Regression Analysis Approach),” INNOVATION MANAGEMENT AND OPERATIONAL STRATEGIES, vol. 1, no. 2 , pp. 0–0, 2020, [Online]. Available: https://sid.ir/paper/369366/en

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