Dividend policy, debt ratio, and stock volatility: An empirical study of the Jordanian industrial sector

  • 47 Views
  • 4 Downloads

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License

Type of the article: Research Article

Abstract
In emerging markets, understanding the dynamics of share price volatility is essential for corporate financial management and investor decision-making. The industrial sector often experiences price movements that may be influenced by companies’ financial policies. This research investigates the impact of dividend policy on share price volatility, with a focus on the moderating role of the debt ratio. The research draws on a balanced panel dataset of 64 Jordanian industrial firms listed on the Amman Stock Exchange during the period 2015–2023.
Using panel regression models, the findings reveal a statistically significant negative association between both dividend yield and payout ratio with share price volatility. Specifically, a 1% increase in dividend yield is associated with a 0.42% reduction in volatility (p < 0.01), while a 1-point increase in the payout ratio reduces volatility by approximately 0.31% (p < 0.05). In addition, the debt ratio significantly moderates these relationships, which reduces the stabilizing impact of dividends in highly leveraged firms. The high interaction term between dividend yield and debt ratio was confirmed by the positive interaction term between dividend yield and debt ratio. These findings highlight the importance of balanced dividend and leverage strategies in reducing stock market risk, which may improve market stability.

Acknowledgment(s)
This research was funded through the annual funding track by the Deanship of Scientific Research, from the vice presidency for graduate studies and scientific research, King Faisal University, Saudi Arabia [Grant No. KFU253003].

view full abstract hide full abstract
    • Table 1. Descriptive statistics
    • Table 2. Pearson correlation coefficients
    • Table 3. Spearman rank correlation
    • Table 4. Regression results – Model 1
    • Table 5. Regression results – Model 2
    • Table 6. Hypotheses testing summary
    • Conceptualization
      Mohammad Fawzi Shubita, Tariq H. Dorgham, Mohammad Ahmad Alqam, Sajead Mowafaq Alshdaifat
    • Data curation
      Mohammad Fawzi Shubita, Tariq H. Dorgham, Mohamed Saad, Mohammad Ahmad Alqam, Dua’a Shubita
    • Investigation
      Mohammad Fawzi Shubita, Sajead Mowafaq Alshdaifat
    • Methodology
      Mohammad Fawzi Shubita, Tariq H. Dorgham
    • Resources
      Mohammad Fawzi Shubita, Mohamed Saad, Mohammad Ahmad Alqam, Dua’a Shubita, Sajead Mowafaq Alshdaifat
    • Supervision
      Mohammad Fawzi Shubita, Tariq H. Dorgham, Dua’a Shubita
    • Writing – original draft
      Mohammad Fawzi Shubita, Mohammad Ahmad Alqam, Dua’a Shubita
    • Writing – review & editing
      Mohammad Fawzi Shubita, Tariq H. Dorgham, Mohamed Saad, Mohammad Ahmad Alqam, Sajead Mowafaq Alshdaifat
    • Project administration
      Mohamed Saad
    • Validation
      Dua’a Shubita
    • Software
      Sajead Mowafaq Alshdaifat