Khan Saifullah, Shoaib Adnan, Aftab Rehan, Yasir Muhammad, Saeed Muhammad Bilal
FAST School of Management, FAST-National University of Computer and Emerging Sciences, Islamabad, Pakistan.
Greater Manchester Business School, University of Greater Manchester, Islamabad, Pakistan.
PLoS One. 2025 Jul 14;20(7):e0325917. doi: 10.1371/journal.pone.0325917. eCollection 2025.
The primary objective of this study is to empirically evaluate the role of various levels of financial friction in explaining stock returns through different asset pricing models. This study enhances asset pricing model estimates by incorporating diverse levels of financial friction by introducing a novel least minus more frictional asset pricing factor specifically constructed for emerging economies. The empirical analysis is conducted using data from a sample including five countries: China, India, Pakistan, Bangladesh, and Sri Lanka. Monthly data from 735 listed manufacturing firms is used to estimate stock returns from 2009 to 2024. These models are rigorously tested for optimal estimation using panel data models. The findings indicated that different levels of financial friction collectively exert inverse effects on stock returns. Macroeconomic and microeconomics frictions are found to be more pronounced in Pakistan compared to other countries, while financial market frictions are more acute in India, and firm-level frictions are most significant in China. The results further reveal that stock returns are overestimated in conventional asset pricing models. Incorporating different levels of financial frictions into these models substantially reduced the abnormal returns. This study has profound implications at macroeconomic, microeconomics, financial market, emerging the economies that are. Managers can leverage these insights to formulate superior strategies aimed at enhancing profitability, fostering robust business-to-business relationships, and minimizing costs across various levels. The findings enable firms to preemptively optimize their operations within the context of prevailing financial frictions.
本研究的主要目的是通过不同的资产定价模型，实证评估不同程度的金融摩擦在解释股票回报方面的作用。本研究通过引入专门为新兴经济体构建的新颖的最小减更多摩擦资产定价因子，纳入不同程度的金融摩擦，从而增强了资产定价模型的估计。实证分析使用了来自中国、印度、巴基斯坦、孟加拉国和斯里兰卡五个国家的样本数据。使用735家上市制造企业2009年至2024年的月度数据来估计股票回报。这些模型使用面板数据模型进行了严格的最优估计测试。研究结果表明，不同程度的金融摩擦共同对股票回报产生反向影响。与其他国家相比，宏观经济和微观经济摩擦在巴基斯坦更为明显，而金融市场摩擦在印度更为严重，企业层面的摩擦在中国最为显著。结果还表明，传统资产定价模型高估了股票回报。将不同程度的金融摩擦纳入这些模型大大降低了异常回报。本研究在宏观经济、微观经济、金融市场以及新兴经济体方面具有深远意义。管理者可以利用这些见解制定卓越战略，以提高盈利能力、促进稳固的企业对企业关系并在各个层面最小化成本。这些发现使企业能够在当前金融摩擦的背景下预先优化其运营。
