The Predictive Capability Of Aggregate Discretionary Accounting Accruals In Damascus Exchange Market

Authors

  • Fadi Jamaan

Abstract

This research aims to study the predictive capability of Aggregate Discretionary Accounting Accruals of the listed companies in Damascus Exchange Market. to achieve that objective the researcher collect financial data for (12) listed companies. The Pearson Correlation Coefficient and simple linear regression Analysis were used to tests the hypotheses and reach the results.

The research conclude that the Aggregate Discretionary Accounting Accruals has predictive capability. This capability is high in predicting future earnings, as the Aggregate Discretionary Accounting Accruals explain 67% of earnings changes. While this capability decreases when predicting cash flows and stock market returns. As the Aggregate Discretionary Accounting Accruals explain 40% of cash flows changes, and explain 36% of stock market returns changes.

 

هدف هذا البحث إلى دراسة القدرة التنبؤية للمستحقات المحاسبية الاختيارية الإجمالية في الشركات المدرجة في سوق دمشق للأوراق المالية. لتحقيق ذلك الهدف قام الباحث بجمع بيانات مالية ل ( 12 ) شركة مدرجة في السوق، واستخدم معامل الارتباط بيرسون وتحليل الانحدار الخطي البسيط لاختبار الفرضيات والتوصل إلى النتائج.

أظهرت نتائج البحث أن المستحقات المحاسبية الاختيارية الإجمالية تمتلك قدرة تنبؤية، وهذه القدرة تكون كبيرة عندما يتعلق الأمر بالتنبؤ بالأرباح المستقبلية، حيث إنها تفسر ما نسبته  67% من تغيرات الأرباح، بينما تنخفض هذه القدرة عند التنبؤ بالتدفقات النقدية والعوائد السوقية للأسهم  حيث إن المستحقات المحاسبية الاختيارية الإجمالية تفسر ما نسبته 40% من تغيرات التدفقات النقدية، و تفسر ما نسبته 36% من تغيرات العوائد السوقية للأسهم.

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Published

2019-12-23

How to Cite

1.
Jamaan F. The Predictive Capability Of Aggregate Discretionary Accounting Accruals In Damascus Exchange Market. Tuj-econ [Internet]. 2019Dec.23 [cited 2024Nov.25];41(6). Available from: https://journal.tishreen.edu.sy/index.php/econlaw/article/view/9298

Issue

Vol. 41 No. 6 (2019): ECONOMIC AND LEGAL SCIENCES

Section

Articles

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