Is the residual income metric of a relevant value? evidence from Saudi Arabia
Salah Ahmed Oraby ()
Edelweiss Applied Science and Technology, 2025, vol. 9, issue 6, 332-344
Abstract:
The study aimed to investigate the value relevance of the residual income metric using Ohlson’s valuation model [1] as the study applied to 10 Saudi banks registered on the Saudi Stock Exchange (TASI). The study employed the panel data method and least squares regression models to test the study’s hypotheses and the Sharpe model to calculate the cost of capital. The results of the regression models that captured the individual value relevance of the residual income metric showed that the residual income had neither value relevance with the stock price, i.e., the price model, nor value relevance with the net annual returns on shares. I.e., Returns model. The results of the regression models, which aim to capture the collective and interactive value relevance, were obtained by adding the residual income metric to the earnings per share and the book value per share in Ohlson [1] model. The analysis revealed that the residual income metric exhibited value relevance in both the price and returns models. The study results are helpful to several stakeholders, including accounting standards setters and regulators of the capital market, as they indicate the importance of the residual income metric, which complements other accounting metrics, such as earnings per share and book value per share.
Keywords: Beta; Book value per share; Cost of capital; Earnings per share; Market risk. (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
https://learning-gate.com/index.php/2576-8484/article/view/7807/2668 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ajp:edwast:v:9:y:2025:i:6:p:332-344:id:7807
Access Statistics for this article
More articles in Edelweiss Applied Science and Technology from Learning Gate
Bibliographic data for series maintained by Melissa Fernandes ().