The Financial Condition of Companies: Predicting using Content Analysis of the Board of Directors Reports A sample of Iraqi Companies on the Iraq Stock Exchange

This paper will discuss the predictive accuracy of narrative disclosures in the reports of the Board of Directors on the financial status of the listed companies in the Iraq Stock Exchange. The study is inspired by the weaknesses of traditional early warning models, which mainly use accounting ratios to formulate explanations, but the approach taken is a text-as-data method of deriving quantitative measures about a company based on its stories and assessing the explanatory power of each incrementally. Based on a sample of Iraqi listed firms followed over several years, the study employs content analysis to determine the disclosure tone based on the frequency of positive and negative words in Board reports, and combines them with traditional financial performance measurements in a block of regression models. The empirical data help to conclude strongly that narrative tone is strongly linked to the financial status of companies. Positive disclosure tone is identified to have a positive and statistically significant relationship to financial performance measures with negative disclosure tone having a strong and significant negative relationship with financial performance measures. It is stated that the estimated models have moderately high or high explanatory powers and that they pass important econometric diagnostics, as they lead to believe that narrative variables have a relevance in explaining variation in financial outcomes that cannot be explained solely by traditional accounting ratios. These results confirm theoretical expectations based on signaling and agency theories, whereby board-level narratives signal informative accounts regarding the underlying financial status, the quality of governance and financial judgments. The paper also adds to the accounting and finance literature due to the provision of evidence in an emerging market with a significant degree of information asymmetry and scarce formal data of distress. In this setting, reports of Board of Directors can be discussed as a significant source of information that is not used fully and can provide valuable insight when making decisions. Its practical implications on investors, analysts, and regulators are that timely textual analysis may be included as part of early warning systems and financial risk evaluation systems. In general, the research proves that narrative disclosures are measurable and applicable to improve predicting the corporate financial position, providing a context-dependent extension to the traditional financial distress prediction frameworks applicable to the new market.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-07
DOI
https://doi.org/10.5281/zenodo.18168732
Primary Topic
Auditing, Earnings Management, Governance
Type
article
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article

The Financial Condition of Companies: Predicting using Content Analysis of the Board of Directors Reports A sample of Iraqi Companies on the Iraq Stock Exchange

Mostafa ABD Alhussein Almansoori1*, Basim mohammed merhej2, Ali nadhem abdulameer3
Zenodo (CERN European Organization for Nuclear Research)
Auditing, Earnings Management, Governance
article

The Financial Condition of Companies: Predicting using Content Analysis of the Board of Directors Reports A sample of Iraqi Companies on the Iraq Stock Exchange

Mostafa ABD Alhussein Almansoori1*, Basim mohammed merhej2, Ali nadhem abdulameer3
article en

Abstract

This paper will discuss the predictive accuracy of narrative disclosures in the reports of the Board of Directors on the financial status of the listed companies in the Iraq Stock Exchange. The study is inspired by the weaknesses of traditional early warning models, which mainly use accounting ratios to formulate explanations, but the approach taken is a text-as-data method of deriving quantitative measures about a company based on its stories and assessing the explanatory power of each incrementally. Based on a sample of Iraqi listed firms followed over several years, the study employs content analysis to determine the disclosure tone based on the frequency of positive and negative words in Board reports, and combines them with traditional financial performance measurements in a block of regression models. The empirical data help to conclude strongly that narrative tone is strongly linked to the financial status of companies. Positive disclosure tone is identified to have a positive and statistically significant relationship to financial performance measures with negative disclosure tone having a strong and significant negative relationship with financial performance measures. It is stated that the estimated models have moderately high or high explanatory powers and that they pass important econometric diagnostics, as they lead to believe that narrative variables have a relevance in explaining variation in financial outcomes that cannot be explained solely by traditional accounting ratios. These results confirm theoretical expectations based on signaling and agency theories, whereby board-level narratives signal informative accounts regarding the underlying financial status, the quality of governance and financial judgments. The paper also adds to the accounting and finance literature due to the provision of evidence in an emerging market with a significant degree of information asymmetry and scarce formal data of distress. In this setting, reports of Board of Directors can be discussed as a significant source of information that is not used fully and can provide valuable insight when making decisions. Its practical implications on investors, analysts, and regulators are that timely textual analysis may be included as part of early warning systems and financial risk evaluation systems. In general, the research proves that narrative disclosures are measurable and applicable to improve predicting the corporate financial position, providing a context-dependent extension to the traditional financial distress prediction frameworks applicable to the new market.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 95%
Auditing, Earnings Management, Governance
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