Validating the impact of accounting disclosures on stock market: A deep neural network approach

2021/06/07 by Prajwal Eachempati, Praveen Ranjan Srivastava, Ajay Kumar +2 · 59 citations
Business, Management and Accounting · Decision Sciences · Economics, Econometrics and Finance · #Accounting #Artificial intelligence #Artificial neural network #Asset (computer security) #Auditing, Earnings Management, Governance #Business #Computer science #Construct (python library) #Deep learning #Econometrics #Economics #Financial Markets and Investment Strategies #Stock Market Forecasting Methods #Stock market #Tone (literature)

paper · open access · doi:10.1016/j.techfore.2021.120903

published in Technological Forecasting and Social Change 170, 120903 (Elsevier BV)

openalex publication_date 2021/06/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Citations

• Towards a Positive Theory of the Determination of Accounting Standards.
• A perspective on judgment and choice: Mapping bounded rationality.
• The Hubris Hypothesis of Corporate Takeovers
• The Information Content of Forward‐Looking Statements in Corporate Filings—A Naïve Bayesian Machine Learning Approach
• Measuring Readability in Financial Disclosures
• The Evolving Disclosure Landscape: How Changes in Technology, the Media, and Capital Markets Are Affecting Disclosure
• The Press as a Watchdog for Accounting Fraud
• The Governance Effect of the Media's News Dissemination Role: Evidence from Insider Trading
• The Quality of Accruals and Earnings: The Role of Accrual Estimation Errors
• Large‐Sample Evidence on Firms’ Year‐over‐Year MD&A Modifications
• Evidence on the Information Content of Text in Analyst Reports

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• Incorporating causality in energy consumption forecasting using deep neural networks. [europepmc]