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  • March 03, 2025 18:44 Category Risk Management ID: 6e653629-9dc... Edition

    Assessing The Predictive Influence Of Financial Statement Analysis On Investments In Financial Assets Among Nigerian Deposit Money Banks

  • 32 days ago on Monday at 18:44

    Submitted By: Oluwadamilola Esan

    Author(s): Arowolo Isiaka O. Adeyemo Kabiru A.

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    Risk Management


    For investors, Nigeria's deposit money banks are essential, and the choices they make are as significant as their financial results. Banks want to improve their financial standing in order to draw in investors, while investors want accurate financial data in order to make wise choices. However, cases of manipulation have raised doubts about the accuracy of financial reporting. Although following International Financial Reporting Standards (IFRS) allows businesses more flexibility, it also opens the door for unethical behavior. Therefore, this research looked the predictive influence of financial statement analysis on investments in financial assets in Nigerian banks in order to remedy this problem. The study, which utilized an ex-post facto research approach, only looked at 13 of Nigeria's 40 banks. During the 14-year period from 2009 to 2022, the chosen data was taken from the financial statements of certain institutions. Panel OLS was used to test the study hypotheses. The findings indicate that Return on Capital Employed (ROCE) has a positive, albeit statistically insignificant, effect on FA (β₁ = -0.7786664, p = 0.344 > 0.05). Conversely, the Cash Reserve Ratio (CRR) exhibits a negative and statistically significant effect on FA (β₂ = 0.0016056***, p = 0.002 < 0.05). Similarly, the Debt-to-Asset Ratio (DAR) has a negative but statistically insignificant effect on FA (β₃ = -0.3709654, p = 0.176 > 0.05), indicating that leverage is not a dominant factor in FA decisions. The Loan-to-Deposit Ratio (LDR) shows a positive but insignificant relationship (β₄ = 0.0037043, p = 0.086 > 0.05), suggesting that while lending activities may influence FA, the effect is not strong enough individually. Collectively, however, the model demonstrates a significant combined effect (prob = 0.0002 < 0.05), highlighting the importance of a holistic approach. This underscores that while individual metrics may have limited standalone influence, their aggregate impact is crucial in shaping