Bibliographic record
Abstract
INTRODUCTIONFinancial ratios play an important role in the analysis of financial statements and accounting research. However, the use of financial ratios comes with its hazards. Both accounting academics and financial statements' users need to understand the problems and limitations in working with financial ratios. The purpose of this paper is to address these issues and to provide guidance on how to mitigate the problems surrounding financial ratios. Both accounting academics and financial statement users will find this study useful in their dealings with financial ratios.The study is organized as follows:1. Uses and benefits of financial ratios;2. Limitations of financial ratios;3. Dealing with the limitations of financial ratios; and4. Conclusion.USES AND BENEFITS OF FINANCIAL RATIOSFinancial ratios play an important role in financial reporting. A ratio expresses the mathematical relationship between one quantity and another, (Kieso et al. 2013, p. 245). A financial ratio consists of a numerator and a denominator, relating two financial amounts. The two financial amounts can be from the balance sheet (e.g. current ratio), or from the income statement (e.g. times interest earned), or from both the balance sheet and the income statement (e.g. return on total assets).Financial ratios help explain financial statements. For example, financial ratios assist in benchmarking a firm's performance with other firms in the same industry. Further, financial ratios help financial statement users in identifying problem areas with a company's operations, liquidity, debt position, or profitability. From this benchmarking and assessment of a firm's performance, financial ratios help in assessing the firm's overall risk (CICA, 1993). Prior research supports the use of financial ratios as a means to predict firms' performance, specifically stock returns and return on assets (e.g., Soliman, 2008; Nissim & Penman, 2001; Fairfield & Yohn, 2001).Financial ratios are frequently used in loan contracts between a firm (borrower) and a financial institution (lender) as a means to limit the firm's activities. A borrower has an incentive to engage in activities that benefit his or her self-interests at the expense of the firm's overall value, resulting in the lender inserting accounting numbers in the debt contract (i.e., debt covenant) to restrict the borrower's value-reducing activities (Watts & Zimmerman, 1986). For example, the loan contract may stipulate that the firm must maintain a current ratio of at least 2:1. In this manner, the firm is encouraged to effectively manage its current assets and current liabilities, for example, by collecting its accounts receivables on a timely basis.For financial statement users, financial ratios not only provide information about where a firm has been, but also provides guidance about where it is headed in the future. For example, negative trends in financial ratios over time could indicate a firm is in decline and provide insights into predicting corporate failure. The Canadian Institute of Chartered Accountants (CICA, 1993) in their Research Report titled Using Ratios and Graphics in Financial Reporting, summarizes these and additional benefits of financial ratio analysis (see Appendix !)*From an academic perspective, financial ratios play an important role in modeling. A variable of interest (dependent variable) is estimated in a linear regression model by key independent variables that are frequently financial ratios. Many bankruptcy prediction models utilize financial ratios (Altman & Hotchkiss, 2006).In summary, financial ratios provide important information about a firm's past performance, predicting a firm's future performance prospects, assessing management's decision-making, risk assessment, and are a critical tool employed in lending agreements to control a firm's activities. In addition, accounting academics use financial ratios in modeling the key variable of interest in their research studies. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.048 | 0.213 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.003 | 0.013 |
| Scholarly communication | 0.017 | 0.028 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.017 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".