Financial analysis is an essential element in organizational development because it significantly informs decision making. It is a process whereby financial data is selected, evaluated, and interpreted in relation to other relevant information for purposes of making decisions on matters financial involvement and investment for an entity such as shareholder, supplier, customer, and lender among others. The financial analysis assesses an entity’s performance in the current year in comparison to competitors, or in comparison with the past years with a view to determining trends or the incoherence thereof in order to forecast future performance. Analysis of past performance trends aids in the evaluation of company issues such as credit policies, worker performance, potential investments, and operating efficiency among other issues which are critical for potential investors. This paper explores the quantitative methods and tools utilized in the financial analysis process, their effectiveness, and the future of quantitative research in the field of financial analysis.
Financial analysis process draws its data from a variety of sources. However, the main source of financial data is an organization’s annual report that bears an income statement, cash flow statements, and the balance sheet alongside their respective commentaries. The three documents summarize a company’s financial position. Financial analysis objectively evaluates a company’s performance based on its laid down goals and strategies. In order to carry out this assessment, the organization must, therefore, provide a disclosure of all the required information. However, care should be exercised to identify any potential bias in the received information. In addition to these disclosures, the financial analyst must conduct a hierarchal evaluation starting with the economy and the industry in which the firm operates and then analyze the firm’s performance.
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There are four main tools that are employed in financial analysis, namely financial ratio analysis, common-size analysis, cross-sectional and trend analysis, and industry comparatives (Helfert, 2001). In ratio analysis, the relationship between various financial accounts is assessed to determine a firm’s financial position. Ratios shed light on the company’s financial flexibility, microeconomic relationships, management performance, and potential risks and returns. One advantage of ratios is that users can easily understand them as their expression in form of percentages and multiples effectively minimize the effect created by size differences thus, facilitating comparability across different-sized organizations. However, use of ratio analysis is attached to some limitations. It is important to note here that not all ratios may be relevant to a certain specific analysis project, hence the need for selection of only relevant ratios per a particular assignment. Also, ratios can only be useful and meaningful if comparisons are based on common accounting periods, or two different firms with similar accounting policies (Helfert, 2001). Furthermore, ratios only mark the beginning of the analysis exercise which must be succeeded by interpretation in order to achieve significance. Examples of the commonly used ratio types include profitability ratios, liquidity ratios, market value ratios, and asset and debt management ratios.
The common-size analysis is a tool that facilitates comparison between two different-size companies or comparison to the overall industry means, thereby providing insight for further investigation on the factors causing the differences and the implications thereof. This technique is applicable in the analysis of balance sheet and income statements where balance sheet line items are expressed as percentages of total assets and income statement line items are expressed as a percentage of total sales respectively. For instance, if $43,000 is the net income from a total of $1,000,000 sales, then the common-size income statement will be 4.3 percent. Common-size analysis, therefore, provides information on a company’s profitability, business mix, competitive advantage in the industry, and any changes that might have taken place of the time under analysis (Helfert, 2001).
Trend analysis is a tool that shows ratio trends over a considerably long period enough to be utilized for forecasting purposes. Through trend analysis, sudden changes in ratios can be identified as to mark significant business adjustments that should be incorporated into the analysis. Industry comparatives is a technique that involves benchmarking other organizations within the same industry in order to draw comparisons on financial performance between one company and another. This technique compares the competitive advantage of one company over another, thereby highlighting spot inefficiencies of a company over others within the industry (Helfert, 2001). Graphics have been used as analytical tools because of their easily understood visual characteristics such as the provision of a visual overview of the business trends, financial structure and performance comparisons over time. Also, graphics clearly and concisely conveys conclusions of the analysis. Examples of commonly utilized graphics include pie charts, line graphs, and stacked column graphs among others. All these tools are usually employed for major items because the analysis is aimed at informing important changes.
The Future of Quantitative Research
Quantitative research in financial analysis, and indeed generally across all fields of study, must adopt a meta-analysis approach where traditional tools are bettered through a systematic combination of both quantitative and qualitative review data and information to facilitate easier interpretation and increase usefulness (Card & Casper, 2013). Some of the gaps that need to be fixed through appropriate research include data quality, data retrieval, sampling bias, and interpretation of outcome. Among the interventions is the comparison of meta-analysis results with the theoretical literature reviews and expert opinions in order to highlight the disparities in interpretation and deductions. There is a need for further research and empirical testing of alternative methods to the present statistical methodologies with a view to checking their accuracy and efficacy. In addition, the future efforts should focus at evaluating and refining the quality of the current statistical analysis tools. As a good scientific practice, the future quantitative analysis must limit extrapolation of interpretation and conclusions to the boundaries of the study review (Thacker, 1988). The available information must be optimally used in the synthesis of information, especially in such an era when scientific information is growing exponentially implying an even wider potential for application of findings.
References
Card, N. A., & Casper, D. M. (2013). Meta-analysis and quantitative research synthesis. Oxford Handbooks Online . doi:10.1093/oxfordhb/9780199934898.013.0030
Helfert, E. A. (2001). Financial analysis: Tools and techniques: A guide for managers . Boston, MA: McGraw-Hill.
Thacker, S. B. (1988). Meta-analysis. A quantitative approach to research integration. JAMA: The Journal of the American Medical Association , 259 (11), 1685-1689. doi:10.1001/jama.259.11.1685
