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Financial analysis helps assess a company’s financial performance over time and identify the trends in that performance. It can also be used to evaluate a company’s equity securities, assess its financial risk exposures, and perform necessary due diligence before a prospective merger or acquisition.
Several tools and techniques may be used when evaluating a company’s financial status. These tools and techniques can especially be helpful when reviewing a company’s financial data over time (time-series analysis) vis-a-vis the performance of other companies (cross-sectional analysis). These tools and techniques include financial ratios, common-sizing financial statements, currency translations, and chart analysis.
Ratio analysis enables the evaluation of a company’s past performances and the assessment of its current financial position. Besides, it provides insights that can be used to project a company’s future results. Financial ratios offer insights into:
Limitations to ratio analysis include:
Ratios can be calculated from a company’s financial statements or databases like Bloomberg, Compustat, FactSet, or Thomson Reuters. These databases offer access to historical data for trend analysis and enable ratio calculations for periods beyond the company’s fiscal year, like trailing 12 months (TTM) or most recent quarter (MRQ).
Analysts should note that different vendors may use varying formulas for ratios. Obtain the specific formula from the vendor and consider potential adjustments. Database providers exercise judgment when classifying items, impacting computations. Using a consistent data source when comparing companies or assessing historical records is advisable. Verify formula consistency and data classifications from the source.
Financial data collection and ratio calculation can be automated through XBRL, attaching “smart tags” to financial information. An international nonprofit consortium, including the IASB, supports XBRL. Analysts can compare a company to peers in vendor databases or use industry data from sources like the Risk Management Association or Dun & Bradstreet, which typically categorize companies into quartiles based on their ratios, allowing analysts to assess a company’s relative industry standing.
The common-size analysis involves the creation of a ratio between each financial statement item and a base item. This typically translates to total assets (when common-sizing the balance sheet) or total revenue (when common-sizing the income statement).
The vertical common-size analysis highlights the composition of the balance sheet. It helps to answer questions such as what mix of assets the company is using, how it is financing itself, and how its balance sheet composition compares with that of its peers. Finally, the vertical common-size analysis offers reasons behind the differences that may exist among companies in the same industry and environment.
Horizontal common-size analysis can highlight structural changes that have occurred in a company over time. An analysis of past trends (historical analysis) can help to develop future expectations by evaluating whether trends are likely to remain constant or change.
Trend analysis provides valuable information on a company’s historical performance and growth. It can be used as a planning and forecasting tool for management and analysts.
Cross-sectional or relative analysis compares one company’s metrics with the same ones for another. This allows comparisons to be made irrespective of whether the companies are of significantly different sizes and report financial data in different currencies.
Whenever companies whose financial performance is being compared differ significantly regarding size or the currency in which their financial data is reported, a comparison of their net income as reported will not be helpful. Financial ratios and common-size financial statements can remove size as a factor and enable a more feasible comparison. Additionally, in addressing the challenge of data being reported in different currencies:
The reported nominal currency revenue or net income amounts for a company may not highlight significant changes in its performance over time. However, using ratio analysis, charts, or stating financial statement quantities relative to a selected base year value can make these changes more visible and apparent.
Differences in fiscal year ends can pose a challenge to comparability. This can be overcome by using the trailing twelve months of data.
Differences in accounting standards can also limit comparability. However, A financial analyst should seek to identify where these differences lie and their impact on comparability. As best as possible, this impact should be minimized by making adjustments where feasible.
Graphs can be used to facilitate a comparison of the performance and financial structure of a company over time. They can highlight the necessary changes in significant aspects of a company’s operations. Moreover, graphs can provide a visual overview of trends in risks.
Regression analysis helps identify relationships between variables, leading to forecast estimates. It can also facilitate the identification of items or ratios that are moving contrary to their historical statistical relationships.
Question 1
Which of the following is least likely a typical approach to comparing financial data reported in different currencies?
- Comparing financial data using ratios.
- Using trailing twelve months of data for each company being compared.
- Translating all reported currencies into one common currency using the prevailing foreign exchange rates at the relevant period’s end.
Solution
The correct answer is B.
Using trailing twelve months of data is useful when differences exist in the fiscal year ends of the companies being compared. It is not used for comparing companies whose differences lie in the reporting currency used to prepare their financial statements.
Options A and C describe typical approaches to overcome differences in reported currencies.
Question 2
To compare the performance of two companies with different end-of-period dates, an analyst would most likely use:
- Ratio analysis.
- Regression analysis.
- Trailing twelve months analysis.
Solution
The correct answer is C.
It is better to start the comparison by compounding the financial results of each company. The rationale for doing so is to match the data collected on each company with the data collected on the other company (in terms of time of occurrence). In other words, an analyst must first compound the financial data of the trailing twelve months of each company to make sure that he is comparing apples to apples.