Limtations of Ratio Analysis
There are some important limitations of financial ratios that analysts should be conscious of: – Many large firms operate different divisions in different industries. For these companies it is difficult to find a meaningful set of industry-average ratios. – Inflation may have badly distorted a company’s balance sheet. In this case, profits will also be affected. Thus a ratio analysis of one company over time or a comparative analysis of companies of different ages must be interpreted with judgment. Seasonal factors can also distort ratio analysis. Understanding seasonal factors that affect a business can reduce the chance of misinterpretation. For example, a retailer’s inventory may be high in the summer in preparation for the back-to-school season. As a result, the company’s accounts payable will be high and its ROA low. – Different accounting practices can distort comparisons even within the same company (leasing versus buying equipment, LIFO versus FIFO, etc. ). – It is difficult to generalize about whether a ratio is good or not.
A high cash ratio in a historically classified growth company may be interpreted as a good sign, but could also be seen as a sign that the company is no longer a growth company and should command lower valuations. – A company may have some good and some bad ratios, making it difficult to tell if it’s a good or weak company. In general, ratio analysis conducted in a mechanical, unthinking manner is dangerous. On the other hand, if used intelligently, ratio analysis can provide insightful information.
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Financial ratios are not very useful on a stand-alone basis; they must be benchmarked against something. Analysts compare ratios against the following: 1. The Industry norm – This is the most common type of comparison. Analysts will typically look for companies within the same industry and develop an industry average, which they will compare to the company they are evaluating. Ratios per industry are also provided by Bloomberg and the S&P. These are good sources of general industry information. Unfortunately, there are several companies included in an index that can istort certain ratios. If we look at the food and beverage ratio index, it will include companies that make prepared foods and some that are distributors. The ratios in this case would be distorted because one is a capital-intensive business and the other is not. As a result, it is better to use a cross-sectional analysis, i. e. individually select the companies that best fit the company being analyzed. 2. Aggregate economy – It is sometimes important to analyze a company’s ratio over a full economic cycle.
This will help the analyst understand and estimate a company’s performance in changing economic conditions, such as a recession. 3. The company’s past performance – This is a very common analysis. It is similar to a time-series analysis, which looks mostly for trends in ratios. Advantages and Limitations of Ratio Analysis Financial ratio analysis is a useful tool for users of financial statement. It has following advantages: Advantages * It simplifies the financial statements. * It helps in comparing companies of different size with each other. It helps in trend analysis which involves comparing a single company over a period. * It highlights important information in simple form quickly. A user can judge a company by just looking at few numbers instead of reading the whole financial statements. Limitations * Despite usefulness, financial ratio analysis has some disadvantages. Some key demerits of financial ratio analysis are: * Different companies operate in different industries each having different environmental conditions such as regulation, market structure, etc.
Such factors are so significant that a comparison of two companies from different industries might be misleading. * Financial accounting information is affected by estimates and assumptions. Accounting standards allow different accounting policies, which impairs comparability and hence ratio analysis is less useful in such situations. * Ratio analysis explains relationships between past information while users are more concerned about current and future information.