Different methods of ratios in retail

Different methods of ratios in retail

 

Why different companies use different methods to analyze a single ratios for example to analyze gearing ratio?

It is because companies ought to have the upper hand because if they don’t that could cause them problems wherein shares earn dividends but in poor years dividends may be zero: that is, businesses don’t always need to pay any. Thus, long term liabilities are usually in the form of loans and they have to be paid interest; even in bad years the interest has to be paid. Also, equity shareholders have the voting rights at general meetings and can made significant decisions. Then, long term liability holders don’t have any voting rights at general meetings but they have the power to override the wishes of the companies if there are severe problems over their interest or capital repayments. The companies like to see the gearing ratio, the relationship between long term liabilities and capital employed, being in their favour! Let’s look at the Carphone Warehouse’s gearing ratio. In addition, gearing ratio fell to almost zero indicating that the business much prefers equity funding to debt funding. This minimises the interest payment problems and the control problems of having a dangerously high level of long-term debt on the balance sheet.

 

When companies are comparing ratios from various fiscal periods or companies; inquire about the types of accounting policies used. Different accounting methods can result in a wide variety of reported figures. The companies determine whether ratios were calculated before or after adjustments were made to the balance sheet or income statement, such as non-recurring items and inventory or pro forma adjustments. In many cases, these adjustments can significantly affect the ratios and companies carefully examine any departures from industry norms.

An Example

A Company has Equity contributed by Shareholder’s amounting to $ 100,000. The funds borrowed from the Bank amount to $ 50,000 for the purpose of purchase of Plant & Machinery. Gearing Ratio = 50,000 / (50,000 + 100,000) * 100 Gearing Ratio = 33%

Interpretation

In this case 33% of the total funds are contributed by way of borrowings. Thus the proportion of debt to total funds appears to be reasonable. However this ratio needs to be compared with other companies in the industry to judge the reasonableness. In a capital intensive industry Gearing Ratio of 50% or less can be considered reasonable. Capital Gearing Ratio above 50% is considered to be risky, since borrowing funds has a cost attached to it by way of interest. Once funds are borrowed, the principal and interest are required to be paid irrespective of the performance of the business. Thus a high Capital Gearing Ratio leads to high risk.

Debt Equity Ratio

Formula

Debt Equity Ratio = (Total Debt / Total Equity) * 100

Example

A Company has Equity amounting to $ 50,000 and has borrowed funds by way of Long Term Loan amounting to $ 75,000 for funding the construction  of building and purchase of Plant & Machinery. A Short Term Loan of $ 25,000 is taken for funding the Working Capital Requirement. Debt Equity Ratio = (100,000 / 50,000) * 100 Debt Equity Ratio = 200%

 

Interpretation

A Debt Equity Ratio of 200% is considered to be very high. There is heavy dependence on borrowed funds which means more risk. In this case the company will need to perform and have sufficient Operating profits from the first year itself in order to meet the interest cost and repay the first year loan installment. In case the company has struck a deal to start repayment of the loan after a couple of years it would have that time period available for setting up and growth of the business. Within this time period the company would be required to make sufficient Cash Profits in order to repay the loan.

Another example, sources of information for the estimation of the size of the fish stocks and the rate of their exploitation are samples from which the age composition of catches may be determined. However, the age composition in the catches often varies as a result of several factors. Stratification of the sampling is desirable, because it leads to better estimates of the age composition, and the corresponding variances and covariances. The analysis is impeded by the fact that the response is ordered categorical. This paper introduces an easily applicable method to analyze such data. The method combines continuation-ratio logits and the theory for generalized linear mixed models. Continuation-ratio logits are designed for ordered multinomial response and have the feature that the associated log-likelihood splits into separate terms for each category levels. Thus, generalized linear mixed models can be applied separately to each level of the logits. The significance of possible sources of variation is evaluated, and formulae for estimating the proportions of each age group and their variance-covariance matrix are derived.

 

 

Credit:ivythesis.typepad.com