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For this blog I will describe a ratio model developed by Robertson in 1983. It is a model that has stood the test of time since the ratios included are those that best measure overall changes in financial health It:
The financial change model (FCM) takes a similar form to Altman’s 1968 model where the total score is found:
FCM = 0.3R1 + 3R2 + 0.6R3 + 0.3R4 + 0.3R5
The model was developed using a systems approach. This required a statement of ‘key elements’ identifiable in failed companies, followed by the development of ratios which have individual meaning and will help to measure each of the elements; finally the provision for feedback (by observing the movements in the scores obtained from the individual ratios) to allow corrective action to be taken if necessary.
The selection of ratios to be included was considered to be the most important factor in the development of the model. Each ratio was selected to reflect the elements that cause changes in a company’s financial health. An explanation of each of the ratios is given below.
This is a measure of trading stability. It highlights the important relationship between assets and revenues. When a company increases its asset base, it is looking for a corresponding increase in revenues. Companies experiencing trading difficulties are unable to maintain a given level for this ratio. Deterioration indicates a fall in the revenue generated from the asset base. If this ratio is maintained it can produce a stabilising effect even for a company that has problems with costs and/or borrowings.
Profit is taken after interest expense but before tax, because failing companies borrow more and suffer increases in interest payments in the years leading to failure. Total assets exclude intangibles and are used as the base because they are not influenced by financing policies and tend to remain constant or increase. Failing companies tend to show a decline in profits in the years leading to failure, often turning into a loss. The deterioration in profit is sufficient to cause this ratio to fall. However, many companies are involved in rapid expansion and this, if present, could cause a further decline in the ratio.
This is an extension of the net working capital ratio, and requires that long term debt is also deducted from current assets. It measures a company’s ability to repay its current debt without liquidating non-current assets. When compared over a number of years, failing companies show a marked deterioration in this ratio due to the current assets falling while total debt remains constant or even increases.
This is a gearing ratio. A low ratio indicates a high proportion of debt which means high gearing with associated high risk. Failing companies experience a drop in equity through a combination of losses in operations and reorganisation/extraordinary costs, while at the same time borrowings tend to increase. This can turn a healthy balance in favour of equity into a negative balance where borrowings exceed equity. Should a company not borrow but instead obtain additional funds from shareholders, then this will have a stabilising effect and reduce the risk of moving toward high gearing and associated interest payments. It will also help to reduce borrowings and improve liquidity ratios.
This ratio tests changes in immediate liquidity. After deducting bank borrowings from liquid assets it is then possible to measure the immediate cover for trade payables. Increasing bank borrowings incurs additional financing costs for current and future periods and might require the company to agree to a fixed and/or floating charge over its assets.
The weights used were selected to adjust the natural values obtained from certain ratios. For example, the ratio of profit before tax divided by total assets could only, at best, produce a natural score of 0.20 (equivalent to a 20% return on total assets) while a liquidity ratio or a gearing ratio could easily produce a natural score of 1.00 or more. In this case the weights allow the profit ratio to be increased and/or the liquidity or gearing ratios to be reduced. Weights can also be used to increase the effect of one ratio and/or reduce the effect of another.
Each ratio should contribute equally to the overall score and by a series of simple arithmetic calculations a set of weights applicable to a group of companies (or even a single company) was arrived at. The resulting weights should be easy to use and experiments were carried out by changing the weights (for example doubling and halving a ratio weight). This showed, contrary to expectations, that changes in individual ratio weights did not significantly affect the total score when comparing a company year–on–year.
In traditional ratio analysis, the same ratios are used across ‘industries’ with ratio values being interpreted by observing the movements from previous periods or from an industry average. Given that the model was developed for use across ‘industries’, it is appropriate to use similar interpretation, i.e. observing the movements in the total (and individual) scores.
In testing the model it was found that, when the total score fell by approximately 40 percent or more in any year, substantial changes had taken place in the financial health of a company. Immediate steps should be taken to identify the reasons for the change and take remedial action. If the score falls by approximately 40 percent or more for a second year running, the company is unlikely to survive, unless drastic action is taken to stop the decline and restore financial health.
In practice, the model should be used to identify all movements in the total score; further checks should then be carried out on the individual ratios contained in the model in order that action be taken to correct the situation.