<URL:http://lipas.uwasa.fi/~ts/sera/sera.html>
|
|
<URL:http://lipas.uwasa.fi/~ts/sera/sera.html> |
|
This paper is reproduced in the electronic format with permission of the Editor of the Publications Board of the University of Vaasa, Finland. Copyright © 1990 by the University of Vaasa and the authors.
CONTENTS:
APPENDIX A: The Ratios
APPENDIX B: Varimax-rotated Factor Pattern for the Averages of the
Ratios 1974-1984
APPENDIX C: Varimax-rotated Factor Pattern for the Averages of the
Ratios 1974-1978
APPENDIX D: Varimax-rotated Factor Pattern for the Averages of the
Ratios 1979-1984
APPENDIX E: Transformation Matrix 1974-78 to 1979-84 (L12)
APPENDIX F: Transformation Matrix Relationships
APPENDIX G: The Firms Included in the Sample
We acknowledge the skilful research assistance in processing the statistical analyses by Janne Lehtinen and Leena Lomakka.
Please use the following reference to this publication: Salmi, T., Virtanen, I and Yli-Olli, P. (1990). On the Classification on Financial Ratios. A Factor and transformation analysis of accrual, cash flow, and market-based ratios. Acta Wasaensia, No. 25., University of Vaasa, Finland. Also available from Word Wide Web: <URL:http://www.uwasa.fi/~ts/sera/sera.html>.
Ilkka Virtanen
Professor of Economic Mathematics and Operations Research
Paavo Yli-Olli
Professor of Accounting and Business Finance
KEYWORDS: Financial ratios, financial statement analysis, classification of financial ratios, stability of financial ratios, cash flows, market-based ratios, profitability, operating leverage, defensive interval measure, size and beta, growth, factor analysis, transformation analysis.
Timo Salmi, Ilkka Virtanen and Paavo Yli-Olli (1990). On the Classification on Financial Ratios. A Factor and transformation analysis of accrual, cash flow, and market-based ratios. Acta Wasaensia, No. 25., University of Vaasa, Finland. Also published on the Word Wide Web as http://www.uwasa.fi/~ts/sera/sera.html
Different approaches have been applied on the classification problem of the financial ratios. The first approach could be called a pragmatic or an authoritative approach. In this approach the classifications of financial ratios have largely developed from established business practices and personal views of eminent financial analysts. Many standard text-books present material from this approach. (See e.g. Aho 1981, Bernstein 1989, Brealey & Myers 1984: Ch. 25, Foster 1986, Fridson & Marocco 1986, Kettunen & Mäkinen & Neilimo 1976 and Lev 1974.
The second approach has been more deductive. In this approach the classification of the financial ratios has been based on the technical relationships between the different financial ratios. The "Du Pont triangle" from the beginning of the century is a classic in this respect. (See Horrigan 1968.) The modern papers using this "pyramid" approach include Courtis (1978), Laitinen (1983), and Bayldon & Woods & Zafiris (1984).
The third approach has been inductive, empirical classification of financial ratios using statistical techniques, factor analysis in particular. In this approach, factor analysis is used to reduce a (large) number of financial ratios into a smaller number of mutually exclusive categories covering the various aspect of the firm's activities. (See e.g. Salmi & Dahlstedt & Luoma & Laakkonen 1986 for a brief summary of the objectives of factor analysis in ratio analysis.) Methodologically, this means reducing a large number of measured variables into a smaller number of latent variables, and then giving interpretative names to these latent variables.
Since the paper by Pinches & Mingo & Caruthers (1973) conventional financial ratios have been factorized in many research papers including Pinches & Eubank & Mingo & Caruthers (1975), Laurent (1979), Johnson (1979), Aho (1980), Chen & Shimerda (1981), Cowen & Hoffer (1982), Yli-Olli & Virtanen (1985), and Ezzamel & Brodie & Mar-Molinero (1987), and using a confirmatory test method Kanto & Martikainen (1989).
Using an inductive approach for classifying financial ratios raises the question of the stability of the results between the different studies, and even between different years within the same study. This fact has been pointed out, and tested for, in several of these studies, Pinches & Mingo & Caruthers (1973) included. They concluded a reasonable stability of their results. On the other hand, the results of Polhman & Hollinger (1981) can be interpreted as a caution against drawing generalized conclusions from the Pinches & Mingo & Caruthers (1973) classification. Yli-Olli & Virtanen (1985, 1989, 1990) introduced using transformation analysis to test for the stability between different years, and data-sets from different countries. It is evident from these studies that the stability of the results is an important, and even a critical issue.
Another issue is the coverage of the selected financial ratios. The financial ratios have usually been selected from the traditional, accrual ratios. It has been put forward, e.g. by Artto (1978), that cash flows contain such information about the activities of the firm which is not present in the accrual-based financial statements. Gombola & Ketz (1983), and Yli-Olli (1983) observed that cash flow ratios produce an independent and persistent factor.
Three facts, which will be relevant for our research problem, are evident in the earlier research on classifying financial ratios using factor analysis. First, earlier research has been largely inductive. A hypothesis approach has been conspicuously scanty. Second, market data has not featured in these studies. Third, the methods of selection of the original financial ratios to be factored has strong ad-hoc features.
First, the need for rules and legislation for security trading conduct has been very much in evidence in Finnish public discussions. Second, the volume of trading grew explosively towards the end of the 1980's. Third, and most importantly for our current focus, the amount publicized of security trading and financial statement information has been steadily increasing. This has been paralleled by a growing number of academic Finnish (mostly empirical) research projects in modern finance theory.
As was discussed in the previous section, the formulas and classifications of analyzing the firms' financial statement numbers have become more or less established in financial statement analysis practices, and much research has been done on categorizing financial ratios.
Likewise, the efficiency of the security markets, and the determinants of security prices have been much researched (especially in the framework of the capital asset pricing model CAPM, and arbitrage pricing theory APT). (For CAPM see Sharpe 1963, Sharpe 1964, Lintner 1965, Mossin 1966, Black 1972, Black & Jensen & Scholes 1972, and Foster 1978. For APT see Ross 1976, Roll 1977, Dhrymes & Friend & Gulletin 1984, and Elton & Gruber 1987.) Despite this fact, both the practice, and theory of classifying the numerical security characteristics information is at its infancy.
With the increasing number of numerical indicators on securities (such as price/earnings, efficient yield, betas, etc.) it is important both from the viewpoint of practice and research to establish what the factual informational content of these numerical security characteristics is. What information is overlapping, are there distinct classes of numerical security characteristics, and what are their relationships to firms' financial statement numbers.
The second group of questions concerns the accrual and cash flow ratios. Does the introduction of the market based variables influence the familiar factor patterns? In other words are the earlier results corroborated, or have they been influenced by the limited selection of variables? In addition to the implications on the traditional accrual ratios, we are interested in whether the results on the distinct nature of the cash flow ratios are corroborated.
In tackling our research problem, we shall use a hypothesis approach rather than just observing and reporting the emerging classifications. The statistical methods will be factor analysis, and transformation analysis.
In tackling our research questions special attention must be given to stability, and avoidance of definitional correlation. One of the pitfalls of inductive methods, such as factor analysis, is whether the results are a consequence of a coincidence, and thus unstable, or do they result from true underlying factors, which would mean better stability. Hence we shall test the stability of our factor analysis results with transformation analysis.
Definitional correlation between financial ratios can easily arise if they include, either directly or indirectly, the same components. (E.g. net profit/total assets and net profit/sales are related by definition.) We strive to avoid this pitfall by a judicious selection of the original variables.
Technically, financial ratios can be divided into several, sometimes overlapping categories. A financial ratio is of the form X/Y, where X and Y are figures derived from the financial statements. One way of categorizing the ratios is on the basis of which statements X and Y come from. The most important sources are the income statement, the balance sheet, the funds flow and/or the cash flow statements.
Consider a few examples. The current ratio (current assets / current liabilities) which reflects liquidity, is a typical balance sheet / balance sheet ratio, and thus often considered static (i.e. a stock variable). Profit margin (net income / sales), reflecting profitability, is a typical income statement / income statement ratio, and thus often considered dynamic (i.e. a flow variable). Return on investments (ROI, i.e. net income / total assets) which reflects profitability, is a typical mixed income statement / balance sheet ratio. The examples could be easily extended into ratios involving funds or cash flows.
The information used in financial statement analysis is not limited to ratios nor, for that matter, numerical information. (In security market analysis, especially, it seems that the non-numerical information has a definite role. Nevertheless, we shall only consider quantifiable, numerical information from here on.) In financial statement analysis some non-ratio indicators are frequently used, and important. Examples of such information are total sales, number of employees, market shares, and so on. (For discussions and results on the ratio format and proportionality in financial statement analysis see Whittington 1980, Barnes 1982, Horrigan 1983, Barnes 1983, Barnes 1987, Fieldsend & Longford & McLeay 1987, and Perttunen & Martikainen 1989.)
An extension of the set of financial ratios is to use market based information in the numerator or the denominator. A typical example of such a ratio is the P/E (share price/earnings) ratio, which is much used in security analysis practice.
Taking the idea one step further we come to the case where both the numerator and the denominator are market based. Furthermore, there are important market based indicators which are not calculated as ratios. A security's beta (the systematic risk) is a prime example.
From now on we shall use the term market-based ratio both for the ratios with a market based component, and for the other market based indicators. The term financial ratio will be used for ratios and other similar data derived from financial statements, both with and without the market based element.
In the theory of finance the most common equilibrium model is the Capital Asset Pricing model. One of the basic assumptions of CAPM is that the investors are price takers, and have homogenous expectations about asset returns. The asset returns have a joint normal distribution in the CAPM assumptions. The implication of the normality assumption is that only two parameters, the mean and the variance, are needed to completely describe the distribution. It follows that our first hypothesis will be:
In defining the firm's performance in terms of profitability in the theory of the firm, two different valuations can be used. These are the economist's valuation and the accountant's valuation. The former is based on cash flows while the latter is based on accrual concepts. It can be shown theoretically that the two will be compatible only in the very special case of applying the annuity method of depreciation in the accountant's evaluation of profits. (See e.g. Salmi & Luoma 1981 for a proof, and a discussion.)
Furthermore empirical evidence from factor analysis studies corroborate that cash flow ratios involve information that is uniquely distinct from accrual ratios. (See Gombola & Ketz 1983, and Yli-Olli 1983.) Also the time-series behavior of cash-based accounting figures and accrual-based accounting figures show a fundamentally differing behavior. (See Kinnunen 1988.) These considerations lead to our second and third hypotheses.
Several considerations prompted spanning the years from 1974 to 1984 in particular. The period is long enough to cover a complete business cycle. The oil-crisis had already culminated. The new Finnish accounting act, which influenced financial statement disclosure in a fundamental way, was passed in 1973. The level of security trading has exploded in the Finnish markets since 1984, and a significant number of mergers and acquisitions disrupting the comparability of the cross-sections have taken place since.
In a study applying data-oriented statistical methods such as factor analysis for categorizing ratios, the quality of the results is (along with other considerations) heavily dependent on a balanced choice of the ratios for the data base. Quite often the selections have, more or less, been based on an ad-hoc, stratified collection of a number of frequently used ratios. We shall use a more systematic procedure. The following interrelated criteria form the basis for our selection:
We introduce the three main categories of ratios, that is the accrual ratios, cash flow ratios, and market-based ratios.
As discussed in the previous chapter, we differentiate between the accrual ratios and the cash flow ratios because different principles of economic theory and accounting are involved. And, as stated, the behavior differences of the cash based accounting numbers from the accrual based has been the focus of interest in several studies.
The market-based ratios constitute the third ex-ante main category. This is natural, since containing market information they are distinct from the conventional financial ratios by definition.
Quick ratio is a prevalent indicator of liquidity with a long history of usage. As is well-known, it is defined as the ratio of the current assets less inventories to current liabilities.
Studies categorizing financial ratios often include the current ratio (current assets to current liabilities) in the data basis along with the quick ratio. We will, however, deliberately exclude the current ratio.
As stated in discussing our approach in the Introduction, definitional correlation between the preselected ratios should be avoided. The quick ratio and the current ratio are prime examples of this feature. Their denominators are the same, and their nominators are quite close definitionally. They only differ by the inventories.
It must be granted, of course, that avoiding definitional links altogether is impossible when selecting a proper set for the database for empirically categorizing financial ratios. This arises from the fact that the ratios must effect a wide coverage of the firms' characteristics and the securities' features.
This principle excludes the simultaneous inclusion of the quick ratio and the current ratio, but it does not indicate which of the two ratios is more suitable for our purposes. Our choice of the quick ratio over the current ratio is based on two considerations. First, inventories (which the current ratio includes) are not always truly liquid in nature. Second, many empirical results indicate that the quick ratio tends to be better behaved statistically than the the current ratio. This is revealed both in classification studies (see e.g. Yli-Olli & Virtanen 1985: 52), and in studies dealing with the distributional properties of these ratios (Virtanen & Yli-Olli 1989: 12-13).
The second included ex-ante liquidity ratio is the defensive interval measure. (See Davidson & Sorter & Kalle 1964.) This ratio is defined as the current assets less inventories per average daily expenditures to operations.
While the quick ratio is a balance sheet / balance sheet ratio, the defensive interval measure is a balance sheet / income statement ratio. We feel that, whenever possible and relevant, the ratios should have such differing bases to increase coverage, and to alleviate the definitional dependencies.
Defensive interval measure can be used to illustrate the fact that the ex-ante classifications of financial ratios are more or less arbitrary. Depending on the way it is looked at, the defensive interval measure could as well be deemed ex-ante a profitability measure. The common way of looking at this measure is that it indicates how well the liquid assets cover the expenditures needed to keep the operations running. But looking at it the other way round, profitability is dependent on the expenditures incurred. Comparing the operating expenditures to the capital base (in this the liquid assets) that is needed to create the activity, gives an inverse type of a profitability measure.
We are not claiming here an attempt to logically deduce which category of financial ratios the defensive interval measure best belongs to. On the contrary we put forward that this kind of duality is an important reason for making the empirical classification studies of financial ratios worthwhile endeavors.
The last of the financial ratios in the liquidity ex-ante category is the relative net working assets. If the liquidity ex-ante category were under observation by itself, we would have opted for net working assets to sales instead of net working assets to total assets. As it is, the selections in the other ex-ante categories have to be taken into account. In this case the total liabilities to sales in the capital adequacy ex-ante category is definitionally too close to net working assets per sales.
As to capital adequacy, we have deliberately used this title instead of the more common financial leverage, since the former is less restrictive.
The financial ratios in the capital adequacy ex-ante category are total liabilities to sales, long term debt to equity, and times interest earned.
Denote balance sheet items by b for short, and income statement items by i. The first of the ratios is a b/i concept, the second b/b, and the third an i/i concept. This variety is intended to give an improved coverage.
Profitability is best regarded as earnings generated in relation to the resources invested in a firm's activities. There are two major ways of looking at profitability. The shareholders are per definition interested mainly in the return on their investment. On the other hand, taking a more managerial oriented view, the focus of interest becomes the productivity of the firm's capital resources. These views are well reflected in including as profitability ratios the return after interest and taxes on equity, and the return on total assets. The empirical classification of these financial ratios in the profitability ex-ante category is naturally of particular interest in our study, where the relation to security market based data is at issue.
The third financial ratio in our profitability ex-ante category is the operating margin to sales. It is selected as an i/i ratio to complement the two b/b ratios.
In calculating the turnover ratios the practice varies between giving the turnover as a period or as a rate (these are inverses of each other). In business practice turnover periods may be easier grasp than turnover rates. Turnover periods also have better statistical properties, especially, a smaller variance and other higher moments, than do the turnover rates. (Virtanen & Yli-Olli 1989). Using these two criteria, we have decided between the two alternatives.
We have here called this ex-ante category efficiency rather than turnover ratios, since the former is more generic. Furthermore, the latter terminology refers to a method of calculation rather than to a concept.
We include two financial ratios in this ex-ante category. (See Appendix A.) These are the labor intensiveness (see Salmi & Dahlstedt & Luoma & Laakkonen 1986: 337-338), and the variable costs to fixed costs. The former is an i/b concept, while the latter is an i/i concept.
Labor intensiveness is defined as the personnel expenditures divided by the adjusted real-term fixed assets. Real-term fixed assets are used here rather than the book value because the former better reflects the technology at the firms disposal.
The empirical availability of the ratios has been one of our criteria in the selecting the ratios to be included in this study. Measuring variable costs to fixed costs is not unproblematic in this respect, because variable and fixes costs are not always easily available separately in Finnish financial statement analysis data. On the other hand variable costs to fixed costs is an established concept in measuring operating leverage.
In measuring the operating leverage as the proportion of the variable costs there are alternative definitions. The denominator of this ratio can be selected in several ways. Operative fixed costs alone can be used (as we are doing). The second alternative is using the operative fixed plus variable costs. The figures produced by the second alternative are easier to interpret, but the first alternative produces a better variation. The third alternative would be to include depreciation charges into fixed costs, but this aspect is already covered in our first measure of the operating leverage.
Considering earnings variability rises both principles and technical issues not present in the financial ratios we have presented this far. The financial ratios included so far are (more or less) easily defined and obtained for annual data as befits a cross section study. Riskiness, however, obviously is a longer-term characteristic of the firm. What is more, devising an annual measure of risk would involve unnecessary practical difficulties. And, as is recalled from our discussion at the beginning of Chapter 2, relevance in financial statement analysis practice, as well as availability and unproblematic calculation are among our criteria in selecting the financial ratios. Hence we shall not include earnings variability in our data base.
Even if we omit earnings variability it is useful briefly to outline measuring this aspect of the firm. Obviously, any growth rate would first have to be eliminated lest it cause variability in itself. Furthermore, a model would be needed to counter the fact that, ceteris paribus, fluctuations in later years would be wider simply because of greater volumes caused by growth. (As is well known, in statistics the phenomenon is called heteroscedasticy.) The earnings variability could be measured as the relative variance of the residual around the earnings trend. But, this would mean using a rather involved model for obtaining financial statement analysis information, and in actual practice calculating financial ratios is usually kept quite simple.
If earnings variability were included, earnings would have to be defined for this purpose. Using earnings after interest and taxes would then be the choice. It would mean using a shareholder's point of view rather than a managerial point of view. The latter is already reflected in the operating and financial leverages when considered in terms of riskiness.
Gordon's well-known dividend growth model postulates a link between a firm's cost of capital and security prices. In other words a link between a firm's features and its securities' features. (See Martikainen 1989: 36-39.) This fact, of course, further prompts including growth in our data basis.
We shall use the long-term growth rate of deflated sales as the indicator for growth. The same difficulty of cross sections versus time series applies as in measuring riskiness. Growth could, technically, be easily calculated in terms of annual growth rates. The possibility of mergers and acquisitions in the data make this alternative more unstable than using a longer term growth rate. Recall, however, that the most problematic years after 1984 are not included.
Size is another non-ratio measure which has to be considered in this connection. Granted, there are research results with Finnish data which do not lend clear-cut support for a size effect on the firms financial ratios, but more research on that particular subject is needed. (See e.g. Lehtinen 1989, and Lukkaroinen 1988. Also see Buckley & Dunning & Pearce 1984.) On the other hand, size effects on risk adjusted returns of NYSE stocks have been reported. (See Banz 1981, and Reinganum 1981.) We shall include total assets in proportion to the whole sample as a measure of size.
Size is measured for each firm for each year by dividing the total assets (adjusted for appreciation) by the maximum observed total assets over all the firms and years. Thus the range of the resultant ratios will be between 0 and 1.
Let us review two of the earlier results on factoring financial ratios when cash flow ratios are included in the data. It is important to note in the ensuing discussion that cash flow ratios have often been regarded as profitability ratios.
Gombola & Ketz (1983: 113) concluded in their empirical study that cash flow ratios do load on separate and distinct factors, "when cash flow is measured as cash revenues from operations less cash expenses for operations". On the basis of their results they emphasize the need of including cash flow ratios "in predictive or descriptive studies involving financial ratios".
Yli-Olli (1983) studied the same problem with a special emphasis on observing the stability of cash flow ratio loadings. He concluded that the cash streams (as calculated in Finland) do not load on the same factor as profitability. He also demonstrated applying transformation analysis that the temporal stability of the loading of the cash flow ratios on different factors is very poor. He concluded that the cash flow ratios measure different aspects of the firms' performance at different stages of business cycles.
The first of our cash flow ratios is cash net income (cash margin II) divided by cash from sales. The second of our cash flow ratios is cash operating income (cash margin Ib) divided by total assets. The cash net income is defined as follows. (For more details see Kinnunen 1988, Appendix 4.)
cash from sales
less cash based direct materials
less cash based direct labor
plus other cash based net (non-operating) income
= cash operating income (cash margin Ib)
less cash based interest
less cash based direct taxes
less cash based dividends
= cash net income (cash margin II)
The choice of the two different cash flows again also reflects
the distinction of the ownership and the managerial function. As
will be recalled, a similar aspect was taken up in discussion the
operating leverage ratios.The third of the cash flow ratios takes up a different aspect of the firms activities, that is its investment intensity. It is defined as cash flow to capital investments divided by cash based sales. The reason for including this cash flow ratio is twofold. On one hand we wish to include a cash flow ratio which is not a profitability (ex-ante) type of ratio as are the other two. On the other hand a measure of investment activity is clearly relevant in trying to have a set of ratios that covers well the different aspects of a firms activities.
Capital investments are at the very heart of a firm's success. Major investments are expected to be reflected on the firm's security prices. If the (discounted) after-tax cash flow from a capital investment at the weighted cost of capital is positive, then the firm's security prices are expected to increase, and vice versa. This fact further emphasizes the need of including a ratio involving the capital investment activity of the firm. Here cash basis is particularly relevant, because then the initial investment outlay is directly involved. Accrual basis smooths the capital investment into a long series of depreciation.
In this light it is surprising that capital investment intensity ratios have not always been included in studies factoring financial ratios. There are, of course, exceptions. The domestic study presented in Aho (1981: Ch. 7) is one example.
The fourth of the cash flow ratios is a cash-based indicator of a firms operating leverage. Cash outflow to materials & supplies and wages & salaries divided by cash from sales indicate the (cash based) structure of the firms expenses. In accounting theory there has been discussion about the order in which expenditures should be deducted from revenues. It has been put forward (Saario 1949, see Salmi 1978 for a review in English) that there is a strict priority order of costs based on the divisibility of the costs. Direct labor has the highest priority of all costs, and direct materials have the second highest priority. This priority order of costs is present in the fourth cash flow ratio, which thus well reflects the operating operating leverage (production technology) of the firm.
The fifth cash flow ratio measures the ability of the firm to meet its financial obligations arising from its debt financing by financial institutions and investors. Cash net income (cash margin II) divided by interest bearing debt indicates the burden caused by the debt financing taken by the firm. Thus this cash flow ratio reflects the financial risk of the firm.
The sixth of the cash flow ratios also measures the firm's ability to meet its financial obligations, but from a slightly different angle. Cash outflow to interest payments divided by cash operating income (cash margin Ib) reflects the firms financial risk based on the interest payments the firm must make in relation to the cash flows the firm is able to generate.
Technically we subdivide the market-based ratios ex ante into three categories. The first category includes ratios which are directly based on financial statements. The second category includes ratios where the numerator comes from financial statements, and the denominator from market based information, or vice versa. The third category includes market based indicators.
In selecting the market-based ratios their prevalence in security analysis practice was primary. (Naturally all the criteria presented at the beginning of Chapter 2 still apply.) For this purpose several foreign and domestic publications directed at the investing public were scanned for eligible frequently used ratios.
Dividend payout ratio is considered an indicator of the firm's dividend policy. Theoretically, the question of the dividend payout policy, and its effect (or irrelevance) on the value of the firm is one of the classical topics of finance. By including this variable we do not directly take a stand about the influence of the payout policy on the value of the firm. We include it to see its empirical behavior in relation to the other ratios of our study.
Nevertheless, there are arguments for the relevance of the dividend payout decision which should be revisited here. (The generic interpretation is that a relevance of dividend decisions reflects market imperfections.) Most importantly, the signaling approach view should be taken up here. According to this important view, changes in the dividends are signals to investors from the management indicating a long-term shift in the firms profitability and/or financial position. Another important view on the relevance of dividend policy is the so-called clientele effect. This effect is based on the idea that firms with different payout policies attract different kind of investors because of the difference in the tax treatment of personal capital gains and dividends. For an interesting survey about management views on the tenets of finance discipline on these issues see Baker & Farrelly & Edelman (1985).
Technically, calculating the dividend payout ratio can be problematic in firms with unprofitable years. This is because dividends my be distributed even in years with negative earnings (i.e. losses). The statutory limit on dividends is set (in Finland) by retained earnings, not the periods earnings alone. Thus the data must be checked for extreme or even negative values.
Dividend yield percentage at the year end prices is readily available for Finnish data.
The P/E ratio, that is price per earnings ratio, is perhaps the most prevalent market-based ratio. Interpreting what this ratio factually means is, however, somewhat ambiguous. Often it is described in the well-known terms of P/E = (D/E)/(k-g), that is payout ratio capitalized by return and growth. This definition has been used to interpret e.g. high P/E ratios. According to this view a high P/E ratio may indicate high dividend growth expectations from the part of the investors, or low risk so that a low return is considered sufficient, and so on.
There is also another way of looking at the P/E ratio. Consider its inverse E/P. Now it is earnings relative to capital invested (capital in the form of price prince per share). Looked at this way, the P/E ratio resembles profitability ratios.
We choose to use the E/P format, since this way round the problem caused by potential near-zero earnings is avoided.
The third ratio in this ex ante category is the market to book ratio. It is calculated as the stock price per share divided by the book values per share.
The first of these ratios is the return on the security. The return on a security has two main components, that is the capital gain (or loss) and dividends. As discussed earlier, there has been much debate whether these two components are valued differently by the investors or not. Including the return on the security and dividend yield as separate variable in our data base covers the potential difference.
Security beta is the second variable in this ex ante category. The concept of beta is central in capital market theory, and more specifically in the capital asset pricing model (CAPM). Expressing the riskiness of a security in terms of its beta can be interpreted as follows. The investor is not interested in the properties of a single security per se. Rather, the investor evaluates a security on the basis of its influence on the risk-return characteristics of his/her portfolio should the security be included in his/her portfolio.
In empirical testing the explanatory power (coefficient of correlation) of CAPM has been quite low. There has been much debate as to the reasons for this state of matters. (See Roll 1977 in particular.) One of the (many) potential explanations is that investors might after all consider a security's variance rather than its beta in assessing its riskiness. According to this view the investors consider securities individually rather than as parts of their portfolios, or the investors' portfolios are quite non-diversified (in other words consist very few securities.) Results regressing security returns with security variances are consistent with this view. (See Levy & Sarnat 1986: Ch. 13.)
Consequently, the third variable we include in this ex ante category is the security's total risk. It is calculated as the variance of the security's returns.
Factor analysis is a statistical method for reducing the original set of variables into a smaller set of underlying factors in a manner that retains as much as possible of the original information of the data. In statistical terms this means finding factors that explain as much as possible of the variance in the data. (For a more comprehensive description of the factor analysis methodology in categorizing financial ratios see Yli-Olli & Virtanen 1985. For the statistical theory of factor analysis see Johnson & Wichern 1982: 401-420.)
Transformation analysis is a statistical method that is well-suited for testing the temporal stability of the factor patterns of the financial (and market-based) ratios. Applying this approach to testing stability was introduced in financial ratio caterization by Yli-Olli & Virtanen (1985). (See their report, and Ahmavaara 1963, Mustonen 1966, and Sänkiaho 1986 for more on this subject and the methodology).
The stability of financial ratio patterns has traditionally been tested with the correlation or congruence coefficients between the sub-periods of the data. Both these indices measure the degree of similarity between two factor solutions in terms of the pattern of correlations / congruences among factor loadings across all the variables in the reduced factor space. This can also be achieved via transformation analysis. In addition, by applying transformation analysis we obtain a regression type of a model for the shifting of the variables from one factor to another. This also means that the dissimilar part in the factor solutions can be modeled and measured quantitatively. (For a more detailed description about the difference between correlation / congruence analysis, and transformation analysis, see Yli-Olli & Virtanen 1990: 13-15.)
To establish the stable factors the period was subdivided into two subperiods. These are 1974-78 and 1979-84. Again, averages were calculated for both sub-periods. These averages make up our second and third data sets.
In calculating weighted averages for ratios equal-weighted and value-weighted averages can be used. (See e.g. Foster 1988: Section 6.3.) There are two reasons why we used equal-weighted averages. First, the Finnish Compustat equivalent TILPANA computer data base at the University of Vaasa does not readily contain all the information that would have been needed for calculating consistent value-weighted averages. Second, even if using value-weighted averages might increase the explained variance, this is not material for our principal tasks, that is finding stable factor patterns and testing the hypotheses.
The sensitivity of the factor analysis results was also tested in respect to the rotation technique and the data set. First, the analyses were repeated using promax oblique factor analysis rotation. The results are not sensitive to the method of rotation. Second, the three sets of ratios (accrual, cash flow, and market-based) ratios were factorized alone. The results are not sensitive to the set of variables in the data basis.
Transformation analysis was performed between the factor matrices of the 1974-78 and the 1979-84 period. The transformation matrix is given in Appendix E, and the transformations are visualized in Appendix F. The largest coefficients of coincidence (the stable transformations) are indicated by asterisks in Appendix E.
One stable pattern emerged, however, centrally involving a market-based ratio. This is the size / beta factor, which will be discussed at a later stage.
The lack of the expected risk and return factor is an interesting phenomenon. An analysis of the reasons is, however, beyond the scope of this study. Nevertheless, it is interesting very briefly to speculate about the potential explanations. It must be stressed that this is highly tentative.
It has been observed in several empirical studies that the significance of market models involving risk and return is not high. For example the results on the capital asset pricing model have had quite low correlation coefficients. (See Friend & Blume 1970, Blume & Friend 1973, and Levy & Sarnat 1986: 343-346.) Thus our results may be a reflection of the low explanatory power of the market models.
As can be seen from the analysis results, two stable factors emerge, which can be interpreted as a profitability factor and a operational leverage factor. Both these factors are stable, as is depicted by the transformation matrix in Appendix E and F. The strength of the transformation (i.e. the coefficient of coincidence) between the two sub-periods is almost one (0.905) for the profitability factor, and a high 0.874 for the operational leverage factor.
The interpretation of operational leverage factor is much fuzzier than that of the very clear-cut profitability factor. The ratios loaded on the operational leverage factor could not easily be foreseen.
Looking at the individual ratios, return on equity, return on total assets, and the E/P ratio best characterize the performance factor. As was discussed earlier, the E/P (or P/E) ratio can, a priori, be looked at as a profitability kind of a measure. Our results agree with this interpretation of the P/E ratio. Labor intensiveness, times interest earned, dividend payout ratio, and net working assets to total assets characterize this operational leverage factor.
The empirical results of the earlier studies have not been interpreted in this light, but they are not contradictory. If the variation in the classifications of the earlier studies is looked from this point of view, they are more consistent than what is usually stated.
Looking at the individual ratios, cash net income / interest bearing debt, cash net income / cash from sales, and cash to interest / cash margin Ib best characterize the cash flow factor.
This corroborates similar results from earlier studies. The difference is that we had a wider range of variables, and the confirmation of the cash flow factor thus is more general than in the previous studies.
Our result on the standard financial ratio classification fits the earlier research results. No clearly consistent pattern of financial ratios has emerged from the earlier studies beyond the first two or three factors. It is obvious that the patterns beyond are dependent on the particular data set. This raises an interesting question for further research. That is whether the divergence of the financial ratio factor patterns can be explained, or whether it is random behavior.
In addition to the stable profitability, leverage, and cash flow factors three other stable factors were found. These are the size & beta factor, the dynamic liquidity factor, and the growth rate factor.
Admittedly, we did not hypothesize the emergence of the size & beta factor, but with the benefit of hindsight the appearance of this factor is not surprising. Increasing attention has been drawn in finance research to the existence of persistent anomalies from market efficiency. Among these anomalies feature e.g. the monday-effect anomaly, the january-effect anomaly, the price-to-earnings ratio anomaly and the concomitant "size-beta" anomaly. Basu (1983: 142) observed for a Compustat sample covering 1962 - 1978 that the betas (systematic risk) of the common stock of NYSE firms "declines quite dramatically and in a monotonic way as one moves from portfolios consisting of small firms to those consisting of the larger ones". The emergence of our size & beta factor agrees with this result.
The defensive interval measure has traditionally been considered a measure of short-term liquidity. (See e.g. Sorter & Benston 1960, Davidson & Sorter & Kalle 1964, and Fadel & Parkinson 1978.) As discussed in introducing the ratios at the early stages of this report, the defensive interval measure is a balance sheet / income statement ratio. Liquidity ratios which include an income statement element are often called dynamic ratios. We shall consequently call this factor a dynamic liquidity factor.
As observed, the accounts receivable turnover period also loaded on the dynamic liquidity factor. And, as can be seen in Appendices B through D, the factor loadings of the two ratios have opposite signs. This is a natural result. It is to be expected that when the accounts receivable turnover period gets smaller (improves), the defensive interval measure grows (the liquidity improves). In managerial terms it could be said that an efficient control of accounts receivable improve liquidity.
The two ratios of the dynamic liquidity factor also have a definitional dependence, but as stated earlier, all such links cannot be avoided. Receivables feature in both the ratios. (The current assets appearing in the defensive interval measure are made up by cash + marketable securities + accounts receivables.)
The emergence of a growth factor supports including growth measures in conventional financial statement analyses. According to our factor analysis results, growth measures produce information not necessarily present in the conventional X/Y-type financial ratios.
Growth and the generation of revenues (reflected in the operating margin) have a positive relationship. In other words fast growth and better than average revenue generating ability appear to be connected. This seems a sensible result. On the other hand, growth and profitability (measured e.g. by return on equity) did not go on the same factor in our study. At first sight this is somewhat baffling because of the evidence on a relationship between growth and profitability. (See e.g. Miller & Modigliani 1966, Singh & Whittington 1968: Ch. 7., Eatwell 1971: 411, and Ruuhela & Salmi & Luoma & Laakkonen 1982: 340.) A closer look at the results in Appendix B for the entire period of observation shows, however, that the defensive interval measure, times interest earned, and return on equity do have significant factor loadings on the growth factor.
The research classifying the financial ratios can be divided into three main approaches. The pragmatic approach is largely based on the common business practices of financial statement analysis. The inductive approach is primarily based on observed statistical behavior of financial ratios. Finally, the deductive approach draws from theoretical considerations and the empirical properties of the financial ratios. Our study best belongs to the third approach.
Our study covered three different types of financial ratios, the accrual ratios, the cash flow ratios, and the market-based ratios. Research categorizing financial ratios has traditionally concentrated on accrual based figures, and the research involving cash flow ratios in the categorization has been more scanty. Market-based ratios have practically been lacking from the earlier studies.
We used factor analysis and transformation analysis as our statistical methods. The former has traditionally been applied to classifying the financial ratios. The latter method was used to test the temporal stability of the financial ratio factors. The use of transformation analysis methodology in financial ratio categorization has few precedents, and can be considered a novel technique in this field.
We used a hypothesis testing approach in our study. Four central hypotheses based on finance and accounting theories, and earlier research, were presented and tested. The hypotheses were called the return and risk categorization hypothesis of market-based ratios, the performance and financial standing dichotomy hypothesis of accrual ratios, the cash flow information hypothesis, and the hypothesis on the viability of standard financial ratio classifications. The content of these hypotheses was the following.
The first hypothesis, stating that the market-based ratios would load on a common factor of return and riskiness, was not confirmed. In fact, the market-based ratios dispersed widely on different factors. Even if unexpected, this result may reflect the low explanatory power of market models such the Capital Asset Pricing Model. This result also means that the development of market-based ratios is either still at an infant stage, and / or that unlike the accrual and cash flow financial ratios the market-based ratios simply are not amenable to a consistent categorization.
It is also interesting to see that the firm size variable and the market-based beta made up a stable factor of their own. This result strongly supports the earlier research results on the interdependence of firm sizes and security betas.
The second hypothesis stated that business firms are characterized by two underlying main features, that is their dynamic performance and static financial standing. The observed accrual-related stable factors included the profitability factor and the operational leverage factor. The identification and interpretation of the profitability factor was very straight-forward, but the operational leverage factor was more difficult to interpret. These results lend reasonable support, but should be take with some caution because of the problems in interpreting the content of the operating leverage factor.
The third hypothesis stating that cash flow ratios would load on a separate and distinct stable factor was strongly confirmed. This corroborates earlier results that cash flow ratios impart information not present in the accrual-based financial ratios.
The fourth hypothesis concerned the standard text-book financial ratio classification into profitability, liquidity, solvency, and turnover. Our results did not lend direct support to this conventional classification, but the here the results must be considered inconclusive.
The empirical results also gave rise to observing that the defensive interval measure and the accounts receivable made up a strongly stable factor, which we named a dynamic liquidity factor. Finally, growth and operating margin formed a distinct and stable growth factor. This factor emphasizes the importance of growth estimates in financial statement analysis.
Aho, Teemu (1980). Empirical Classification of Financial Ratios. Christer Carlsson, ed. Management Science in Finland (MASC 1980) Proceedings, 413-421.
Aho, Teemu (1981). Yrityksen tilinpäätösanalyysi. 3rd edition. Espoo: Otapaino, Otakustantamo.
Artto, Eero (1978). Money Flow Analysis. Journal of Business Finance & Accounting 5:1, 27-37.
Baker, Kent H. & Farrelly, Gail E. & Edelman, Richard B. (1985). A Survey of Management Views on Dividend Policy. Financial Management 14:3, 78-84.
Banz, R. (1981). The Relationship between Returns and Market Value of Common Stocks. Journal of Financial Economics 9:1, 3-18.
Barnes, Paul (1982). Methodological Implications of Non-normally Distributed Financial Ratios. Journal of Business Finance & Accounting 9:1, 51-62.
Barnes, Paul (1983). Methodological Implications of Non-normally Distributed Financial Ratios: A Reply. Journal of Business Finance & Accounting 10:4, 691-693.
Barnes, Paul (1987). The Analysis and Use of Financial Ratios: A Review Article. Journal of Business Finance & Accounting 14:4, 449-461.
Basu, Sanjoy (1983). The Relationship Between Earnings' Yield, Market Value and Return for NYSE Common Stocks: Further Evidence. Jounal of Financial Economics 12, 129-156.
Bayldon, R. & Woods, A. & Zafiris, N. (1984). A Note on the 'Pyramid' Technique of Financial Ratio Analysis of Firms' Performance. Journal of Business Finance & Accounting 11:1, 99-106.
Bernstein, Leopold A. (1989). Financial Statement Analysis: Theory, Application, and Interpretation. Fourth Edition. Homewood, Illinois: Richard D. Irwin, Inc., 1. ed. 1974.
Black, F. (1972). Capital Market Equilibrium with Restricted Borrowing. Journal of Business 45:3, 444-455.
Black, F. & Jensen, M. & Scholes, M. (1972). The Capital Asset Pricing Model: Some Empirical Tests. M.C. Jensen, editor. Studies in the Theory of Capital Markets.
Blume, Marshall & Friend, Irwin (1973). A New Look at the Capital Asset Pricing Model. Journal of Finance 28:1, 19-34.
Bowen, R.M. & Burgstahler, D. & Daley, L.A. (1987). The Incremental Information Content of Accrual versus Cash Flows. The Accounting Review 62:4, 723-747.
Brealey, Richard & Myers, Stewart (1984). Principles of Corporate Finance. Second Edition. Auckland, etc: McGraw-Hill.
Buckley, Peter J. & Dunning, John H. & Pearce, Robert D. (1984). An Analysis of the Growth and Profitability of the World's Largest Firms 1972 to 1977. Kyklos 37:1, 3-26.
Chen, Kung H. & Shimerda, Thomas A. (1981). An Empirical Analysis of Useful Financial Ratios. Financial Management. Spring, 51-60.
Courtis, John K. (1978). Modelling a Financial Ratios Categoric Framework. Journal of Business Finance and Accounting 5:4, 371-386.
Cowen, Scott S. & Hoffer, Jeffrey A. (1982). Usefulness of Financial Ratios in a Single Industry. Journal of Business Research 10:1, 103-118.
Davidson, Sidney & Sorter, George H. & Kalle, Hemu (1964). Measuring the Defensive Position of a Firm. Financial Analyst's Journal 20, 23-29.
Dhrymes, P.J. & Friend, I. & Gultegin, N.B. (1984). A Critical Reexamination of the Empirical Evidence of the Arbitrage Pricing Theory. The Journal of Finance 39:2, 323-346.
Eatwell, John L. (1971) Growth, Profitability and Size: The Empirical Evidence. Morris, Robin & Wood, Adrian, editors. The Corporate Economy: Growth, Competition, and Innovative Potential. Macmillan 389-412
Elton, E.J. & Gruber, M.J. (1987). Modern Portfolio Theory and Investment Analysis. New York: John Wiley & Sons.
Ezzamel, Mahmoud & Brodie, J. & Mar-Molinero, C. (1987). Financial Patterns of UK Manufacturing Companies. Journal of Business Finance & Accounting 14:4, 519-536.
Fadel, Hisham & Parkinson, John M. (1978) Liquidity Evaluation by Means of Ratio Analysis Accounting and Business Research 30, 101-107.
Fieldsend, Susan & Longford, Nicholas & McLeay, Stuart (1987). Industry Effects and the Proportionality Assumption in Ratio Analysis: A Variance Component Analysis. Journal of Business Finance & Accounting 14:4, 497-517.
Foster, G. (1978). Asset Pricing Models: Further Tests. Journal of Financial and Quantitative Analysis 13:1, 39-53.
Foster, George (1986). Financial Statement Analysis. Second edition. Englewood Cliffs, New Jersey: Prentice Hall, Inc.
Fridson, Martin S. & Marocco, Michael J. (1986). Financial Statement Analysis. Altman, Edward I. & Mary Jane McKinney, editors. Chapter 3: Handbook of Corporate Finance. John Wiley & Sons.
Friend, Irwin & Blume, Marshall (1970). Measurement of Portfolio Performance under Uncertainty. American Economic Review. September, 561-575.
Gombola, Michael J. & Ketz, Edward (1983). A Note on Cash Flow and Classification Patterns of Financial Ratios. The Accounting Review LVIII:1, 105-114.
Horrigan, James O. (1968). A Short History of Financial Ratio Analysis. The Accounting Review 43, 284-294.
Horrigan, James (1983). Methodological Implications of Non-normally Distributed Financial Ratios: A Comment. Journal of Business Finance & Accounting 10:4, 683-689.
Ismail, Badr E. & Kim, Moon K. (1989). On the Association of Cash Flow Variables with Market Risk: Further Evidence. The Accounting Review LXIV:1, 125-136.
Johnson, R.A. & Wichern, D.W. (1982). Applied Multivariate Statistical Analysis. Englewood Cliffs: Prentice Hall, Inc.
Johnson, Bruce (1979). The Cross-Sectional Stability of Financial Ratio Patterns. Journal of Financial and Quantitative Analysis XIV:5, 1035-1049.
Kanto, Antti J. & Martikainen, Teppo (1989). A Confirmatory Test of the Validity of an a Priori Classification Pattern of Financial Ratios. Proceedings of the University of Vaasa. Discussion Papers 99.
Kettunen, Pertti & Mäkinen, Vesa & Neilimo, Kari (1976). Tilinpäätösanalyysi. Ekonomia-sarja 46. Espoo: Weilin+Göös.
Kinnunen, Juha (1988). The Time Series Properties of Accrual versus Cash-Based Income Variables: Empirical evidence from listed Finnish Firms. Doctoral Dissertation. The Helsinki School of Economics.
Laitinen, Erkki (1983). A Multivariate Model of the Financial Relationships in the Firm. The Finnish Journal of Business Economics 32:4, 317-333.
Laitinen, Erkki K. (1988). Yrityksen talouden mittarit. Ekonomia-sarja. Weilin+Göös.
Laurent C.R. (1979). Improving the Efficiency and Effectiveness of Financial Ratio Analysis. Journal of Business Finance & Accounting 6:3, 401-413.
Lehtinen, Janne (1989). Yrityksen koon, iän ja toimialan vaikutus tunnuslukuihin. Unpublished Master's Thesis in Accounting and Business Finance. University of Vaasa.
Lev, Baruch (1974). Financial Statement Analysis: A New Approach. Englewood Cliffs, New Jersey: Prentice Hall, Inc.
Levy, Haim & Sarnat, Marshall (1986). Capital Investment and Financial Decisions. 3rd edition. Englewood Cliffs, N.J., London, etc.: Prentice/Hall International.
Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets. The Review of Economics and Statistics 47:1, 13-37.
Lukkaroinen, Teija (1988). Yrityksen koon vaikutus tunnuslukuihin - perinteiset ja kassavirtaan perustuvat tunnusluvut. Unpublished Master's Thesis in Accounting and Business Finance. University of Vaasa.
Martikainen, Teppo (1989). Stock Price Behavior and Economic Operations of the Firm. Licentiate Dissertation in Accounting and Business Finance. University of Vaasa.
Miller, M.H. & Modigliani, F. (1966) Some Estimates of the Cost of Capital to the Electric Utility Industry 1954-57. American Economic Review 56:3, 333-348.
Mossin, J. (1966). Equilibrium in a Capital Market. Econometrica 34:4, 768-783.
Mustonen, Seppo (1966). Symmetric Transformation Analysis (in Finnish). Reports from the Social Research Institute of Alcohol Studies. No. 24.
Perttunen, Jukka & Martikanen, Teppo (1989). The Functional Specification of Financial Ratios. Proceedings of the University of Vaasa. Research Paper 142.
Pinches, George & Eubank, A. & Mingo, K. & Caruthers, K. (1975). The Hierarchical Classification of Financial Ratios. Journal of Business Research 3:4, 295-310.
Pinches, George E. & Mingo, Kent A. & Caruthers, J. Kent (1973). The Stability of Financial Patterns in Industrial Organizations. Journal of Finance 28, 389-396.
Pohlman, Randolph & Hollinger, Robert D. (1981). Information Redundancy in Sets of Financial Ratios. Journal of Business Finance & Accounting 8:4, 511-528.
Rayburn, J. (1986). The Association of Operating Cash Flow and Accruals with Security Returns. Supplement to the Journal of Accounting Research 24, 112-133.
Reinganum, M. (1981). Misspecification of Capital Asset Pricing: Empirical Anomalies Based on Earnings Yield and market Values. Journal of Financial Economics 9, 19-46.
Roll, R. (1977). A Critique of the Asset Pricing Theory's Tests. Journal of Financial Economics 5:1, 129-176.
Ross, S.A. (1976). The Arbitrage Pricing Theory and Capital Asset Pricing. Journal of Economic Theory. December, 343-362.
Ruuhela, R. & Salmi, T. & Luoma, M. & Laakkonen, A. (1982). Direct Estimation of the Internal Rate of Return from Published Financial Statements. The Finnish Journal of Business Economics 31:4, 329-345.
Saario, Martti (1949). Kustannusten etuoikeusjärjestyksestä. Huugo Raninen 50 vuotta. Helsinki.
Salmi, Timo (1978). A Comparative Review of the Finnish Expenditure-Revenue Accounting. European Institute for Advanced Studies in Management. Working Paper 78-2.
Salmi, Timo & Luoma, Martti (1981). Deriving the Internal Rate of Return from the Accountant's Rate of Profit: Analysis and Empirical Estimation. The Finnish Journal of Business Economics 30:1, 20-45.
Salmi, Timo & Dahlstedt, R. & Luoma, M. & Laakkonen, A. (1986). Financial ratio variability and industry classification. The Finnish Journal of Business Economics 35:4, 333-356.
Sharpe, W.F. (1963). A Simplified Model for Portfolio Analysis. Management Science 9:1, 277-293.
Sharpe, W.F. (1964). Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk. Journal of Finance 19:3, 425-442.
Singh, A. & Whittington, G. & Burley, H.T. (1968) Growth, Profitability and Valuation. A Study of United Kingdom Quoted Companies Cambridge at the University Press
Sorter, G.H. & Benston, George (1960) Appraising the Defensive Position of a Firm: The Interval Measure The Accounting Review 35:4, 69-76.
Sudarsanam, P.S. & Fortune, L.H. (1987). Relative Usefulness of Accrual-based and Cashflow-based Earnings in Security Evaluation: An Empirical Test. Presented at the EAA Annual Conference in Stuttgart 5-7 Apr.
Sänkiaho, Risto (1986). Temput ja kuinka ne tehdään. Monimuuttajamenetelmät kansan palvelijoina. Reports from the Institute of Educational Research 220/1974. University of Jyväskylä.
Virtanen, Ilkka & Yli-Olli, Paavo (1989). Cross-sectional Properties and Time-series Persistence of Financial Ratio Distributions: Empirical Evidence with Finnish Data. European Institute for Advanced Studies in Management. Working Paper 89-04.
Whittington, Geoffrey (1980). Some Basic Properties of Accounting Ratios. Journal of Business Finance & Accounting 7:2, 219-232.
Wilson, G.P. (1987). The Incremental Information Content of the Accrual and Funds Components of Earnings after Controlling for Earnings. The Accounting Review 62:2, 293-322.
Wilson, G.P. (1986). The Relative Information Content of Accruals and Cash Flows: Combined Evidence at the Earnings Announcement and Annual Report Date. Supplement to the Journal of Accounting Research 24, 165-200.
Yli-Olli, Paavo & Virtanen, Ilkka (1985). Modelling a Financial Ratio System on the Economy-Wide Level. Acta Wasaensia No. 21. University of Vaasa.
Yli-Olli, Paavo & Virtanen, Ilkka (1989). On the Long-term Stability and Cross-country Invariance of Financial Ratio Patterns. European Journal of Operational Research 39:1, 40-53.
Yli-Olli, Paavo (1983). Tilinpäätösanalyysissä käytettävien tunnuslukujen luokittelu ja stabiilisuus. (Summary: The empirical classification of financial ratios and the stability of the classification.) Proceeding of the University of Vaasa. Research Papers No. 95.
Yli-Olli, Paavo & Virtanen, Ilkka (1990). Forthcoming. Transformation Analysis Applied to Long-term Stability and Structural Invariance of Financial Ratio Patterns: U.S. vs. Finnish Firms. American Journal of Mathematical and Management Sciences 10.
APPENDIX A: The Ratios
ACCRUAL RATIOS
Liquidity
- quick ratio
= current assets less inventories / current liabilities
- defensive interval measure
= current assets less inventories / daily expenditures to
operations
- net working capital to total asset
Capital Adequacy
- total liabilities / sales
- long-term debt to equity
- times interest earned
= earnings before interest and taxes plus depreciation /
interest
Profitability
- return (after interest and taxes) on equity
= net income / common equity
- return on total assets
- operating margin / sales
Efficiency (turnover ratios)
- inventory turnover period
= average inventory / cost of goods sold
- accounts receivable turnover period
= receivables / sales
Operating Leverage
- labor intensiveness
= personnel expenditures / adjusted real-term fixed assets
- variable costs / fixed costs
Riskiness
Volume
- growth rate
= long-term growth rate of deflated sales
- size
= firm's total assets in proportion to the largest firm
(annual figures)
CASH FLOW RATIOS
- cash net income (cash margin II) divided by cash from sales
- cash operating income (cash margin Ib) divided by total assets
- cash outflow to capital investments divided by cash from sales
- cash outflow to materials & supplies and wages & salaries
divided by cash from sales
- cash net income (cash margin II) divided by interest bearing
debt (average)
- cash outflow to interest payments divided by cash operating
income (cash margin Ib)
MARKET-BASED RATIOS
Firm Ratios
- dividend payout ratio
= dividends per share / earnings per share
Combined Ratios
- dividend yield
- E/P (inverse of price per earnings)
- market to book ratio
= stock price per share / book value per share
Pure Market Ratios
- return on the security (capital gains and dividend yield)
- security's beta
- security's total risk
APPENDIX B: Varimax-rotated Factor Pattern for the Averages of the
Ratios 1974-1984
FACT1 FACT2 FACT3 FACT4 FACT5
X3 0.903 . . . . net work. cap. to tot. ass.
X12 0.777 . . . . labor intensiveness
X6 0.717 . . . . times interest earned
X1 0.717 0.418 . . 0.338 quick ratio
X4 -0.684 . -0.372 0.329 . total liabilities/sales
X17 . 0.912 . . . cash margin Ib / total ass.
X16 . 0.905 . . . cash net income / cash sales
X20 . 0.788 0.309 . . cash netinc. / int bear debt
X21 0.505 0.714 . . . cash to inter / cash marg Ib
X10 . 0.659 . -0.511 . inventory turnover period
X19 0.353 -0.461 0.302 0.357 . cash to mat & w / cash sales
X24 0.362 . 0.861 . . E/P-ratio
X7 . 0.302 0.646 . . return on equity
X26 . . 0.620 -0.519 . return on the security
X5 -0.436 . -0.491 . . long-term debt to equity
X27 . . . 0.873 . security's beta
X15 . . . 0.834 . size
X2 . . . . 0.844 defensive interval measure
X11 . . . . -0.835 acc. rec. turnover period
X14 . . . . .
X9 -0.369 . . . .
X22 . . . . .
X8 0.397 0.350 0.429 . .
X18 . . . . .
X28 . . . . .
X23 . . . . .
X13 . . . . -0.323
X25 . . . 0.423 0.390
NOTE: VALUES LESS THAN 0.3 HAVE BEEN PRINTED AS '.'
FACT6 FACT7 FACT8 FACT9 FACT10
X3 . . . . .
X12 . . . . .
X6 0.316 0.360 . . .
X1 . . . . .
X4 0.332 . . . .
X17 . . . . .
X16 . . . . .
X20 . . . . .
X21 . . . . .
X10 . . . . .
X19 . . . . 0.327
X24 . . . . .
X7 0.307 . . . .
X26 . . . . .
X5 . . . 0.457 .
X27 . . . . .
X15 . . . . .
X2 0.312 . . . .
X11 . . . . .
X14 0.873 . . . . growth rate
X9 0.729 . . . . operating margin
X22 . 0.928 . . . dividend payout ratio
X8 . 0.581 . . . return on total assets
X18 . . 0.791 . . cash to cap inv / cash sales
X28 . . -0.743 . . security's total risk
X23 . . . 0.864 . dividend yield
X13 . . . . 0.824 variable costs/fixed costs
X25 . . . . 0.500 market to book ratio
NOTE: VALUES LESS THAN 0.3 HAVE BEEN PRINTED AS '.'
VARIANCE EXPLAINED BY EACH FACTOR
FACTOR1 FACTOR2 FACTOR3 FACTOR4 FACTOR5
4.403194 4.238279 2.715487 2.622527 2.241442
FACTOR6 FACTOR7 FACTOR8 FACTOR9 FACTOR10
2.109226 1.929188 1.510821 1.400599 1.336602
Cumulative Proportion of total variance
FACTOR1 FACTOR2 FACTOR3 FACTOR4 FACTOR5
0.2451 0.4264 0.5268 0.6150 0.6760
FACTOR6 FACTOR7 FACTOR8 FACTOR9 FACTOR10
0.7317 0.7770 0.8144 0.8463 0.8753
FINAL COMMUNALITY ESTIMATES: TOTAL = 24.507366
X1 X2 X3 X4 X5 X6 X7
0.908735 0.892475 0.936411 0.909261 0.820585 0.893423 0.937337
X8 X9 X10 X11 X12 X13 X14
0.903409 0.910361 0.900782 0.813549 0.860574 0.829672 0.871482
X15 X16 X17 X18 X19 X20 X21
0.863071 0.937182 0.941458 0.743830 0.859216 0.893015 0.956612
X22 X23 X24 X25 X26 X27 X28
0.905599 0.877821 0.930363 0.795191 0.853346 0.832598 0.730011
APPENDIX C: Varimax-rotated Factor Pattern for the Averages of the
Ratios 1974-1978
FACT1 FACT2 FACT3 FACT4 FACT5
X24 0.938 . . . . E/P-ratio
X7 0.812 . . . . return on equity
X8 0.622 . 0.603 . . return on total assets
X26 0.516 . . 0.474 -0.420 return on the security
X1 0.494 . . . . quick ratio
X4 -0.584 . . -0.463 0.370 total liabilities/sales
X5 -0.748 . . . . long-term debt to equity
X17 . 0.901 0.302 . . cash margin Ib / total ass.
X16 . 0.875 . -0.306 . cash net income / cash sales
X20 . 0.851 . . . cash netinc / int bear debt
X21 . 0.684 0.575 . . cash to inter / cash marg Ib
X10 . 0.574 . . -0.459 inventory turnover period
X22 . . 0.872 . . dividend payout ratio
X6 0.427 . 0.803 . . times interest earned
X12 0.375 . 0.634 . . labor intensiveness
X3 0.384 -0.414 0.463 0.351 . net work. cap. to tot. ass.
X13 . . . 0.848 . variable costs/fixed costs
X19 . . . 0.793 . cash to mat & w / cash sales
X9 . . . -0.764 . operating margin
X15 . . . . 0.841 size
X27 . . . . 0.821 security's beta
X25 . . . . 0.548 market to book ratio
X11 . . . . .
X2 . . . -0.376 .
X28 . . . . .
X23 0.468 . . . .
X14 . . . . .
X18 . . . . .
NOTE: VALUES LESS THAN 0.3 HAVE BEEN PRINTED AS '.'
FACT6 FACT7 FACT8 FACT9 FACT10
X24 . . . . .
X7 . . . . .
X8 . . . . .
X26 . . . . .
X1 -0.434 . . . 0.485
X4 . . . . -0.330
X5 . . . . .
X17 . . . . .
X16 . . . . .
X20 . . . . .
X21 . . . . .
X10 . -0.306 . . 0.378
X22 . . . . .
X6 . . . . .
X12 . . . . 0.322
X3 . . . . 0.420
X13 . . . . .
X19 . . . . .
X9 . . 0.349 . -0.305 (operating margin)
X15 . . . . .
X27 . . . . .
X25 . . . 0.511 .
X11 0.941 . . . . acc. rec. turnover period
X2 -0.825 . . . . defensive interval measure
X28 . 0.875 . . . security's total risk
X23 . -0.560 . . 0.315 dividend yield
X14 . . 0.933 . . growth rate
X18 . . . 0.871 . cash to cap inv / cash sales
VARIANCE EXPLAINED BY EACH FACTOR
FACTOR1 FACTOR2 FACTOR3 FACTOR4 FACTOR5
4.378313 3.649694 3.240343 3.071599 2.625934
FACTOR6 FACTOR7 FACTOR8 FACTOR9 FACTOR10
2.096879 1.632641 1.501724 1.378910 1.248399
Cumulative Proportion of total variance
FACTOR1 FACTOR2 FACTOR3 FACTOR4 FACTOR5
0.2661 0.4200 0.5305 0.6154 0.6803
FACTOR6 FACTOR7 FACTOR8 FACTOR9 FACTOR10
0.7402 0.7891 0.8282 0.8597 0.8866
FINAL COMMUNALITY ESTIMATES: TOTAL = 24.824436
X1 X2 X3 X4 X5 X6 X7
0.872644 0.894561 0.914550 0.900938 0.765444 0.942703 0.908289
X8 X9 X10 X11 X12 X13 X14
0.922396 0.921668 0.935987 0.928411 0.907007 0.877017 0.914587
X15 X16 X17 X18 X19 X20 X21
0.834947 0.930683 0.941563 0.843185 0.885844 0.935010 0.965654
X22 X23 X24 X25 X26 X27 X28
0.844763 0.876725 0.922139 0.748515 0.825211 0.850206 0.813790
APPENDIX D: Varimax-rotated Factor Pattern for the Averages of the
Ratios 1979-1984
FACT1 FACT2 FACT3 FACT4 FACT5
X12 0.912 . . . . labor intensiveness
X6 0.817 0.365 . . . times interest earned
X22 0.812 . . . . dividend payout ratio
X3 0.688 . . . . net work. cap. to tot. ass.
X4 -0.564 . -0.332 0.504 . total liabilities/sales
X20 . 0.922 . . . cash netinc / int bear debt
X16 -0.316 0.741 . . . cash net income / cash sales
X21 0.580 0.739 . . . cash to inter / cash marg Ib
X1 . 0.682 . . -0.430 quick ratio
X7 . . 0.854 . . return on equity
X24 . . 0.836 . . E/P-ratio
X8 0.429 . 0.619 . . return on total assets
X9 -0.355 . . 0.794 . operating margin
X14 . . . 0.741 . growth rate
X5 -0.377 . . 0.532 . long-term debt to equity
X11 . . . . 0.906 acc. rec. turnover period
X2 . . . . -0.868 defensive interval measure
X10 . . . . .
X17 . 0.509 . . .
X19 . . . -0.408 .
X25 . . . . .
X13 . . . . 0.356
X27 . . 0.372 . .
X15 . . . 0.340 .
X26 . . 0.448 . -0.310
X23 . . . . .
X28 . . . . .
X18 . . . . .
NOTE: VALUES LESS THAN 0.3 HAVE BEEN PRINTED AS '.'
FACT6 FACT7 FACT8 FACT9 FACT10
X12 . . . . .
X6 . . . . .
X22 . . . . -0.338
X3 . . . . .
X4 . . . . .
X20 . . . . .
X16 0.303 . . . .
X21 . . . . .
X1 . . . . .
X7 . . . . .
X24 . . . . .
X8 . . . 0.361 .
X9 . . . . .
X14 . . . . .
X5 . . . 0.430 .
X11 . . . . .
X2 . . . . .
X10 0.957 . . . . inventory turnover period
X17 0.574 . . 0.436 . cash margin Ib / total ass.
X19 -0.650 . . . . cash to mat & w / cash sales
X25 . 0.794 . . . market to book ratio
X13 . 0.752 . . . variable costs / fixed costs
X27 . . 0.817 . . security's beta
X15 . . 0.739 . . size
X26 . . -0.578 -0.302 . return on the security
X23 . . . 0.822 . dividend yield
X28 . . . . 0.874 security's total risk
X18 . -0.433 . . -0.600 cash to cap inv / cash sales
NOTE: VALUES LESS THAN 0.3 HAVE BEEN PRINTED AS '.'
VARIANCE EXPLAINED BY EACH FACTOR
FACTOR1 FACTOR2 FACTOR3 FACTOR4 FACTOR5
4.316926 3.367783 2.741719 2.475085 2.309695
FACTOR6 FACTOR7 FACTOR8 FACTOR9 FACTOR10
1.996683 1.995761 1.940643 1.815787 1.767355
Cumulative Proportion of total variance
FACTOR1 FACTOR2 FACTOR3 FACTOR4 FACTOR5
0.2349 0.4115 0.5052 0.5891 0.6673
FACTOR6 FACTOR7 FACTOR8 FACTOR9 FACTOR10
0.7258 0.7803 0.8246 0.8580 0.8831
FINAL COMMUNALITY ESTIMATES: TOTAL = 24.727437
X1 X2 X3 X4 X5 X6 X7
0.905749 0.880392 0.846420 0.909287 0.818603 0.916645 0.940584
X8 X9 X10 X11 X12 X13 X14
0.844907 0.952743 0.952222 0.912810 0.903211 0.818652 0.888208
X15 X16 X17 X18 X19 X20 X21
0.836716 0.937781 0.915702 0.776996 0.874437 0.932460 0.950174
X22 X23 X24 X25 X26 X27 X28
0.888035 0.790788 0.849289 0.846701 0.863722 0.895879 0.878326
APPENDIX E: Transformation Matrix 1974-78 to 1979-84 (L12)
1 2 3 4 5
1 0.185 0.077 0.905* -0.241 -0.156
2 -0.185 0.836* 0.074 0.046 0.187
3 0.874* 0.171 -0.059 0.095 0.127
4 0.080 0.121 -0.112 -0.344 0.106
5 -0.150 0.220 -0.006 0.023 -0.054
6 0.042 -0.161 0.070 -0.036 0.912*
7 0.052 0.362 -0.170 -0.062 -0.019
8 0.122 0.019 0.108 0.852* -0.075
9 0.131 0.196 -0.268 -0.101 -0.153
10 0.321 -0.081 -0.207 -0.264 -0.224
6 7 8 9 10
1 -0.019 0.007 0.008 -0.241 -0.026
2 0.390 0.103 -0.113 0.213 -0.062
3 -0.158 -0.143 0.073 0.348 -0.083
4 -0.434 0.743 -0.235 -0.019 0.202
5 -0.293 0.119 0.908* 0.003 -0.019
6 0.126 0.004 0.142 -0.313 -0.028
7 -0.262 -0.464 -0.090 -0.468 0.567
8 0.014 0.354 -0.047 -0.308 0.136
9 -0.052 0.018 -0.066 -0.563 -0.718
10 0.679 0.248 0.258 -0.217 0.302
APPENDIX F: Transformation Matrix Relationships
X1 = quick ratio X22 = dividend payout ratio X2 = defensive interval measure X23 = dividend yield X3 = net working capital to total assets X24 = E/P-ratio X4 = total liabilities / sales X25 = market to book ratio X5 = long-term debt to equity X26 = return on the security X6 = times interest earned X27 = securitys beta X7 = return on equity X28 = securitys total risk X8 = return on total assets X9 = operating margin X10 = inventory turnover period X11 = accounts receivable turnover period X12 = labor intensiveness X13 = variable costs / fixed costs X14 = growth rate X15 = size X16 = cash net income / cash from sales X17 = cash margin Ib / total assets X18 = cash to capital investments / cash sales X19 = cash to materials & wages / cash sales X20 = cash net income / interest bearing debt X21 = cash to interests / cash margin Ib
APPENDIX G: The Firms Included in the Sample
TOL 31 Manufacture of Food, Beverages and Tobacco:
Huhtamäki, Rettig, Suomen Sokeri
TOL 32 Textile, Wearing Apparel and Leather Industries:
Finlayson, Lassila & Tikanoja, Tamfelt, Suomen Trikoo
TOL 34 Manufacture of Paper and Paper Products, Printing and
Publishing:
Enso-Gutzeit, Kajaani, Kaukas, Kemi, Kymi-Strömberg, Otava,
Wilh. Schauman, G.A. Serlachius, Tampella, Yhtyneet Paperitehtaat
TOL 36 Manufacture of Non-metallic Mineral Products, Except
Products of Petroleum and Coal:
Lohja, Partek
TOL 38 Manufacture of Fabricated Metal Products, Machinery and
Equipment:
Fiskars, Instrumentarium, Nokia, Rauma-Repola, W. Rosenlew,
Wärtsilä;
TOL 61 Wholesale Trade:
Ford, Kesko, Rake, Tamro, Talous-Osakekauppa
TOL 62 Retail Trade:
Stockmann
TOL 71 Transport and Storage:
Effoa
Other scientific publications by Timo Salmi in electronic format
itv(ät)uwasa.fi
pyo(ät)uwasa.fi
[ts(ät)uwasa.fi ]
[Photo ]
[Programs ]
[FAQs ]
[Research ]
[Lectures ]
[Acc&Fin
links ]
[Faculty ]
[University ]
[Revalidate]