A comprehensive formal ranking of the popularity of financial ratios in multivariate modeling of corporate collapse

This paper provides a fonnal ranking of the popularity of financial ratios in modeling corporate collapse. The analysis identified 48 financial ratios and ranked them according to their usefulness as portrayed in 53 studies that have utilized such ratios in modeling corporate collapse. The methodologies adopted in those studies are predominantly of the "multivariate" type. The 53 studies extend from 1966 to 2002, inclusive.

Connection between commonly used financial ratios and misrepresentation of financial statements of collapsed corporations

This paper unravels dynamic and intriguing shifts in the use of financial ratios in signaling corporate collapse. An empirical examination of the anecdotal evidences from notable recent corporate collapses coupled with the short-lived usefulness of financial ratios in various prediction models suggest that companies(1) that deliberately misrepresent their financial statements may have taken cues from the ratios that are commonly investigated. This proposition is supported by an extensive examination of over 50 studies conducted between 1968 and 2002. The erosion in the reliability of numbers in financial statements has led to significant distortions in the predictive power of financial ratios when used in signaling corporate collapse. Recent collapses such as Parmalat in Europe, Enron and WorldCom in the U.S. and HIH in Australia, present yet another reminder that financial statement items are being misrepresented. These are all large corporations with well-established household names, and are for sure closely monitored by financial communities around the globe. Nevertheless, a common thread seems to link the collapse of these companies: none of these collapses were foreseen by credit rating agencies or foretold by the widely accepted bankruptcy prediction models. Why? This paper attempts to use some anecdotal evidence in order to provide logical explanations to the existence of such a common thread. It argues that there appears to be anecdotal evidence to suggest that directors of publicly listed companies that have collapsed may have deliberately misrepresented financial statement items.

Connection between commonly used financial ratios and misrepresentation of financial statements of collapsed corporations

This paper unravels dynamic and intriguing shifts in the use of financial ratios in signaling corporate collapse. An empirical examination of the anecdotal evidences from notable recent corporate collapses coupled with the short-lived usefulness of financial ratios in various prediction models suggest that companies(1) that deliberately misrepresent their financial statements may have taken cues from the ratios that are commonly investigated. This proposition is supported by an extensive examination of over 50 studies conducted between 1968 and 2002. The erosion in the reliability of numbers in financial statements has led to significant distortions in the predictive power of financial ratios when used in signaling corporate collapse. Recent collapses such as Parmalat in Europe, Enron and WorldCom in the U.S. and HIH in Australia, present yet another reminder that financial statement items are being misrepresented. These are all large corporations with well-established household names, and are for sure closely monitored by financial communities around the globe. Nevertheless, a common thread seems to link the collapse of these companies: none of these collapses were foreseen by credit rating agencies or foretold by the widely accepted bankruptcy prediction models. Why? This paper attempts to use some anecdotal evidence in order to provide logical explanations to the existence of such a common thread. It argues that there appears to be anecdotal evidence to suggest that directors of publicly listed companies that have collapsed may have deliberately misrepresented financial statement items.

Financial fraud and the use of ratios in corporate collapse prediction models

This paper highlights the prevalence and extent of financial fraud amongst collapsed corporations. In doing so, it examines the recent spectacular corporate collapses of Parmalat in Europe, Enron and WoridCom in the USA and HIH in Australia. A new methodology that provides empirical evidence to the financial fraud claims found in the literature, is then put forward. The proposed methodology argues that if financial fraud was a possibility amongst collapsed corporations, then two premises ought to be observed in the literature on ratio based multivariate modelling for predicting corporate collapse. First, in the absence of financial fraud, we expect the models to consistently predict corporate collapse with a high degree of accuracy; particularly, as one approaches the incident of collapse. Second, if financial fraud takes place and statement figures are distorted, then we expect the financial ratios, which are the predictor variables in these models, to lose relevance and therefore their use in models will be short-lived. Empirical support from Hossari and Rahman (2004) and Hossari and Rahman (2005) is presented as evidence to the two premises.

Empirical evidence from the corporate collapse literature suggesting re-examination of accounting standards in relation to valuation of assets

This paper examines the recent spectacular corporate collapses of Parmalat in Europe, Enron and WorldCom in the USA and HIH in Australia and argues for a re-examination of corporate governance regulations, particularly in relation to accounting standards regarding the valuation of assets. The recommendation that is put forward in this regard is based upon empirical evidence arising from further examination of the empirical results in (Hossari and Rahman, 2004). Specifically, the recommendation is based upon the realization that, among the 48 financial ratios across the 50-plus refereed studies, five financial ratios, all of which contained assets as one of the variables, were a relatively robust indicator of corporate collapse. The five ratios are: Net Income/Total Assets, Current Assets/Current Liabilities, Total Liabilities/Total Assets, Working Capital/Total Assets, and Earnings Before Interest and Taxes/Total Assets. This paper suggests that it's not the failure of the corporate collapse prediction models, rather it's the erosion of the reliability of some key input data, namely assets and the valuation thereof, that is largely responsible for the apparent failure of these models in capturing impending collapses, such as those that we witnessed in the recent past. Such empirical findings support the argument that assets are soft targets for misrepresentation, because of the leeway granted in accounting standards with regards to their valuation.

Methodological shifts in ratio-based modelling of corporate collapse

The year 1968 saw a major shift from univariate to multivariate methodological approaches to ratio-based modelling of corporate collapse. This was facilitated by the introduction of a new statistical tool called Multiple Discriminant Analysis (MDA). However, it did not take long before other statistical tools were developed. The primary objective for developing these tools was to enable deriving models that would at least do as good a job asMDA, but rely on fewer assumptions. With the introduction of new statistical tools, researchers became pre-occupied with testing them in signalling collapse. lLTUong the ratio-based approaches were Logit analysis, Neural Network analysis, Probit analysis, ID3, Recursive Partitioning Algorithm, Rough Sets analysis, Decomposition analysis, Going Concern Advisor, Koundinya and Purl judgmental approach, Tabu Search and Mixed Logit analysis. Regardless of which methodological approach was chosen, most were compared to MDA. This paper reviews these various approaches. Emphasis is placed on how they fared against MDA in signalling corporate collapse.

A dynamic ratio-based model for signalling corporate collapse

The recognition of behavioural elements in finance has caused major shifts in the analytic framework pertaining to ratio-based modeling of corporate collapse. The modeling approach so far has been based on the classical rational theory in behavioural economics, which assumes that the financial ratios (i.e., the predictors of collapse) are static over time. The paper argues that, in the absence of rational economic theory, a static model is flawed, and that a suitable model instead is one that reflects the heuristic behavioural framework, which is what characterises behavioural attributes of company directors and in turn influences the accounting numbers used in calculating the financial ratios. This calls for a dynamic model: dynamic in the sense that it does not rely on a coherent assortment of financial ratios for signaling corporate collapse over multiple time periods. This paper provides empirical evidence, using a data set of Australian publicly listed companies, to demonstrate that a dynamic model consistently outperforms its static counterpart in signaling the event of collapse. On average, the overall predictive power of the dynamic model is 86.83% compared to an average overall predictive power of 69.35% for the static model.

Changing governance mechanisms and its impact on Australian Building Societies' performance

This paper examines the relation between the governance mechanism (ownership structure) and performance of Australian building societies. Financial performance measures, provided by financial ratios of the major mutual building societies in Australia are used to explore their behaviour under different governance structures in the 1980s and 1990s. The theoretical and empirical literature has suggested that mutual deposit-taking institutions should have lower profitability and higher operating expenses than their publicly listed counterparts. Accounting ratios are observed over time to investigate if governance change in mutual deposit-taking organizations accounted for any discernable differences in profitability and cost efficiency pre- and postdemutualisation.

Does organizational structure matter? The behaviour of Australian Building Societies pre-and post-demutualization

Financial performance measures, provided by accounting-based financial ratios, of the major mutual building societies in Australia are used to explore their behaviour pre-and post-demutualization in the 1980s and 1990s. The theoretical and empirical literature has suggested that mutual deposit-taking institutions would have lower profitability and higher operating expenses than their publicly listed counterparts. Common accounting ratios are observed over time to investigate if ownership change in a mutual deposit-taking organization accounted for any discernable differences in profitability and cost efficiency of the firms after conversion.

A heuristic framework for ratio-based modelling of corporate collapse

This paper draws on empirical evidence to demonstrate that a heuristic framework signals collapse with significantly higher accuracy than the traditional static approach. Using a sample of 494 US publicly listed companies comprising 247 collapsed matched with 247 financially healthy ones, a heuristic framework is decisively superior the closer one gets to the event of collapse, culminating in 12.5% more overall accuracy than a static approach during
the year of collapse. An even more dramatic improvement occurs in relation to reduction of Type I error, with a heuristic framework delivering an improvement of 66.7% over its static counterpart.

Organisation change and its impact on Australian Building Societies' performance

The paper examines the relation between changing ownership structure and performance of Australian building societies. An analysis and discussion of the theories of organizational development and change is undertaken to explore the mutual building societies' motivation for change. The financial performance measures, provided by financial ratios of the major mutual building societies in Australia, are examined to assess the behaviour of building societies under different governance structures in the 1980s and 1990s. The theoretical and empirical literature has suggested that mutual deposit-taking institutions should have lov^^er profitability and higher operating expenses than their publicly listed counterparts. Accounting ratios are observed over time to investigate if governance change in mutual deposit-taking organizations accounted for any discernable differences in profitability and cost efficiency pre- and post- demutualization. The study finds support for the contention that demutualized building societies will have higher profitability and lower costs than their mutual counterparts. The study is confined to investigation of the six largest building societies that undertook the demutualization process. It could he extended to the entire building society sector. The results have implications for investors, managers and 'ovraers' of firms that retain their mutual structure, suggesting the demutualization vnû benefit these groups. There is no study that compares mutual deposit-taking institutions pre- and post-conversion in Australia.

Optimising errors in signaling corporate collapse using MCCCRA

Purpose – The purpose of this paper is to put forward an innovative approach for reducing the variation between Type I and Type II errors in the context of ratio-based modeling of corporate collapse, without compromising the accuracy of the predictive model. Its contribution to the literature lies in resolving the problematic trade-off between predictive accuracy and variations between the two types of errors.

Design/methodology/approach – The methodological approach in this paper – called MCCCRA – utilizes a novel multi-classification matrix based on a combination of correlation and regression analysis, with the former being subject to optimisation criteria. In order to ascertain its accuracy in signaling collapse, MCCCRA is empirically tested against multiple discriminant analysis (MDA).

Findings – Based on a data sample of 899 US publicly listed companies, the empirical results indicate that in addition to a high level of accuracy in signaling collapse, MCCCRA generates lower variability between Type I and Type II errors when compared to MDA.

Originality/value – Although correlation and regression analysis are long-standing statistical tools, the optimisation constraints that are applied to the correlations are unique. Moreover, the multi-classification matrix is a first in signaling collapse. By providing economic insight into more stable financial modeling, these innovations make an original contribution to the literature.

Modelling SME credit risk : a Thai empirical evidence

This paper develops and tests a model to predict small and medium enterprise (SME) financial distress based on empirical evidence from Thailand. A sample comprising 198 financial statements of non-financially distressed and 68 statements of financially distressed SMEs were used. A parametric t-test was conducted to establish differences between financial characteristics of the two groups of SMEs.

Results show statistically significant differences (t values significant at .001) between the two groups of SMEs in the financial ratios used for the study. Discriminant analysis was then conducted to develop a model for predicting the likelihood of an SME experiencing financial distress.

The model hits an accuracy level of 97%, which compares favourably with the probability of accurate classification by chance (i.e., 65% after adjusting for the unequal sample sizes of the two groups of SMEs). A test of the model with a new sample shows the validity of the model beyond the original sample, confirming that Thai SME financial distress is amenable to prediction to a statistically significant extent. The model is expected to serve SME managers and creditors in assessing financial health of SMEs before making important decisions. The results are also expected to inform policymakers in formulating economic policies concerning SMEs.

Multiple states of financially distressed companies: Tests using a competing-risks model

This study examines the determinants of multiple states of financial distress by applying a competing-risks model. It investigates the effect of financial ratios, market-based variables and company-specific variables, including company age, size and squared size on three different states of corporate financial distress: active companies; distressed external administration companies; and distressed takeover, merger or acquisition companies. A sample of 1,081 publicly listed Australian non-financial companies over the period 1989 to 2005 using a competing-risks model is used to determine the possible differences in the factors of entering various states of financial distress. It is found that specifically, distressed external administration companies have a higher leverage, lower past excess returns and a larger size; while distressed takeover, merger or acquisition companies have a lower leverage, a higher capital utilisation efficiency and a larger size compared to active companies. Comparing the results from both the single-risk model and the competing-risks model reveals the need to distinguish between financial distress states.

Stock return predictability and determinants of predictability and profits

We examine stock return predictability for India and find strong evidence of sectoral return predictability over market return predictability. We show that mean-variance investors make statistically significant and economically meaningful profits by tracking financial ratios. For the first time in this literature, we examine the determinants of time-varying predictability and mean-variance profits. We show that both expected and unexpected shocks emanating from most financial ratios explain sectoral return predictability and profits. These are fresh contributions to the understanding of asset pricing.