The application of financial ratios in analysing nonprofit organisations

Historically ratios have been used to assess the financial standing of profit organisations. It would be expected the role which such ratios play in analysing nonprofit organisations would be considerably different due to the lack of profit motive. Many traditional ratios are based on profitability as a benchmark. The nonprofit sector plays an important role in society yet to date there has been no research carried out on financial statement analysis for nonprofit organisations in Australia. This paper examines ratios of a group of nonprofit organisations and assesses the applicability of the traditional profit-based ratios to nonprofit organisations. Financial statements of a sample of charities registered in Queensland are analysed. The traditional profitability, liquidity and financial stability ratios are analysed and calculated wherever practicable and compared to the typical benchmarks used in profit analysis.

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.

Tips and tricks about financial ratios: how to anticipate unpleasant surprises

Following recent accounting and ethical scandals within the Telecom Industry like Gowex case, old cards are laid on the table: what kind of management and control are we doing on our businesses and what use do we give to the specific tools we have at our disposition? There are indicators, that on a very specific, concise and accurate manner, aside from brief, allow us to analyze and capture the complexity of a business and also they constitute an important support when making optimal decisions. These instruments or indicators show, a priori, all relevant data from a purely economic perspective, while there also exist, the possibility of including factors that are not of this nature strictly. For instance, there are indicators that take into account the customer?s satisfaction, the corporate reputation among others. Both kind of performance indicators form, together, an integral dashboard while the pure economic side of it could be considered as a basic dashboard. Based on DuPont?s methodology, we will be able to calculate the ROI (Return on Investment) of a company from the disaggregation of very useful and much needed indicators like the ROE (Return on Equity) or the ROA (Return on Assets); thereby, we will be able to get to know, to control and, hence, to optimize the company?s leverage level, its liquidity ratio or its solvency ratio, among others; as well as the yield we will be able to obtain if our decisions and management are optimal related to the bodies of assets. Bear in mind and make the most of the abovementioned management tools and indicators that we have at our disposition, allow us to act knowing our path and taking full responsibility, as well as, to obtain the maximum planned benefits, instead of leaving them to be casual. We will be able to avoid errors that can lead the company to an unfortunate and non-desirable situation and, of course, we will detect, way in advance, the actual needs of the business in terms of accounting and financial sanitation before irreversible situations are reached.

An aggregate measure of financial ratios using a multiplicative DEA model

This paper examines the problems in the definition of the General Non-Parametric Corporate Performance (GNCP) and introduces a multiplicative linear programming as an alternative model for corporate performance. We verified and tested a statistically significant difference between the two models based on the application of 27 UK industries using six performance ratios. Our new model is found to be a more robust performance model than the previous standard Data Envelopment Analysis (DEA) model.

Financial Ratios: Perceptions of Lodging Industry General Managers, and Financial Executtves

Financial ratios are the most meaningful information in financial statements to executives and managers. The author analyzes the results of two surveys designed to rank the degree of importance and usefulness of these ratios to several user groups.

Not-for-profit ratios for financial resilience and internal accountability : a study of Australian international aid organisations

Not-for-profit (NFP) financial ratio research has focused primarily on organisational efficiency measurements for external stakeholders. Ratios that also capture information about stability, capacity (liquidity), gearing and sustainability, enable an assessment of financial resilience. They are thus valuable tools that can provide a framework of internal accountability between boards and management. The establishment of an Australian NFP regulator highlights the importance of NFP sustainability, and affirms the timeliness of this paper. We propose a suite of key financial ratios for use by NFP boards and management, and demonstrate its practical usefulness by applying the ratios to financial data from the 2009 reports of ACFID (Australian Council for International Development)-affiliated international aid organisations.

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.

Company financial performance: Does board size matter? Case of the EUROSTOXX50 index

[EN] This study analyzes the relationship between board size and economic-financial performance in a sample of European firms that constitute the EUROSTOXX50 Index. Based on previous literature, resource dependency and agency theories, and considering regulation developed by the OECD and European Union on the normative of corporate governance for each country in the sample, the authors propose the hypotheses of both positive linear and quadratic relationships between the researched parameters. Using ROA as a benchmark of financial performance and the number of members of the board as measurement of the board size, two OLS estimations are performed. To confirm the robustness of the results the empirical study is tested with two other similar financial ratios, ROE and Tobin s Q. Due to the absence of significant results, an additional factor, firm size, is employed in order to check if it affects firm performance. Delving further into the nature of this relationship, it is revealed that there exists a strong and negative relation between firm size and financial performance. Consequently, it can be asseverated that the generic recommendation one size fits all cannot be applied in this case; which conforms to the Recommendations of the European Union that dissuade using generic models for all countries.

Exploring profitability diversity through financial statement analysis

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Network externalities across financial institutions

We propose and estimate a financial distress model that explicitly accounts for the interactions or spill-over effects between financial institutions, through the use of a spatial continuity matrix that is build from financial network data of inter bank transactions. Such setup of the financial distress model allows for the empirical validation of the importance of network externalities in determining financial distress, in addition to institution specific and macroeconomic covariates. The relevance of such specification is that it incorporates simultaneously micro-prudential factors (Basel 2) as well as macro-prudential and systemic factors (Basel 3) as determinants of financial distress. Results indicate network externalities are an important determinant of financial health of a financial institutions. The parameter that measures the effect of network externalities is both economically and statistical significant and its inclusion as a risk factor reduces the importance of the firm specific variables such as the size or degree of leverage of the financial institution. In addition we analyze the policy implications of the network factor model for capital requirements and deposit insurance pricing.

On the utility of input selection and pruning for financial distress prediction models

Analyzes the use of linear and neural network models for financial distress classification, with emphasis on the issues of input variable selection and model pruning. A data-driven method for selecting input variables (financial ratios, in this case) is proposed. A case study involving 60 British firms in the period 1997-2000 is used for illustration. It is shown that the use of the Optimal Brain Damage pruning technique can considerably improve the generalization ability of a neural model. Moreover, the set of financial ratios obtained with the proposed selection procedure is shown to be an appropriate alternative to the ratios usually employed by practitioners.

Variable selection for financial distress classification using a genetic algorithm

This paper is concerned with the use of a genetic algorithm to select financial ratios for corporate distress classification models. For this purpose, the fitness value associated to a set of ratios is made to reflect the requirements of maximizing the amount of information available for the model and minimizing the collinearity between the model inputs. A case study involving 60 failed and continuing British firms in the period 1997-2000 is used for illustration. The classification model based on ratios selected by the genetic algorithm compares favorably with a model employing ratios usually found in the financial distress literature.