Detecting financial distress

This paper examines two types of statistical tests, which are multiple discriminant analysis (MDA) and the logit model to detect financially distressed companies. Comparison between the two statistical tests is implemented to identiy factors that could differentiate financially distressed companies from the healthy company. Among the fifteen explanators, M D A shows that the current ratios, net income to total asset, and sales to current asset, are the indicators of financially distressed companies. Other than net income to total asset, the logit model provides two different ratios which are shareholders’filnd to total liabilities, and cash flow from financing to total liabilities, to identi@ financially distressed companies. It zuasfound that the logit model could accurately predict 91.5% of the estimation sample and 90% of the holdout sample whereas the discriminant model shows an overall accuracy rate of 84.5% and 80% for the estimatiorl and the holdout sample respectively

Financial crises and bank failures: a review of prediction methods

In this article we analyze financial and economic circumstances associated with the U.S. subprime mortgage crisis and the global financial turmoil that has led to severe crises in many countries. We suggest that the level of cross-border holdings of long-term securities between the United States and the rest of the world may indicate a direct link between the turmoil in the securitized market originated in the United States and that in other countries. We provide a summary of empirical results obtained in several Economics and Operations Research papers that attempt to explain, predict, or suggest remedies for financial crises or banking defaults; we also extensively outline the methodologies used in them. The intent of this article is to promote future empirical research for preventing financial crises.Subprime mortgage ; Financial crises

The importance of a better design of conditionality for improving implementation of World Bank-supported reforms: The case of Sub-Saharan African countries

Some recent empirical research suggests that the implementation of policy reforms is largely dependent on domestic political economy factors. This finding is taken to suggest that aid and adjustment lending should only be provided to those countries that, on the basis of certain characteristics, are more likely to implement policy reform. We put these issues to scrutiny by employing a sophisticated World Bank dataset to explain Sub-Saharan African programme countries’ compliance record. Our empirical results highlight the role of a country’s income status, economic performance and political stability during the programme, the external economic environment, the size of financial support for the reform programme, and initial macroeconomic conditions. These results contradict the evidence underpinning the selectivity approach to policy-based lending and suggest that poor compliance is not the result of low implementation capacity and poor institutional quality alone but also a consequence of poor policy design.

Accounting information and the prediction of farm viability

Until recently farm management made little use of accounting and agriculture has been largely excluded from the scope of accounting standards. This article examines the current use of accounting in agriculture and points the need to establish accounting standards for agriculture. Empirical evidence shows that accounting can make a significant contribution to agricultural management and farm viability and could also be important for other agents involved in agricultural decision making. Existing literature on failure prediction models and farm viability prediction studies provide the starting point for our research, in which two dichotomous logit models were applied to subsamples of viable and unviable farms in Catalonia, Spain. The first model considered only non-financial variables, while the other also considered financial ones. When accounting variables were added to the model, a significant reduction in deviance was observed.Accounting, agriculture, farm distress, viability, prediction

Financial crises and bank failures: a review of prediction methods

In this article we provide a summary of empirical results obtained in several economics and operations research papers that attempt to explain, predict, or suggest remedies for financial crises or banking defaults, as well as outlines of the methodologies used. We analyze financial and economic circumstances associated with the US subprime mortgage crisis and the global financial turmoil that has led to severe crises in many countries. The intent of the article is to promote future empirical research that might help to prevent bank failures and financial crises.financial crises; banking failures; operations research; early warning methods; leading indicators; subprime markets

Statistical modelling to predict corporate default for Brazilian companies in the context of Basel II using a new set of financial ratios

This paper deals with statistical modelling to predict failure of Brazilian companies in the light of the Basel II definition of default using a new set of explanatory variables. A rearrangement in the official format of the Balance Sheet is put forward. From this rearrangement a framework of complementary non-conventional ratios is proposed. Initially, a model using 22 traditional ratios is constructed. Problems associated with multicollinearity were found in this model. Adding a group of 6 non-conventional ratios alongside traditional ratios improves the model substantially. The main findings in this study are: (a) logistic regression performs well in the context of Basel II, yielding a sound model applicable in the decision making process; (b) the complementary list of financial ratios plays a critical role in the model proposed; (c) the variables selected in the model show that when current assets and current liabilities are split into two sub-groups - financial and operational - they are more effective in explaining default than the traditional ratios associated with liquidity; and (d) those variables also indicate that high interest rates in Brazil adversely affect the performance of those companies which have a higher dependency on borrowing

Identification of relevant predictors of loan default using the Elastic Net model

The timely prediction of loan default plays an important role in lending decisions and monitoring loans. However, there has been little development of models for the selection of relevant variables for the prediction of loan default. This study identifies financial and economic indicators for the forward-looking prediction of loan default by the application of a penalised regression approach, namely the Elastic Net model. The study employs a sample of US firms with 162 loan default events in total between 1998 and 2013. The sample is sub-divided to form a Test sample and two holdout samples: one drawn from the same period as the Test sample; and one drawn from a subsequent period. The sample of non-defaulting firms is constructed using prior probabilities based on the bond default rate for each year. The 278 potential variables, including the ten economic indicators and 268 financial ratios or summary indicators, are regularised with the application of the Elastic Net model. This process results in the extraction of the ten predictor variables, thus identified as relevant to distinguishing between defaulting and non-defaulting firms. Only one economic indicator, the interest rate, is identified as relevant to the prediction of loan default. The prediction-usefulness of identified predictor variables are tested using the two most widely used conventional prediction models, multiple discriminant analysis (MDA) and logistic regression (Logit). The resulting MDA and Logit models are compared with Altman’s Z-score model and Ohlson’s O-score model, respectively. Both the Elastic Net prediction models provide more logical explanations of the distinctive characteristics of loan defaulting firms than the Altman’s Z-score and Ohlson’s O-score models. The Elastic Net prediction models outperform the Altman’s Z-score and Ohlson’s O-score models in the accuracy of the Type I, the Type II and the overall classification. When applied to a holdout samples within and outside the same periods, the prediction accuracy of the Elastic Net models is maintained for both defaulting and non-defaulting firms. This thesis contributes to the loan default literature by introducing the Elastic Net model for variable selection which enhances the predictive ability of the loan default prediction model. The findings of this thesis are potentially useful to financial institutions. Identification of financial and economic predictor variables of loan default can also facilitate assessment of the credit risk of loan applicants. The findings of this thesis may also facilitate better loan default prediction for purposes of monitoring loans. Lastly, the identification of relevant predictor variables may be useful for the classification of loans in the application of the expected loss model in the preparation of financial statements.Thesis (Ph.D.) -- University of Adelaide, Business School, 201

A Study Of Employee Perceptions About Performance Appraisal At Transnet Engineering, South Africa

Transnet Engineering is a division of Transnet, which is a key South African state owned enterprise that is responsible for providing railroad, freight and logistics services to South African and international business enterprises. Transnet Engineering is located at Koedoespoort, just outside Pretoria, South Africa. This manuscript is a result of data gathered from 198 employees of Transnet Engineering as part of an attempt made by the company to describe and quantify the perception held by employees of Transnet Engineering on the degree to which the performance of appraisal system used by the company for performance appraisal was suitable enough for its intended purpose. The perception of employees was measured by using a benchmark defined by Pichler (2012) in which similar measurements were made under near-identical circumstances. All measurements were taken based on a standardised, validated and pre-tested instrument. Pearson’s two-by-two chi-squared tests of associations, discriminant analysis and logit regression were used for analyses. The study found that about 63% of participants were happy with the performance appraisal system used by the company, whereas about 37% of participants held a negative perception. The results confirmed that the perception of employees about the performance appraisal system used at Transnet Engineering was affected by the perception of employees on fairness, and the assessment of performance of employees based on key performance indicators. Findings obtained from the study are quite relevant and valuable to all other South African state owned enterprises

Evaluating the Risk of Insolvency

3noThis paper analyzes the risk of bankruptcy of an Italian manufacturing firms data set from the Marche region that has the greater share of persons employed in industry as a proportion of those employed in the non-financial business economy in the country. This evidence is more important if we consider that in Europe only 17% of regions reaches more than 40% of its employed in industry. Moreover, the considered firms are excellent in terms of their size in relation to turnover and employment and are representative examples of what in Italy is known as “fourth capitalism”. Alternative default probability predictive methods have been tested on the accounting data from these statistical units. Specifically, after testing the adequacy of Altman’s Z-score model, we attempt to solve its well known limit due to the consideration of the same number of defaulting and non-defaulting firms in the sample, up till the selection of new explicative variables related to enterprise’s bankruptcy risk and an alternative fixed effects panel data approach to estimate the model parameters. So, we progressively obtain a considerable improvement in the overall forecasting error.reservedmixedM. MARCONI; A.G. QUARANTA; S. TARTUFOLIMarconi, Mauro; Quaranta, ANNA GRAZIA; S., Tartufol