Aggregate economy risk and company failure: An examination of UK quoted firms in the early 1990s

Considerable attention has been directed in the recent finance and economics literature to issues concerning the effects on company failure risk of changes in the macroeconomic environment. This paper examines the accounting ratio-based and macroeconomic determinants of insolvency exit of UK large industrials during the early 1990s with a view to improve understanding of company failure risk. Failure determinants are revealed from estimates based on a cross-section of 369 quoted firms, which is followed by an assessment of predictive performance based on a series of time-to-failure-specific logit functions, as is typical in the literature. Within the traditional for cross-sectional data studies framework, a more complete model of failure risk is developed by adding to a set of traditional financial statement-based inputs, the two variables capturing aggregate economy risk - one-year lagged, unanticipated changes in the nominal interest rate and in the real exchange rate. Alternative estimates of prediction error are obtained, first, by analytically adjusting the apparent error rate for the downward bias and, second, by generating holdout predictions. More complete, augmented with the two macroeconomic variables models demonstrate improved out-ofestimation- sample classificatory accuracy at risk horizons ranging from one to four years prior to failure, with the results being quite robust across a wide range of cutoff probability values, for both failing and nonfailed firms. Although in terms of the individual ratio significance and overall predictive accuracy, the findings of the present study may not be directly comparable with the evidence from prior research due to differing data sets and model specifications, the results are intuitively appealing. First, the results affirm the important explanatory role of liquidity, gearing, and profitability in the company failure process. Second, the findings for the failure probability appear to demonstrate that shocks from unanticipated changes in interest and exchange rates may matter as much as the underlying changes in firm-specific characteristics of liquidity, gearing, and profitability. Obtained empirical determinants suggest that during the 1990s recession, shifts in the real exchange rate and rises in the nominal interest rate, were associated with a higher propensity of industrial company to exit via insolvency, thus indicating links to a loss in competitiveness and to the effects of high gearing. The results provide policy implications for reducing the company sector vulnerability to financial distress and failure while highlighting that changes in macroeconomic conditions should be an important ingredient of possible extensions of company failure prediction models

Aggregate economy risk and company failure: An examination of UK quoted firms

Considerable attention has been directed in the recent finance and economics literature to issues concerning the effects on company failure risk of changes in the macroeconomic environment. This paper examines the accounting ratio-based and macroeconomic determinants of insolvency exit of UK large industrials during the early 1990s with a view to improve understanding of company failure risk. Failure determinants are revealed from estimates based on a cross-section of 369 quoted firms, which is followed by an assessment of predictive performance based on a series of time-to-failure-specific logit functions, as is typical in the literature. Within the traditional for cross-sectional data studies framework, a more complete model of failure risk is developed by adding to a set of traditional financial statement-based inputs, the two variables capturing aggregate economy risk - one-year lagged, unanticipated changes in the nominal interest rate and in the real exchange rate. Alternative estimates of prediction error are obtained, first, by analytically adjusting the apparent error rate for the downward bias and, second, by generating holdout predictions. More complete, augmented with the two macroeconomic variables models demonstrate improved out-ofestimation- sample classificatory accuracy at risk horizons ranging from one to four years prior to failure, with the results being quite robust across a wide range of cut-off probability values, for both failing and non-failed firms. Although in terms of the individual ratio significance and overall predictive accuracy, the findings of the present study may not be directly comparable with the evidence from prior research due to differing data sets and model specifications, the results are intuitively appealing. First, the results affirm the important explanatory role of liquidity, gearing, and profitability in the company failure process. Second, the findings for the failure probability appear to demonstrate that shocks from unanticipated changes in interest and exchange rates may matter as much as the underlying changes in firm-specific characteristics of liquidity, gearing, and profitability. Obtained empirical determinants suggest that during the 1990s recession, shifts in the real exchange rate and rises in the nominal interest rate, were associated with a higher propensity of industrial company to exit via insolvency, thus indicating links to a loss in competitiveness and to the effects of high gearing. The results provide policy implications for reducing the company sector vulnerability to financial distress and failure while highlighting that changes in macroeconomic conditions should be an important ingredient of possible extensions of company failure prediction models

Bankruptcy prediction models in Galician companies. Application of parametric methodologies and artificial intelligence

This paper provides empirical evidence on the prediction of non-financial companies’ failure. We develop several models to evaluate failure risk in companies from Galicia. We check the predictive ability of parametric models (multivariate discriminant, logit) compared with auditor’s report. Models are based on relevant financial variables and ratios, in financial logic and a in financial distress situations. We examine a random sample of companies in cross-sectional perspective, checking the predictive capacity at any given time, also verifying is models give reliable signals to anticipate future events of financial distress. Findings suggest that our models are extremely effective when applied in medium and long term, and that they offer higher predictive capabilities than external audit.peer-reviewe

Consensus on circulatory shock and hemodynamic monitoring. Task force of the European Society of Intensive Care Medicine.

OBJECTIVE: Circulatory shock is a life-threatening syndrome resulting in multiorgan failure and a high mortality rate. The aim of this consensus is to provide support to the bedside clinician regarding the diagnosis, management and monitoring of shock. METHODS: The European Society of Intensive Care Medicine invited 12 experts to form a Task Force to update a previous consensus (Antonelli et al.: Intensive Care Med 33:575-590, 2007). The same five questions addressed in the earlier consensus were used as the outline for the literature search and review, with the aim of the Task Force to produce statements based on the available literature and evidence. These questions were: (1) What are the epidemiologic and pathophysiologic features of shock in the intensive care unit ? (2) Should we monitor preload and fluid responsiveness in shock ? (3) How and when should we monitor stroke volume or cardiac output in shock ? (4) What markers of the regional and microcirculation can be monitored, and how can cellular function be assessed in shock ? (5) What is the evidence for using hemodynamic monitoring to direct therapy in shock ? Four types of statements were used: definition, recommendation, best practice and statement of fact. RESULTS: Forty-four statements were made. The main new statements include: (1) statements on individualizing blood pressure targets; (2) statements on the assessment and prediction of fluid responsiveness; (3) statements on the use of echocardiography and hemodynamic monitoring. CONCLUSIONS: This consensus provides 44 statements that can be used at the bedside to diagnose, treat and monitor patients with shock

Predicting The Financial Failure Of Retail Companies In The United States

Predicting the financial failure of companies using financial ratios is a topic that has been explored in various ways for many years, and the current economic climate suggests that these models may still be more useful than ever.  Various financial ratios and bankruptcy prediction methods have been used in order to try to find the most accurate prediction model possible.  With historically successful retailers, like Sears, Kmart and JCPenney, struggling in recent years, predicting the future of retailers has become even more important.Therefore, this paper focuses specifically on the application of a failure prediction model to companies from the retail industry.  Logistic regressions are used in this study in order to attempt to predict which companies are likely to fail.  The sample for this study includes publicly traded United States companies from the retail industry, and data is collected from the COMPUSTAT database for the period from 2005-2012.  Based on prior studies, the author hypothesizes that companies are most likely to fail if they are unprofitable, highly leveraged, and having cash flow problems.  As expected, the results demonstrate that smaller retail companies with fewer employees are more likely to fail.  The results also provide strong evidence that firms with lower cash to current liability ratios, lower cash flow margins, and higher debt to equity ratios are more likely to file for bankruptcy

Importancia de la información contable para el análisis y predicción de la viabilidad de las explotaciones agrícolas

Spanish and Western agriculture show a continuous decrease in the number of farms. One of the main factors for this trend is the economic non-viability of many of the existing farms. In addition, interrelationship of agriculture with other industries is growing. Thus, policymakers, banks, creditors and other stakeholders are interested in predicting farm viability. The aim of this paper is to provide empirical evidence that the use of accounting-based information could significantly improve understanding and prediction of various degrees of farm viability. Two multinomial logit models were applied to a sample of farms of Catalonia, Spain. One model included non-accounting-based variables, while the other also considered accounting-based variables. It was found that accounting added significant information to predict various degrees of farm viability. This finding reveals, both the need of encouraging the little existing use of accounting by farms and to develop appropriate accounting standards for agriculture.Accounting, agriculture, farm, non-viability, failure prediction models