Comparative analysis between statistical and artificial intelligence models in business failure prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

Survival Analysis Employed in Predicting Corporate Failure: A Forecasting Model Proposal

In face of the current economic and financial environment, predicting corporate bankruptcy is arguably a phenomenon of increasing interest to investors, creditors, borrowing firms, and governments alike. Within the strand of literature focused on bankruptcy forecasting we can find diverse types of research employing a wide variety of techniques, but only a few researchers have used survival analysis for the examination of this issue. We propose a model for the prediction of corporate bankruptcy based on survival analysis, a technique which stands on its own merits. In this research, the hazard rate is the probability of ‘‘bankruptcy’’ as of time t, conditional upon having survived until time t. Many hazard models are applied in a context where the running of time naturally affects the hazard rate. The model employed in this paper uses the time of survival or the hazard risk as dependent variable, considering the unsuccessful companies as censured observations.

Comparative Analysis between Statistical and Artificial Intelligence Models in Business Failure Prediction

A growing number of predicting corporate failure models has emerged since 60s. Economic and social consequences of business failure can be dramatic, thus it is not surprise that the issue has been of growing interest in academic research as well as in business context. The main purpose of this study is to compare the predictive ability of five developed models based on three statistical techniques (Discriminant Analysis, Logit and Probit) and two models based on Artificial Intelligence (Neural Networks and Rough Sets). The five models were employed to a dataset of 420 non-bankrupt firms and 125 bankrupt firms belonging to the textile and clothing industry, over the period 2003–09. Results show that all the models performed well, with an overall correct classification level higher than 90%, and a type II error always less than 2%. The type I error increases as we move away from the year prior to failure. Our models contribute to the discussion of corporate financial distress causes. Moreover it can be used to assist decisions of creditors, investors and auditors. Additionally, this research can be of great contribution to devisers of national economic policies that aim to reduce industrial unemployment.

How logrolling can explain the failure of the government coalition in Brazil

This article presents an analysis of the behavior of federal representatives in the Brazilian House of Representatives between 1995 and 1998, when a series of constitutional amendments were presented by the president to be voted on by Congress. The objective is to show that the lack of a stable government coalition resulted in costs to society that were not anticipated by the government. The study argues that a logroll - a trade of votes - was the strategy used by the government in order to guarantee the number of votes necessary to approve the amendments. This strategy created a vicious system in which representatives would only vote with the government if they had benefits in return.

Shear-induced lamellar ionic liquid-crystal foam

n a recent paper we reported an experimental study of two N-alkylimidazolium salts. These ionic compounds exhibit liquid crystalline behaviour with melting points above 50 degrees C in bulk. However, if they are sheared, a (possibly non-equilibrium) lamellar phase forms at room temperature. Upon shearing a thin film of the material between microscope slides, textures were observed that are strikingly similar to liquid (wet) foams. The images obtained from polarising optical microscopy (POM) were found to share many of the known quantitative properties of a two-dimensional foam coarsening process. Here we report an experimental study of this foam using a shearing system coupled with POM. The structure and evolution of the foam are investigated through the image analysis of time sequences of micrographs obtained for well-controlled sets of physical parameters (sample thickness, shear rate and temperature). In particular, we find that there is a threshold shear rate below which no foam can form. Above this threshold, a steady-state foam pattern is obtained where the mean cell area generally decreases with increasing shear rate. Furthermore, the steady-state internal cell angles and distribution of the cell number of sides deviate from their equilibrium (i.e. zero-shear) values.

Health related quality of life in patients with refractory chronic heart failure undergoing cardiac resynchronization: type of therapeutic response

The benefits of cardiac resynchronization therapy (CRT) in the health-related quality of life (HRQL) are largely demonstrated in selected patients with severe congestive heart failure (CHF). However, the differences between responders and non-responders, with regard to the effect of CRT in the various dimensions that constitute HRQL are still a matter of discussion. Objective: To evaluate the impact of CRT on the HRQL of patients with CHF refractory to optimal pharmacological therapy, within 6 months after CRT. Methods: 43 patients, submitted to successful implantation of CRT, were evaluated in hospital just before intervention and in the outpatient clinic within 6 months after CRT. HRQL was analyzed based on the Kansas City Cardiomyopathy Questionnaire (KCCQ). Patients were classified as super-responders (ejection fraction of left ventricle - LVEF - ≥45% post-CRT), n=15, responders (sustained improvement in functional class and LVEF increased by 15%), n=19, and non-responders (no clinical or LVEF improvement), n=9. Results: In the group of super-responders, CRT was associated with an improvement in HRQL for the various fields and sums assessed (ρ<0.05); in responders, CRT has been associated with an improvement of HRQL in the various fields and sums, except in the self-efficacy dimension (ρ<0.05); in non-responders, CRT was not associated with improvement of HRQL. Conclusion: In a population with severe CHF undergoing CRT, the patients with clinical and echocardiographic positive response, obtained a favorable impact in all dimensions of HRQL, while the group without response to CRT showed no improvement. These data reinforces the importance of HRQL as a multidimensional tool for assessment of benefits in clinical practice.

Evaluating the quality of life in patients with refractory chronic heart failure undergoing cardiac resynchronization regarding the type of therapeutic response

The benefits of cardiac resynchronization therapy (CRT) in the quality of life have been largely demonstrated in selected patients with severe congestive heart failure (CHF). However, the differences between responders and non-responders, with regard to the effect of CRT in the various dimensions of quality of life is still a matter of discussion. Objective: to evaluate the impact of CRT on the quality of life of patients with CHF refractory to optimal pharmacological therapy, within 6 months after CRT.

Relation of happiness, hope and affection with quality of life in patients with heart failure

Introduction: Meeting the actual role of positive psychology, begins to be recognized the relation of positive variables with health. Objective: To know the relation of happiness, hope and affection with quality of life in individuals with heart failure. Population and Methodology: 128 individuals with heart failure, 98 men and 30 women, 61.9±12,1 years of age, 6,6±3,9 years in school and 74,2% retired because of this disease. 56,3% were in Class III of New York Heart Association, with poor left ventricular ejection fraction (25,3±6,2%). The clinical history was of 9,4±8,5 years for this heart disease and had at least one hospitalization due to heart failure with 51,6% having ischemic heart disease.

Happiness, hope and affection as predictors of quality of life and functionality of individuals with heart failure at 3 month follow up

Introduction: Meeting the actual role of positive psychology, begins to be recognized the contribution of positive variables in health outcomes. Objective: To know the contribution of happiness, hope and affection individually and as a whole in the quality of life and functionality of individuals with heart failure. Population and Methodology: 128 individuals with heart failure, 98 men and 30 women, 61.9±12,1 years of age, 6,6±3,9 years of school and 74,2% retired because of this disease. 56,3% were in Class III of New York Heart Association, with poor left ventricular ejection fraction (25,3±6,2%). The clinical history was of 9,4±8,5 years for this heart disease and had at least one hospitalization due to heart failure with 51,6% having ischemic heart disease.

Quality of life in dilated cardiomyopathy with refractory chronic heart failure undergoing devices implantation

Heart failure is the final stage of most of cardiac diseases. It is a complex syndrome in which the patients should have the following features: symptoms of heart failure, typically shortness of breath at rest or during exertion, and/or fatigue; signs of fluid retention such as pulmonary congestion or ankle swelling; and objective evidence of an abnormality of the structure or function of the heart at rest. This progressive syndrome as a high incidence and prevalence and poor prognosis: four-year mortality is around 50% with 40% of the patients admitted to hospital dying or readmitted within a year. With ageing, many patients will develop chronic heart failure, which, because of its symptoms, patient’s awareness of their risk of dying, and the effects of therapy, together with frequent hospitalizations, has considerable impact on patient’s health-related quality of life.

A model to forecast financial failure, in non financial galician SMES

We are concerned with providing more empirical evidence on forecast failure, developing forecast models, and examining the impact of events such as audit reports. A joint consideration of classic financial ratios and relevant external indicators leads us to build a basic prediction model focused in non-financial Galician SMEs. Explanatory variables are relevant financial indicators from the viewpoint of the financial logic and financial failure theory. The paper explores three mathematical models: discriminant analysis, Logit, and linear multivariate regression. We conclude that, even though they both offer high explanatory and predictive abilities, Logit and MDA models should be used and interpreted jointly.

Dynamic power- and failure-aware cloud resources allocation for Sets of independent tasks

Cloud computing is increasingly being adopted in different scenarios, like social networking, business applications, scientific experiments, etc. Relying in virtualization technology, the construction of these computing environments targets improvements in the infrastructure, such as power-efficiency and fulfillment of users’ SLA specifications. The methodology usually applied is packing all the virtual machines on the proper physical servers. However, failure occurrences in these networked computing systems can induce substantial negative impact on system performance, deviating the system from ours initial objectives. In this work, we propose adapted algorithms to dynamically map virtual machines to physical hosts, in order to improve cloud infrastructure power-efficiency, with low impact on users’ required performance. Our decision making algorithms leverage proactive fault-tolerance techniques to deal with systems failures, allied with virtual machine technology to share nodes resources in an accurately and controlled manner. The results indicate that our algorithms perform better targeting power-efficiency and SLA fulfillment, in face of cloud infrastructure failures.

Seasonal variation in hospitalizations due to heart failure in Niterói city, Southeastern Brazil

The objective of the study was to describe seasonality of hospitalizations for heart failure in tropical climate as it has been described in cold climates. Seasonal Auto-regressive Integrated Moving-Average model was applied to time-series data of heart failure hospitalizations between 1996 and 2004 in Niteroi (Southeastern Brazil), collected from the Brazilian National Health Service Database. The standard seasonal variation was obtained by means of moving-average filtering and averaging data. The lowest and the highest annual hospital admissions were 507 (1997) and 849 (2002), respectively; the lowest and the highest monthly rates were 419 (December) and 681 (October), respectively. Peak admission rates were seen during the fall and winter. Although weak, the seasonality observed indicates that slight variations result in increased hospitalizations for heart failure.

Happiness, hope, and affection as predictors of quality of life and functionality of individuals with heart failure at three-month follow-up

The scientific evidence supporting the management of the chronically ill in a positive psychological perspective in opposition to traditional pathological approach is scarce. This study examines issues associated with recovery of health status in heart failure, in particular hope, affection, and happiness. We use a longitudinal study of 128 symptomatic patients who after medical intervention reported improved quality of life and function at 3-month follow-up. We evaluated the contribution of happiness, hope and affection, individually and as a whole, in the quality of life and functionality of individuals with heart failure. Happiness (Subjective Happiness Scale), Hope (HOPE Scale), and affection (PANAS (positive and negative affect schedule)) were determined before medical intervention. Individually, we found that happiness is correlated with the quality of life and functionality, hope to self-efficacy dimension of the quality of life scale, positive affect to functionality and negative affect with symptoms dimension, quality of life dimension, and overall sum of the quality of life scale. Overall, we found that happiness has a unique contribution to the quality of life, except in self-efficacy dimension where hope takes this contribution and positive affect has a unique contribution to the functionality in this short-term follow-up. The results highlight the importance of positive variables to health outcomes for people with heart failure and should be considered in intervention programs for this syndrome.