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The aim of this paper is to investigate whether a model utilizing cash-flow ratios in combination with other categories of financial ratios results in a model superior to a model that does not include cash-flow ratios. The study uses both, operating cash-flow and the traditional definition of cash-flow, as proxies for cash-flow ratios. Other categories of ratios are profitability, activity, liquidity...
This paper mainly discusses the study of models for financial distress pre-warning, trying to select general financial indexes by principal component analysis, and meanwhile adding nonfinancial indexes which reflect corporate governance state to complement. Logit Model which is more accurate in prediction is selected, with the 56 company samples including both delisting pre-warned companies and counterparts...
This paper is to propose an integrated rough sets and PCA-RBFN model for corporate financial distress prediction problem in an attempt to suggest a new model with better explanatory power and stability. To serve this purpose, the RS and the PCA method is employed to simplify the indicators, and the RBFN is used as a predicting tool for corporate financial situation. In addition, to evaluate the performance...
Lately, many notorious financial distress and bankruptcy events occurred in the world economic. As we known, bankruptcy of Lehman Brothers Holdings Inc. (LEH) is the largest bankruptcy filing in U.S. history in 2008. These events have serious impacted on the socio-economic and investment in public wealth. Due to solve this dilemma, this research collected 68 listed companies as the raw data from Taiwan...
Although originally developed in 1968 using a small sample of firms from the 1950s and 1960s, Altman's Z-Score model remains a commonly used tool for evaluating the financial health of companies. Because of the age of the model and other its attributes, such as its small sample of manufacturing firms and the use of equal group sizes of bankrupt and non-bankrupt firms, it is likely that the model is...
The operating status of a forest industry enterprise is disclosed periodically for viability. As a result, the manager usually only get information about the operating decision. An employer may be in after the formal financial statement has been published. If the employer executives intentionally package financial statements with the purpose of hiding the actual status of the forestry industry enterprise,...
Financial distress is the most synthetic form of business crisis and financial distress prediction (FDP) has been a widely and continually studied topic in the field of corporate finance. This paper attempts to put forward OR-CBR in K-nearest neighbors model, which can be the implementation of corresponding algorithm.
To overcome the shortages of the existing financial prediction models such as strict hypothesis, poor generalization ability, low prediction accuracy and low learning rate etc., a new early warning model of financial crisis have established for listed company using Extreme Learning Machine. From five dimensions of solvency, operating-ability, profitability, cash-ability and grow-ability, fifteen financial...
In the predicting financial distress, we know that irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper use rough sets as a preprocessor of SVR to select a subset of input variables and employ the particle swarm optimization algorithm (PSOA) to optimize...
There is a vast amount of financial information on companies' financial performance. This information is of great interest for different stakeholders, i.e., stockholders, creditors, auditors, financial analysts, and managers. For stakeholders it is important to extract relevant performance information of the companies they are interested in. As a common method for classification and prediction, decision...
The paper presents method of hybrid prediction system for debt portfolio appraisal. Based on the local area competence, time spread repayment values are predicted by means of hybrid combination of various machine learning techniques. The above methods include among others clustering of references, model selection and enrichment of input variables with prediction outputs from preceding periods. Experimental...
This paper examines published data to develop a model of Logistic Regression for detecting factors associated with Fraudulent Financial Statement (FFS). After an exhaustive exploitation of prior work used financial ratios, 21 ratios are selected as potential predictors of FFS and a series of experiments have been conducted to determine the optimal parameters for Logistic model. Then, we propose an...
In the analysis of predicting financial distress based on support vector regression (SVR), irrelevant or correlated features in the samples could spoil the performance of the SVR classifier, leading to decrease of prediction accuracy. In order to solve the problems mentioned above, this paper used rough sets as a preprocessor of SVR to select a subset of input variables and employed the immune clone...
Through comparison of the efficiency of the credit default discrimination among the KMV model based on the distance to default, the logistic model with the distance-to-default DD and the logistic model without the distance-to-default DD, we find the distance to default can improve the efficiency of Logistic model to discriminate the default risk of the SMEs, and the discrimination effect of the distance...
Financial distress and bankruptcy of companies may cause the resources to be wasted and the investment opportunities to be faded. Bankruptcy prediction by providing necessary warnings can make the companies aware of this problem so they can take appropriate measures with these warnings. The aim of this study is model development for financial distress prediction of listed companies in Tehran stocks...
In this paper, we applied culture particle swarm optimization algorithm (CPSO) to optimize the parameters of SVM. Utilizing the colony aptitude of particle swarm and the ability of conserving the evolving knowledge of the culture algorithm, this CPSO algorithm constructed the population space based on particle swarm and the knowledge space. The two spaces evolved independently, at the same time, the...
Cash flow forecasting and control are essential to the survival of any contractor. The time available for a detailed pre-tender cash flow forecast is often limited. Therefore, contractors require simpler and quicker techniques which would enable them to forecast cash flow with reasonable accuracy. The paper is based on classifying projects into groups and producing a standard curve for each group...
The operating status of a construction project is disclosed periodically in investment risks. As a result, investors usually only get information about the investment risks, an employer may be in after the formal financial statement has been published. If the employer executives intentionally package financial statements with the purpose of hiding the actual status of the constructive project, then...
Recent outbreak of corporate financial crises worldwide has brought attention to the need for a new international financial architecture which rests on crisis prediction and crisis management. Financial data have been widely used by researchers to predict financial crisis, but few studies exploit the use of non-financial indicators in corporate governance to construct financial crisis prediction model...
In the analysis of predicting financial distress based on support vector machine (SVM), the two parameters of SVM, c and sigma, which its value have important effect on the predicting accuracy, must be predetermined carefully. In order to solve this problem, this paper proposed a new culture genetic algorithm (CGA) to optimize the parameters of SVM. Through embedding GA into the cultural algorithm...
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