â  using of prediction models is one of the methods of financial performance prediction. financial ratios are employed as predictive variable in prediction models. the main purpose of this study is to compare the incremental information content of accrual and cash ratios for prediction and evaluation of the financial performance of business entities by data mining models. in align with research...

the main focus in this study is on data pre-processing, reduction in number of inputs or input space size reduction the purpose of which is the justified generalization of data set in smaller dimensions without losing the most significant data. in case the input space is large, the most important input variables can be identified from which insignificant variables are eliminated, or a variable ...

the bankruptcy prediction models have long been proposedas a key subject in finance. the present study, therefore, makes aneffort to examine the corporate bankruptcy prediction through employmentof the genetic algorithm model. furthermore, it attempts to evaluatethe strategies to overcome the drawbacks of ordinary methods forbankruptcy prediction through application of genetic algorithms. thesa...

abstract this study aims at profitability prediction of listed companies in tehran stocks exchange (tse), using artificial neural network. the respected sample consists of 90 firms from 2002  to 2009 (720 firm/years). attention to the framework of study reduced the number of 720 firm/years to 630 firm/years. these firms separated in two groups of learning sample (540 firm/years) and test sample...

Financial failure prediction models have been developed by using Logistic Regression (LR) analysis from traditional statistical methods and Data Envelopment Analysis (DEA), which is a mathematically based nonparametric method over the financial reports of the companies traded in The Istanbul Stock Exchange National 100 Index (BIST 100) between the years 2014-2016. In the development of these mo...

The bankruptcy prediction models have long been proposedas a key subject in finance. The present study, therefore, makes aneffort to examine the corporate bankruptcy prediction through employmentof the genetic algorithm model. Furthermore, it attempts to evaluatethe strategies to overcome the drawbacks of ordinary methods forbankruptcy prediction through application of genetic algorithms. Thesa...

The main focus in this study is on data pre-processing, reduction in number of inputs or input space size reduction the purpose of which is the justified generalization of data set in smaller dimensions without losing the most significant data. In case the input space is large, the most important input variables can be identified from which insignificant variables are eliminated, or a variable ...

Given financial data from popular sites like Yahoo and the London Exchange, the presented paper attempts to model and predict stocks that can be considered ”good investments”. Stocks are characterized by 125 features ranging from gross domestic product to EDIBTA, and are labeled by discrepancies between stock and market price returns. An artificial neural network (Self-Organizing Map) is fitted...

Financial distress prediction is always important for financial institutions in order for them to assess the financial health of enterprises and individuals. Bankruptcy prediction and credit scoring are two important issues in financial distress prediction where various statistical and machine learning techniques have been employed to develop financial prediction models. Since there are no gene...