At present, there are many technical analyses for prediction in stock market. However, the technical indices are fluctuated with the quantity of stock exchanges. The financial indices are more reliable, nonvolatile and valid compared with the technical indices. In this paper, we propose an original and universal method by using SVM with financial statement analysis for prediction of stocks. We ...

Lately, stock and derivative securities markets continuously and rapidly evolve in the world. As quick market developments, enterprise operating status will be disclosed periodically on financial statement. Unfortunately, if executives of firms intentionally dress financial statements up, it will not be observed any financial distress possibility in the short or long run. Recently, there were o...

According to the adverse consequences that are brought by financial distress for companies, economy and financial –monetary institutions, the use of methods that can predict the occurrence of financial failure and prevent the loss of wealth is of great importance. The major models of credit risk assessment are based on retrospective information and using the methods which use the updated market...

 In this paper, a new Dynamic Geometric Genetic Programming (DGGP) technique is applied to empirical analysis of financial ratios and bankruptcy prediction. Financial ratios are indeed desirable for prediction of corporate bankruptcy and identification of firms’ impending failure for investors, creditors, borrowing firms, and governments. By the time, several methods have been attempted in...

The majority of past research has focused on the use of literature feedback or factor analysis as metrics for financial distress prediction. The theoretical basis for the former is relatively thin, while the latter is severely limited by data requirements. As such, this paper will instead use grey relation analysis to determine several indices with high levels of relation, and to select several...

In this paper, we propose Wavelet packet transform based prediction of trends in nonlinear financial time series data. Bombay stock Exchange (INDIA) was selected as a tool to show the Wavelet packet transform based prediction of trends in financial time series. The experimental results demonstrate that the proposed method substantially outperform existing approaches.

Today in every organization financial analysis provides the basis for understanding and evaluating the results of business operations and delivering how well a business is doing. This means that the organizations can control the operational activities primarily related to corporate finance. One way that doing this is by analysis of bankruptcy prediction. This paper develops an ontological model...

Studies on human monetary prediction and decision making emphasize the role of the striatum in encoding prediction errors for financial reward. However, less is known about how the brain encodes financial loss. Using Pavlovian conditioning of visual cues to outcomes that simultaneously incorporate the chance of financial reward and loss, we show that striatal activation reflects positively sign...

The operating status of an enterprise is disclosed periodically in a financial statement. Financial distress prediction is important for business bankruptcy prevention, and various quantitative prediction methods based on financial ratios have been proposed. This paper presents a financial distress prediction model based on wavelet neural networks (WNNs). The transfer functions of the neurons i...

this study predicts corporate bankruptcy five years before its occurrence using financial ratios introduced in altman’s z-score model and current ratio. three estimation methods namely; liner probability, logit and probit models have chosen for model estimation. the sample contains 134 companies in tehran stock exchange during 2003. the precision of prediction of the estimated models for the ma...