In this paper, a new FEPA portfolio forecasting model is based on the EMD decomposition method. The special empirical modal of financial time series, principal component analysis, and artificial neural network to forecast for nonlinear, nonstationary, multiscale complex series predict stock market indices foreign exchange rates empirically investigate hot area in research. combined proposed pap...

The stock price forecasting has always been considered as a difficult problem in time series prediction. Mass of financial Internet information play an important role in the financial markets, information sentiment is an important indicator reflecting the ideas and emotions of investors and traders. Most of the existing research use the stock's historical price and technical indicators to predi...

Business failures can cause financial damages to investors, creditors, or even society. For this reason bankruptcy prediction is one of the most challenging tasks in the field of financial decisionmaking. Business failure prediction has been an active research area since the 60s. The work of Beaver (1966) who performed univariate analysis of financial ratios and the work of Altman (1968) who em...

Prediction of financial time series is described as one of the most challenging tasks of time series prediction, due to its characteristics and their dynamic nature. Support vector regression (SVR), Support vector machine (SVM) and back propagation neural network (BPNN) are the most popular data mining techniques in prediction financial time series. In this paper a hybrid combination model is i...

A lot of methods have been used in the past for the prediction of failure business like Discriminant analysis, Logit analysis, Quadratic Function etc. Although some of these methods lead to models with a satisfactory ability to discriminate between healthy and bankrupt, they endure some limitations, often due to the unrealistic assumption of statistical hypotheses. This is why we have undertake...

Bankruptcy prediction has been addressed by many researchers in the field of finance since few decades. One of the best approaches to deal with this issue is considering it as a classification problem. In this paper a time series prediction model of bankruptcy via Adaptive neuro-fuzzy inference system (ANFIS) is formulated, which is capable of predicting the bankruptcy of a firm for any future ...

The forecast is very complex in financial markets. The reasons for this are the fluctuation of financial data, Such as Stock index data over time. The determining a model for forecasting fluctuations, can play a significant role in investors deci-sion making in financial markets. In the present paper, the Black Scholes model in the prediction of stock on year later value, on using data from mel...

The present study, according to our knowledge, is the first attempt to establish a financial distress prediction model for a unique set of enterprises, which are the enterprises listed on the specialized Hong Kong Growth Enterprise Market. It also makes an analysis of corporate financial sustainability and its relationship to financial distress prediction. The logistic regression and jackknife ...