Sharif Digital Repository

The past few years have witnessed a growing rate of attraction in adoption of Artificial Intelligence (AI) techniques and combining them to improve forecasting accuracy in different fields. Besides, stock market forecasting has always been a subject of interest for most investors and professional analysts. Stock market forecasting is a tough problem because of the uncertainties involved in the movement of the market. This paper proposes a hybrid artificial intelligence model for stock exchange index forecasting, the model is a combination of genetic algorithms and feedforward neural networks. Actually it evolves neural network weights by using genetic algorithms. We also employ preprocessing... 

As the intersection of finance and statistics, financial surveillance is a new interdisciplinary field of research. In this field, statistical process control methods are applied to monitor financial indices. The final aim is to detect out-of-control conditions and trigger a signal as soon as possible. These early signals can help practitioners in making on-time decisions. In this paper, a new method based on a support vector machine is proposed to detect upward and downward shifts with step and trend patterns in auto-correlated financial processes. These processes are modeled by the autoregressive moving average (ARMA) and generalized autoregressive conditional heteroskedasticity (GARCH)...