The stock market is the most popular investing places for users. Because of its expected high profit. Recently forecasting stock market returns gaining more attention. The prediction of stock markets is regarded as a challenging task. Data analysis is the way of predicting future value. if future stocks prices will increase or decrease. The main objective of this paper is to predict future stoc...

In order to obtain better prediction results, this paper combines improved complete ensemble EMD (ICEEMDAN) and the whale algorithm of multi-objective optimization (MOWOA) improve bidirectional gated recurrent unit (BIGRU), which makes full use original complex stock price time series data improves hyperparameters BIGRU network. To address problem that cannot make stationary data, sequence are ...

The aviation industry has a great impact on the economic development of countries. This is effective in increasing global gross domestic product both directly and indirectly. share airline companies this important. study, it tried to estimate monthly stock price an company that contributes growth. In prices shares Delta airlines, which are among largest America, traded New York Stock Exchange (...

In this paper, we propose a hybrid machine learning system based on Genetic Algorithm (GA) and Support Vector Machines (SVM) for stock market prediction. A variety of indicators from the technical analysis field of study are used as input features. We also make use of the correlation between stock prices of different companies to forecast the price of a stock, making use of technical indicators...

In recent years, many academy researchers have proposed several forecasting models based on technical analysis to predict models such as Engle (1982) and Cheng, Chen, and Wei (2010). After reviewing the literature, two major drawbacks are found in past models: (1) the forecasting models based on artificial intelligence algorithms (AI), such as neural networks (NN) and genetic algorithms (GAs), ...