Many researchers attempt to accurately predict stock price trends using technologies such
as machine learning and deep learning to achieve high returns in the stock market …

Stock market forecasting has attracted significant attention mainly due to the potential
monetary benefits. Predicting these markets is a challenging task due to numerous …

The new transformed read-write Web has resulted in a rapid growth of user generated
content on the Web resulting into a huge volume of unstructured data. A substantial part of …

Forecasting the direction of the daily changes of stock indices is an important yet difficult task
for market participants. Advances on data mining and machine learning make it possible to …

With the advent of new technology paradigm, SMAC (Social media, Mobile, Analytics and
Cloud) the information network generates an infinite ocean of data spreading faster and …

The prediction of stock price has always been a main challenge. The time series of stock
price tends to exhibit very strong nonlinear characteristics. In recent years, with the rapid …

Financial markets are complex systems influenced by many interrelated economic, political
and psychological factors and characterised by inherent nonlinearities. Recently, there have …

Financial markets are complex dynamic systems influenced by a high number of active
agents, which produce a behavior with high randomness and noise. Trading strategies are …

In this research, a novel approach is developed to predict stocks return and risks. In this
three stage method, through a comprehensive investigation all possible features which can …

Financial data forecasting is one of the most important areas in financial markets. In the
stock market, if the stock falls or rises to a point and then rises or falls for a long time, these …