As a complex hot problem in the financial field, stock trend forecasting uses a large amount
of data and many related indicators; hence it is difficult to obtain sustainable and effective …

In this paper, we developed a prediction model based on support vector machine (SVM) with
a hybrid feature selection method to predict the trend of stock markets. This proposed hybrid …

Stock trend prediction is regarded as a challenging task. Recently many researches have
shown that a successful feature selection method can improve the prediction accuracy of …

Prediction of stock market trends has been an area of great interest both to researchers
attempting to uncover the information hidden in the stock market data and for those who …

This paper introduces a new approach to forecast daily stock trends using the random forest
technique. This study intends to include as many features as possible to hopefully describe …

Stock values are predicted using the market's biggest issues. Stock price data is hard to
predict due to its distinct traits and volatility. Online news and comments reflect investor …

The stock market is a crucial component of the financial market, playing a vital role in wealth
accumulation for investors, financing costs for listed companies, and the stable development …

With the return of deep learning methods to the public eye, more and more scholars and
industry researchers have tried to start exploring the possibility of neural networks to solve …

Nowadays, people show more and more enthusiasm for applying machine learning
methods to finance domain. Many scholars and investors are trying to discover the mystery …

Stock investment has become an important investment activity in Taiwan. However,
investors usually get loss because of unclear investment objective and blind investment …