function whose output is the probability distribution over labels. In this work, the objective is to forecast the direction of daily price movements of the stock price, this direction are used to create a binary class label where a label \[1,0\] represents that the stock price will increase and label \[0,1\] represents that the stock price will decrease.

Experiments
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Experimental Setup
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### Data

We evaluated our model on a data set of financial news collected from Reuters and Bloomberg over the time period from October 2006 to November 2013. This data set was made publicly available by Ding et al. [@ding2014using] and shown in table \[tab:Data set\]. We further collected data from Reuters for 473 companies listed in the Standard & Poor’s 500 over the time period started from November 2013 to march 2018. Meanwhile, the historical stock price data from October 2006 to March 2018 for all individual shares in Standard & Poor’s 500 are collected from Yahoo Finance. The second part of the data are used for individual stock price prediction and shown in table  \[tab:individual\]. Due to the page limit, We only show the major companies listed in the S&P 500, this will also be 