Abstract
Forecasting the stock price of a particular has been a difficult task for many analysts and researchers. In fact, investors are highly interested in the research area of stock price prediction. However, to improve the accuracy of forecasting a single stock price is a really challenging task; therefore in this paper, I propose a sequential learning model for prediction of a single stock price with corporate action event information and Macro-Economic indices using LTSM-RNN method. The results show that the proposed model is expected to be a promising method in the stock price prediction of a single stock with variables like corporate action and corporate publishing.
Highlights
In the practice of stock asset management business, forecasting the stock price is one of the important tasks
The results show that the proposed model is expected to be a promising method in the stock price prediction of a single stock with variables like corporate action and corporate publishing
It is difficult to know at what point of time the information presented is affecting the stock price, it seems that the LSTM-Recurrent Neural Network (RNN) will be an effective means to make prediction of stock price incorporating such situations
Summary
In the practice of stock asset management business, forecasting the stock price is one of the important tasks. The person who analyzes individual companies focuses on the announcement of company’s financial results that is published quarterly by many companies and daily press releases because by knowing the progress of results, it is significant to judge whether the prospects so far have been correct and to what extent the future growth of the company can be expected. The stock price rises if there is information that a lot of investors think about enhancing corporate value in the future. Information such as announcement of company’s financial results and press releases has a very important meaning in predicting future stock prices. It can be said that stock prices in the past include the speculation of investors who have judged based on such information [1]. It is difficult to know at what point of time the information presented is affecting the stock price, it seems that the LSTM-RNN will be an effective means to make prediction of stock price incorporating such situations
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
