JPX Japan Stock Exchange Prediction

Find us on Google Scholar
Peer Review Policy
Article Processing Charges
Publication Procedure
Research Topics
FAQ
Copyright Infringement
Refund and Cancellation Policy
[featured_image]
Download
Download is available until [expire_date]
  • Version
  • Download 364
  • File Size 301.45 KB
  • File Count 1
  • Create Date 23/12/2022
  • Last Updated 23/12/2022

JPX Japan Stock Exchange Prediction

JPX Japan Stock Exchange Prediction

Zarinabegam Mundargi, Chetanya Rathi, Harsh Dhabekar, Harshit Mundhra, Pushkar Helge

Abstract— It is crucial to make an extremely accurate forecast of a future trend in a market that is financially volatile, such as the stock market. In the context of the economic crisis and the need to make money, a trustworthy estimate of stock values is crucial.  Advanced machine learning methods are needed to predict another model. Thousands of people make stock market investments every business day. Some of these investors experience financial gains or losses. On any given trading day, the gain or loss is unexpected. Stock market research is required because of the high demand for stock price forecasts. Effective forecasting systems help traders in an indirect way by providing useful information like price position in the future. In this study, a stacked LSTM-based system for stock forecasting is built. Finding sound investments is a requirement for success in any financial sector. These financial decisions were done manually by experts, technology has opened up new possibilities for retail investors. Numerous quantitative trading initiatives are currently being employed to study financial markets and develop investment plans. Such a technique needs real-time and historical data, which is difficult to come by, especially for individual investors. We have considered both of these factors in this model based on the dataset provided by Japan Exchange Group, Inc. (JPX).

Key words : LSTM , JPX , ML , Real time prediction.

Follow Us

Google Scholar

ResearchGate

Facebook

Instagram

Working Hours

Mon – Sat: 9:00 AM – 6:00 PM

Sunday: 9:00 AM – 1:00 PM

📧 editor@ijsrem.com

📞 +91 93911 67991

Contact Us

International Journal of Scientific Research in Engineering and Management (IJSREM)

EDTECH PUBLISHERS (OPC) PRIVATE LIMITED

📍 #62/1, New No 7, 1st Cross, 2nd Main,
Ganganagar, R T Nagar, Bangalore North,
Bangalore, Karnataka, India – 560032

Visit Contact Page