Stock Market Price Prediction System using Python

Ms. Jyoti Murty

Title:
Stock Market Price Prediction System using Python

Authors:
Ms. Jyoti Murty

Cite This Article :

Ms. Jyoti Murty "Stock Market Price Prediction System using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications, March 2026, pp.911-928, URL: https://www.ijtsrd.com/papers/ijtsrd101670.pdf

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Abstract :
The stock market is a tricky thing to predict. It is hard to guess what the prices of stocks will be because the market is always changing. If we can predict the prices of stocks it will be very helpful for people who invest in the stock market. They will be able to make decisions about what to buy and sell. These days we use something called machine learning to try to predict the prices of stocks. Machine learning is a way of using computers to find patterns in data. We can use it to look at what has happened in the past and try to guess what will happen in the future. There are things that can affect the stock market. The economy how well companies are doing what is happening in the world. How people are feeling about the market can all have an impact. It is hard to take all of these things into account when trying to predict what will happen. In this study we used a kind of machine learning called Long Short-Term Memory or LSTM for short. We compared it to ways of predicting stock prices to see which one was the best. We used data from the ten years to test our models. The LSTM model was the best it was able to predict the prices of stocks with a degree of accuracy. We also used something called indicators to help us make our predictions. These are numbers that can tell us things about the stock market. We used things like Moving Averages and Relative Strength Index to help us make our predictions.

Keywords :
Stock Market Prediction; Machine Learning; LSTM; Deep Learning; Python; Time Series Forecasting; Technical Indicators; Financial Analysis; Neural Networks; Predictive Analytics

Publication Details:

Unique Identification Number : IJTSRD101670

Published In : Special Issue | Smart Innovations in Computer Science and Applications, March 2026

Page Number(s) : 911-928

Publisher Name : IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470

Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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