Enhancing Stock Price Prediction Using Machine Learning: A Comparative Analysis of Random Forest and Other Algorithms

Registration ID: IJNRD_300374

Published ID: IJNRD2409154

DOI: Click Here to Get

S.Subasree , A.Samyuktha , S.Hamsana , A.Harithira , P.Nidhishkumar

Random Forest, Machine Learning ,Stock Prediction

Predicting stock prices is a difficult task due to the ever-changing and complex nature of financial markets. However, the use of machine learning algorithms has shown promise in improving the accuracy of these forecasts. This research focuses on the random forest algorithm, which is an ensemble learning technique, for predicting stock prices. By analyzing historical stock price and trading volume data, we trained a random forest model to make future predictions. We compared the performance of the random forest model to other machine learning algorithms like linear regression and decision trees using metrics such as mean absolute error (MAE) and root mean squared error (RMSE). Our results indicate that the random forest algorithm outperforms other algorithms in terms of prediction accuracy. It effectively captures the intricate and non-linear relationships among different variables, making it well-suited for stock price prediction tasks. Additionally, the random forest algorithm identified key features such as trading volume and historical price trends that have a significant impact on stock prices. In conclusion, this study emphasizes the effectiveness of the random forest algorithm for accurate stock price prediction

Published Paper   E-Certificate

S.Subasree, A.Samyuktha, S.Hamsana, A.Harithira, & P.Nidhishkumar (September-2024). Enhancing Stock Price Prediction Using Machine Learning: A Comparative Analysis of Random Forest and Other Algorithms. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(9), b462-b472. https://ijnrd.org/papers/IJNRD2409154.pdf

Volume 9 Issue 9, September-2024

Pages : b462-b472

Paper Reg. ID: IJNRD_300374

Published Paper Id: IJNRD2409154

Downloads: 000121984

Research Area: Science and Technology

Country: PUDHUCHERRY, PUDHUCHERRY, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2409154.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2409154

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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