Stock Market Prediction using Machine Learning Techniques

Author(s)	A. Vani, K. Naga Vihari, Shaik Nafeez Umar, M. Bhupathi Naidu, N. Ramachandra
Country	India
Abstract	Generally, the stock market index oscillating over the time periodand influencingmany factors. Different stock market indices determined from various mixture of stock may share similar trend in certain. The purpose of this research to predict market price index of Bombay Stock Exchange (BSE) on day wise closing using machine learning technique. The machine learning techniques ANN (Artificial Neural Network)including feedforward with lagged values of the as input, and Support Vector Machine (SVM) are compared. The price index was found to be most relevant and influenced the market performance. The results showed that performance of BSE index can be predicted with machine learningapproach. The machine learning approach shown ANN model better performance than the SVM model. The Mean Absolute Percentage Error (MAPE) of ANN is 0.5790 and the Root Mean Square Error (RMSE) is 472.12.
Keywords	Bombay Stock Exchange, ANN, SVM and Prediction
Field	Mathematics > Statistics
Published In	Volume 6, Issue 4, July-August 2024
Published On	2024-08-31
Cite This	Stock Market Prediction using Machine Learning Techniques - A. Vani, K. Naga Vihari, Shaik Nafeez Umar, M. Bhupathi Naidu, N. Ramachandra - IJFMR Volume 6, Issue 4, July-August 2024. DOI 10.36948/ijfmr.2024.v06i04.26698
DOI	https://doi.org/10.36948/ijfmr.2024.v06i04.26698
Short DOI	https://doi.org/gt8gv8

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9898-5948-55	editor@ijfmr.com

International Journal For Multidisciplinary Research