PREDICTING THE STOCK PRICE USING LINEAR REGRESSION
Main Article Content
Abstract
Stock price prediction is always a predominant goal for every investor which helps them to knowing the future prices considering the previous records. We made our effort in predicting the same using statistical modeling approach, the Linear Regression Technique for finding Open, Close, High and Low values of TCS from National Stock Exchange Of India (NSEI).
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.
References
Muhammad Waqar, Hassan Dawood,Muhammad Bilal Shahnawaz, Mustansar Ali Ghazanfar, Ping Guo. “Prediction of Stock Market by Principal Component Analysis,†13th International Conference on Computational Intelligence and Security, 2017.DOI: 10.1109/CIS.2017.00139, https://ieeexplore.ieee.org/document/8288561/ [2] Dinesh Bhuriya, Ashish Sharma, Upendra Singh. “Stock Market Prediction using Linear Regression,†International Conference on Electronics, Communication and Aerospace Technology ICECA 2017.DOI:
1109/ICECA.2017.8212716, https://ieeexplore.ieee.org/document/8212716/
P. A. Samarakoon, D. A. S. Athukorala, System abnormality detection in stock market complex trading systems using machine learning techniques, Information Technology Conference (NITC), 2017 National.DOI: 10.1109/NITC.2017.8285660, https://ieeexplore.ieee.org/document/8285660/
C. Narendra Babu, B. Eswara Reddy, Selected Indian stock predictions using a hybrid ARIMA-GARCH model, Advances in Electronics, Computers and Communications (ICAECC), 2014 International Conference.DOI: 10.1109/ICAECC.2014.7002382, https://ieeexplore.ieee.org/abstract/document/7002382/
Harun Ercan. “Baltic Stock Market Prediction by Using NARX,†Computer Sciences and Information Technologies (CSIT), 2017 12th International Scientific and Technical Conference.DOI: 10.1109/STCCSIT.2017.8098829, https://ieeexplore.ieee.org/abstract/document/8098829/
Qiubin Liang, WengeRong, Jiayi Zhang, Jingshuang Liu, Zhang Xiong. †Restricted Boltzmann Machine Based Stock Market Trend Prediction,†Neural Networks (IJCNN), 2017 International Joint Conference.DOI: 10.1109/IJCNN.2017.7966014, https://ieeexplore.ieee.org/document/7966014/
Kai Chen, Yi Zhou, Fangyan Dai, A LSTM-based method for stock returns prediction: A case study of China stock market, Big Data (Big Data), 2015 IEEE International Conference.DOI: 10.1109/BigData.2015.7364089, https://ieeexplore.ieee.org/document/7364089/
Poonam Somani, ShreyasTalele, SurajSawant, Stock market prediction using Hidden Markov Model, Information Technology and Artificial Intelligence Conference (ITAIC), 2014 IEEE 7th Joint International.DOI: 10.1109/ITAIC.2014.7065011, https://ieeexplore.ieee.org/document/7065011/
Eslam Nader Desokey, Amr Badr, Abdel Fatah Hegazy. “Enhancing Stock Prediction Clustering Using K-Means with Genetic Algorithm,†Computer Engineering Conference (ICENCO), 2017 13th International.DOI: 10.1109/ICENCO.2017.8289797, https://ieeexplore.ieee.org/document/8289797/
A.J.P. Samarawickrama, T.G.I. Fernando. “A Recurrent Neural Network Approach in Predicting Daily Stock Prices,†Industrial and Information Systems (ICIIS), 2017 IEEE International Conference.DOI: 10.1109/ICIINFS.2017.8300345, https://ieeexplore.ieee.org/document/8300345/
RohitVerma, PkumarChoure , Upendra Singh, Neural networks through stock market data prediction, Electronics, Communication and Aerospace Technology (ICECA), 2017 International conference.