Predicting ETF prices using linear regression
Keywords:Machine learning; simple linear regression; exchange-traded funds.
Machine learning has allowed computers to analyze data and make future predictions based on those dates. One of the most common and easiest to implement machine learning algorithms used to do this is simple linear regression. Simple linear regression finds trends in a data set by graphing a line that shows the relationship between two variables. This paper will show how Simple linear regression can predict future ETF prices by finding linear trends in two particular exchange-traded funds: Invesco QQQ and vanguard VGT, predict their value six months later using their five-year closing price in yahoo finance and compare their respective predicted growth rate.
Umer, M., Awais, M., & Muzammul, M. (2019). Stock Market Prediction Using Machine Learning (ML)Algorithms. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 8(4), 97–116.
Vaishnavi Gururaj, Shriya V R, and Dr. Ashwini K “Stock Market Prediction Using Linear Regression and Support Vector Machines,” International Journal of Applied Engineering Research ISSN 0973-4562 Volume 14, Number 8 (2019) Pp. 1931-1934, 2019.
Ishita Parmar, Navanshu Agarwal, Sheirsh Saxena, Ridam Arora, Shikhin Gupta, Himanshu Dhiman, Lokesh Chouhan “Stock Market Prediction Using Machine Learning”, Department of Computer Science and Engineering National Institute Of Technology, Hamirpur – 177005, INDIA.
S, Lokasree B. “Data Analysis and Data Classification in Machine Learning Using Linear Regression and Principal Component Analysis”, Turkish Journal of Computer and Mathematics Education Vol.12 No.2 (2021), 835- 844.
Sreehari, E., and G. S. Pradeep Ghantasal. “Climate Changes Prediction Using Simple Linear Regression”, Journal of Computational and Theoretical Nanoscience Vol. 16, 1–4, 2019.
Maulud, Dastan Hussen, and Adnan Mohsin Abdulazeez. “A Review on Linear Regression Comprehensive in Machine Learning”, Journal of Applied Science and Technology Trends Vol. 01, No. 04, Pp. 140 –147, (2020)
Harikrishnan, R., Gupta, A., Tadanki, N., Berry, N., & Bardae, R. (2021). Machine Learning Based Model to Predict Stock Prices: A Survey. IOP Conference Series: Materials Science and Engineering, 1084.
Ahangar, R. G., Yahyazadehfar, M., & Pournaghshband, H. (2010). The comparison of methods artificial neural network with linear regression using specific variables for prediction stock price in Tehran stock exchange. arXiv preprint arXiv:1003.1457.
Sheta, A. F., Ahmed, S. E. M., & Faris, H. (2015). A comparison between regression, artificial neural networks and support vector machines for predicting stock market index. Soft Computing, 7(8), 2.
Har, W.P., & Ghafar, M. (2015). The Impact of Accounting Earnings on Stock Returns: The Case of Malaysia’s Plantation Industry. International Journal of Biometrics, 10, 155.
How to Cite
This work is licensed under a Creative Commons Attribution 4.0 International License.