Stock Price Trend Prediction Using Multiple Linear Regression
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 10
Abstract
Stock markets are major institutions where trades are made daily having their worth in millions and billions on a daily basis. Some consider as a fast way to fill up their pockets whereas some have a traditional approach to invest in a company and reap long term benefits. A well done research about the company and its performance can help to gain better financial profits. Industry experts and major conglomerates invest heavily in research and development and with the technological developments, minimising the error probability and estimating the future performance has become achievable. Machine Learning algorithms have proved to fetch benevolent results in predicting stock prices. In this paper, we have studied and documented the performance of APPLE INC.’s stock price using Multiple Linear Regression and gauged its performance using Root Mean Squared Error. The results are promising but can be improved by taking into consideration more parameters.
Authors and Affiliations
Shruti Shakhla, Bhavya Shah, Niket Shah, Vyom Unadkat, Pratik Kanani
Keywords
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