ISSN:2582-5208

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Paper Key : IRJ************843
Author: Aniket Wasnik, Anshul Chaudharir, Abhishek Khasre, Chetan Kaware, Abhishek Kondalkar, Rajesh Nakhate
Date Published: 06 Dec 2022
Abstract
Stock trading is one of the most essential operations in the financial world. Stock market prediction is the attempt to estimate the future value of a stock or other financial instrument listed on a stock exchange. This article explores how Machine Learning can be used to forecast the price of a stock. The majority of stockbrokers utilise technical, fundamental, and time series analysis when making stock forecasts. Python is the programming language used for stock market forecasting. The goal of this paper is to use Facebook Prophet and yfin to examine the flaws in the current system and develop a time-series model that would implement more effective algorithms to largely mitigate them. Anyone can monitor the preferred stock they want to invest in using this model, and they can maximise profit by buying lots of it at the cheapest price and selling it at the highest.
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