Stock Market Prediction

In the finance world stock trading is one of the most important activities. Stock market prediction is
an act of trying to determine the future value of a stock other financial instrument traded on a
financial exchange. This project explains the prediction of a stock using Machine Learning. The
technical and fundamental or the time series analysis is used by the most of the stockbrokers while
making the stock predictions. The programming language used to predict the stock market using
machine learning is Python. In this project we propose a Machine Learning (ML) approach that will
be trained from the available stocks data and gain intelligence and then uses the acquired knowledge
for an accurate prediction. In this context this project uses a machine learning technique called Linear
Regression to predict stock prices for the large and small capitalizations and in the three different
markets, employing prices with both daily and up-to-the-minute frequencies.
Stock Price Forecasting is a popular and important topic in financial and academic studies, although
Share Market is an untidy place for predicting since there are no significant rules to estimate or
predict the price of share in the share market. Many methods like technical analysis, fundamental
analysis, time series analysis and statistical analysis, etc. are all used to attempt to predict the price in
the share market but none of these methods are proved as a consistently acceptable prediction tool.
The fluctuation of stock market is violent and there are many complicated financial indicators.