Stock Market Prediction Using Machine Learning(ML)Algorithms - Umer, Muhammad; Awais, Muhammad; Muzammul, Muhammad (Advances in distributed computing and artificial intelligence journal, 2019)
Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosive increase in the average person’s interest for stock market. In a financially explosive market, as the stock market, it is important to have a very accurate prediction of a future trend. Because of the financial crisis and recording profits, it is compulsory to have a secure prediction of the values of the stocks. Predicting a non-linear signal requires progressive algorithms of machine learning with help of Artificial Intelligence (AI).In our research, we are going to use Machine Learning Algorithm specially focus on Linear Regression (LR), Three month Moving Average(3MMA), Exponential Smoothing (ES) and Time Series Forecasting using MS Excel as best statistical tool for graph and tabular representation of prediction results. We obtained data from Yahoo Finance for Amazon (AMZN) stock, AAPL stock and GOOGLE stock after implementation LR we successfully predicted stock market trend for next month and also measured accuracy according to measurements.