OBJECTIVE :
The aim of this project is to predict and compare the future value of the financial stocks of big companies- Apple, GE, Google, IBM, and Microsoft so that the user can easily invest in those companies stocks’ which are going to make profits in the upcoming future. For this machine learning is used to make prediction based on the data of current stock market indices by training on their previous data values. With the help of this project, the use of irregular sources for collection of information and prediction of stock market will decrease which in turn will also save the user’s valuable time.
LANGUAGE : Python
TOOLS USED: Jupyter (Anaconda Navigator)
LIBRARIES & PACKAGES USED : Pandas, Matplotlib, NumPy, Scikit-learn
METHODOLOGY :
We used machine learning which is in the recent trend and made predictions based on the data of the current stock market indices by training on their previous data values. We collected the last 7 years of input data(date, open, high, low, close, adj close) and extract Apple, GE, Google, IBM, and Microsoft Stocks Price from Yahoo Finance for the prediction. After that analyzed stocks using rolling mean and return rate. To get a better understanding of this, plotted it out with the help of matplotlib. In the graph, the upturns will show a favorable time to sell the stocks while the downturn shows a favorable time to buy the stocks. After that we calculate High Low Percentage and Percentage Change to predict our stocks. Then we pre-processed our data, and start analysis using- Simple Linear Analysis, Multi Linear Analysis and K Nearest Neighbors. At last, we plot our prediction. The successful prediction of the stock will be a great asset for the market companies and will provide real-life solutions to the problem that stock investors face in today’s time.