Vinaitheerthan R. Stock price analysis through...tools....2021 torrent

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Stock price analysis involves different methods such as fundamental analysis and technical analysis which is based on data related to price movement of the stock in the past. Price of the stock is affected by various factors such as company's performance, current status of economy and political factor. These factors play an important role in supply and demand of the stock which makes the price to be volatile in the short term. Investors and stock traders aim to book profit through buying and selling the stocks. There are different statistical and data science tools are being used to predict the stock price.
Data Science and Statistical tools assume only the stock price's historical data in predicting the future stock price. Statistical tools include measures such as Graph and Charts which depicts the general trend and time series tools such as Auto Regressive Integrated Moving Averages (ARIMA) and regression analysis.
Introduction
R Software
Graphical Analysis
Stock price prediction using Statistical tools
Stock price prediction using Support Vector Machine (SVM)
Stock price prediction using Artificial Neural Network (ANN)
Stock price prediction using Decision Tree
Stock price prediction using Random Forest
Stock price prediction using Naïve Bayes method
Stock price prediction using Deep Learning
Stock price prediction using Recurrent Neural Network (RNN)
Stock price prediction using Long Short Term Memory (LSTM)
Stock price prediction using Text Mining models and Sentiment analysis