The huge volume of Investors are available in the market, with good enough knowledge and has a prediction as well as control over their investments. The stock market fails to attract new investor at times. An approach with adequate expertise is designed to help investors to ascertain hidden patterns from the historical data that have feasible and improved predictive ability in their investment decisions. The stock data for the past decade has been collected and trained using the ARIMA model with different parameters. The performance of the trained model is analysed and it also tested to find the trend and the market behavior for future forecast.
Simple analytics collected data from the client. Data like stock open price, close price and the average price information is available and based on that we will go for analysis. Simple Analytics worked closely with the client’s team and did a series of analysis in understanding the stock market to predict forecasting closing price rate.
In stock market data, we have used to models ARIMA and ARMA technique from time series forecasting. Basically, we have to forecast the next three years stock market closing price value. Time series model works on closing price rate and predicts the forecasting value with better time series model.
In the essence, Simple Analytics forecasting model come across various significant factor model that makes an impact on stock market closing price rate. Simple Analytics advised a client to concentrate on these factor model in order to reduce their stock market price error percentage.