Stocks in broader sense refers to acquiring of a part of company. Supply and demand, earning and expectation, economic indicators are some of the factors affecting stocks. One have to know the difference between time series data and cross sectional data for more understanding of stocks. Time series refers to consider the different value of same data over different point whereas later refers to considering the value of different assets or different data over the same time. For analyzing the pattern in the stocks it is very important to understand the stationary time series data rather than cross sectional or non-stationary time series data. You can go for deep learning, support vector regression, lasso, linear regression or can use auto regression and integrated moving averages (ARIMA) for predicting the future forecast of the closing price. Moving average and auto regression will take into consideration forecasting error and past weighted value. Analyzing the stocks, it is provided with continuous value hence regression model will fit. For data related queries you can use yahoo finance to download data and do some experiment with it. Now it is the time to write what AI Sangam offers you.
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