shareprice-forecasting - TATASTEEL
Evaluating stock performance is very individual to each investor. There have been several studies indicating that stock prices follow the laws of hysteresis. Additionally, these factors can often be visualised through trends, and through algorithms that can crunch numbers to statistically establish a forecast than to blatantly predict based on simple guesses and intuition. The primary objective of this project is to build a forecasting model that can predict the closing price(s) of a stock, with respect to secondary and tertiary factors. Closing price of a stock is a good metric to predict as it constitutes not only a metric for one day, but also constitutes in forecasting an opening price for the following day.
With that being said, this project can be identified as an attempt to algorithmically forecast the stock price(s) of the Indian Steel Industry. India was once the second largest steel producer in the World, and consequently, the Indian Steel Industry has been a major contributor to India’s manufacturing output.
The primary stock that is considered in this project is that of TATA Steel. TATA Steel is a huge name and a prominent figure in the Indian as well as global steel industry, commanding over 30% market share in India. For this project, I am considering the stock price of TATA Steel over a period of 3 years, spanning from 1st January 2017 till 31st December 2019.
The regressors that are being considered are Support Vector Regression (SVR) and a linear regressor.