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What is Closing Price

Handbook of Research on Pattern Engineering System Development for Big Data Analytics
The price of particular stock at the end of trading.
Published in Chapter:
Machine Learning Models for Forecasting of Individual Stocks Price Patterns
Dilip Singh Sisodia (National Institute of Technology, Raipur, India) and Sagar Jadhav (National Institute of Technology Raipur, India)
DOI: 10.4018/978-1-5225-3870-7.ch008
Stock investors always consider potential future prices before investing in any stock for making a profit. A large number of studies are found on the prediction of stock market indices. However, the focus on individual stock closing price predictions well ahead of time is limited. In this chapter, a comparative study of machine-learning-based models is used for the prediction of the closing price of a particular stock. The proposed models are designed using back propagation neural networks (BPNN), support vector regression (SVR) with SMOReg, and linear regression (LR) for the prediction of the closing price of individual stocks. A total of 37 technical indicators (features) derived from historical closing prices of stocks are considered for predicting the future price of stock in a time window of five days. The experiment is performed on stocks listed on Bombay Stock Exchange (BSS), India. The model is trained and tested using feature values extracted from the past five-year closing price of stocks of different sectors including aviation, pharma, banking, entertainment, and IT.
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