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Optimal Feature Selection of Technical Indicator and Stock Prediction Using Machine Learning Technique by Nagaraj Naik; Biju R. Mohan is a book available to read on EtoBox.

What is Optimal Feature Selection of Technical Indicator and Stock Prediction Using Machine Learning Technique about?

Short-term trading is a difficult task due to fluctuating demand and supply in the stock market. These demands and supply are reflected in stock prices. The stock prices may be predicted using technical indicators. Most of the existing literature considered the limited technical indicators to measure short-term prices. We have considered 33 different combinations of technical indicators to predict the stock prices. The paper has two objectives, first is the technical indicator feature selection and identification of the relevant technical indicators by using Boruta feature selection technique. The second objective is an accurate prediction model for stocks. To predict stock prices we have proposed ANN (Artificial Neural Network) Regression prediction model and model performance is evaluated using metrics is Mean absolute error (MAE) and Root mean square error (RMSE). The experimental results are better than the existing method by decreasing the error rate in the prediction to 12%. We have used the National Stock Exchange, India (NSE) data for the experiment.

Author

Nagaraj Naik; Biju R. Mohan

Publisher

Springer Singapore : Imprint: Springer

Published

2019

Language

EN

ISBN

9789811382994

Subjects

Mathematics, Engineering, Computer Science

Rating

5 / 5 (1 ratings)

Updated

2026-03-24