Analyzing and Predicting Market Trends using SVM

Authors

  • Akhilesh Rane Department of Computer Engineering, Pimpri Chinchwad College of Engineering & Research, Ravet
  • Dheeraj Sukhnani Department of Computer Engineering, Pimpri Chinchwad College of Engineering & Research, Ravet
  • Meghana Arali Department of Computer Engineering, Pimpri Chinchwad College of Engineering & Research, Ravet
  • Priya Mishra Department of Computer Engineering, Pimpri Chinchwad College of Engineering & Research, Ravet
  • Prof. Ompriya Kale Department of Computer Engineering, Pimpri Chinchwad College of Engineering & Research, Ravet

Keywords:

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Abstract

Support Vector Machine is a popular machine learning technique which can be used to forecast stock
prices effectively. This study uses daily closing prices for different stocks to predict future stock patterns. The
available stock patterns are used as input parameters to the SVM model. The model attempts to predict whether a
stock price in the future will be higher or lower than it is presently. Our results suggest that SVM is a powerful
predictive tool for predicting stocks in the commercial market.

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Published

2018-03-25

How to Cite

Akhilesh Rane, Dheeraj Sukhnani, Meghana Arali, Priya Mishra, & Prof. Ompriya Kale. (2018). Analyzing and Predicting Market Trends using SVM. International Journal of Advance Research in Engineering, Science & Technology, 5(3), 902–906. Retrieved from https://ijarest.org/index.php/ijarest/article/view/1389

Issue

Vol. 5 No. 3 (2018): Volume: 05, Issue: 03 - March, 2018.

Section

Articles