Article Title

Competitive Models to Detect Stock Manipulation

Authors

Jose J. Thoppan, Saintgits Institute of Management, India
Punniyamoorthy M., National Institute of Technology – Tiruchirappalli, India
Ganesh K., McKinsey & Company, Inc.

Abstract

In this paper, data from the Indian stock market is used to study the prediction accuracy of various classification techniques that can be used to identify market manipulation. The data contains information regarding price, volume and volatility of various stocks. Techniques like discriminant analysis, a composite model based on artificial neural network – genetic algorithm (ann-ga) and support vector machine (svm) have been used for classifying stocks into manipulated and non manipulated categories. It is observed that the support vector machine based technique gives the best classification accuracy among the three techniques.

Recommended Citation

Thoppan, Jose J.; M., Punniyamoorthy; and K., Ganesh (2017) "Competitive Models to Detect Stock Manipulation," Communications of the IIMA: Vol. 15: Iss. 2, Article 5.
DOI: https://doi.org/10.58729/1941-6687.1385
Available at: https://scholarworks.lib.csusb.edu/ciima/vol15/iss2/5