Measuring stock price manipulation using entropy analysis: A conceptual framework

Abstract

The stock markets of developed and developing countries have witnessed online trading, dematerialization of securities, rolling settlements and tight settlement cycles, over the last two decades. However, market regulators face the challenge of clamping down on price manipulation and trading, based on inside information. While the regulators rely on sequential patterns or features in the stock price and the trade volume, which present themselves to study price rigging, academicians have studied the same under various situations like asymmetric information, imperfect competition, financial signaling and front running. This paper discusses the suitability of the information theoretic concept of entropy and its different versions, viz., approximate entropy, sample entropy and multi-scale entropy, to study price manipulation in stock market.