Measuring and Modelling of participants' behaviour in financial markets

Abstract

This article proposes methods to measure states of market participants based on their behavioral patterns both comprehensively and circumstantially. In order to quantify monopolization of trading patterns the normalized information entropy for relative frequencies of quotations/transactions estimated from high-resolution data of financial markets is employed. The empirical results by using high-resolution data of the foreign exchange market are shown and an agent-based explanatory model is considered in order to understand meaning of proposal indices. It is concluded that the proposal methods may measure participants' behavioral patterns associated with their cognitive patterns.