Similarity, Clustering, and Scaling Analysesfor the Foreign Exchange Market —Comprehensive Analysis on States of Market Participants with High-Frequency Financial Data

摘要

This article proposes mathematical methods to quantify states of market participants inthe foreign exchange market (FX market) and conduct comprehensive analysis on behaviorof market participants by means of high-frequency financial data. Based on econophysicstools and perspectives we study similarity measures for both rate movements and quotationactivities among various currency pairs. We perform also clustering analysis on market statesfor observation days, and find scaling relationship between mean values of quotation activitiesand their standard deviations. Using these mathematical methods we can visualize statesof the FX market comprehensively. Finally we conclude that states of market participantstemporally vary due to both external and internal factors.