Application of spectral methods for high-frequency financial data to quantifying states of market participants

Authored by Aki-Hiro Sato

Date Published: 2008-06-15

DOI: 10.1016/j.physa.2008.01.044

Sponsors: Japanese Ministry of Education, Culture, Sports, Science and Technology

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Empirical analysis of the foreign exchange market is conducted based on methods to quantify similarities among multidimensional time series with spectral distances introduced in [A.-H. Sato, Physica A 382 (2007) 258-270]. As a result it is found that the similarities among currency pairs fluctuate with the rotation of the earth, and that the similarities among best quotation rates are associated with those among quotation frequencies. Furthermore, it is shown that the Jensen-Shannon spectral divergence is proportional to a mean of the Kullback-Leibler spectral distance both empirically and numerically. It is confirmed that these spectral distances are connected with distributions for behavioural parameters of the market participants from numerical simulation. This concludes that spectral distances of representative quantities of financial markets are related into diversification of behavioural parameters of the market participants. (C) 2008 Elsevier B.V. All rights reserved.

Tags

Agent-based modelling econophysics spectral distance