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

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  • Sato, Aki-Hiro

Abstract

Empirical analysis of the foreign exchange market is conducted based on methods to quantify similarities among multi-dimensional 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.

Suggested Citation

  • Sato, Aki-Hiro, 2008. "Application of spectral methods for high-frequency financial data to quantifying states of market participants," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(15), pages 3960-3966.
    • Handle: RePEc:eee:phsmap:v:387:y:2008:i:15:p:3960-3966
    DOI: 10.1016/j.physa.2008.01.044
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    Cited by:

    1. Maharaj, Elizabeth Ann & D’Urso, Pierpaolo, 2010. "A coherence-based approach for the pattern recognition of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(17), pages 3516-3537.

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