Transition in the waiting-time distribution of price-change events in a global socioeconomic system

Guannan Zhao, Mark McDonald, Dan Fenn, Stacy Williams, Nicholas Johnson, Neil F. Johnson

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

The goal of developing a firmer theoretical understanding of inhomogeneous temporal processes-in particular, the waiting times in some collective dynamical system-is attracting significant interest among physicists. Quantifying the deviations between the waiting-time distribution and the distribution generated by a random process may help unravel the feedback mechanisms that drive the underlying dynamics. We analyze the waiting-time distributions of high-frequency foreign exchange data for the best executable bid-ask prices across all major currencies. We find that the lognormal distribution yields a good overall fit for the waiting-time distribution between currency rate changes if both short and long waiting times are included. If we restrict our study to long waiting times, each currency pair's distribution is consistent with a power-law tail with exponent near to 3.5. However, for short waiting times, the overall distribution resembles one generated by an archetypal complex systems model in which boundedly rational agents compete for limited resources. Our findings suggest that a gradual transition arises in trading behavior between a fast regime in which traders act in a boundedly rational way and a slower one in which traders' decisions are driven by generic feedback mechanisms across multiple timescales and hence produce similar power-law tails irrespective of currency type.

Original languageEnglish (US)
Pages (from-to)6458-6469
Number of pages12
JournalPhysica A: Statistical Mechanics and its Applications
Volume392
Issue number24
DOIs
StatePublished - Dec 15 2013

Keywords

  • Agent based model
  • Foreign exchange market
  • Lognormal distribution
  • Power-law distribution
  • Waiting-time distribution

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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