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Agent-based modelling in directional-change intrinsic time

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  • V. Petrov
  • A. Golub
  • R. Olsen

Abstract

We describe an agent-based model where trades happen in event-based time called directional-change intrinsic time. Events are defined as the reversal price moves of a directional-change threshold from a local extreme. The price impact of traded volumes is modelled according to the empirically observed squared root impact function. The time series generated by the agents is characterised by statistical properties typical for foreign-exchange rates: low autocorrelation of returns, fat-tailed distribution of returns, aggregated normality, and the price jump scaling law. Furthermore, we introduce and use as a benchmark, the overshoot scaling law, which is an omnipresent feature of liquid markets and relates the expected length of price overshoots to the length of the corresponding directional-change threshold.

Suggested Citation

  • V. Petrov & A. Golub & R. Olsen, 2020. "Agent-based modelling in directional-change intrinsic time," Quantitative Finance, Taylor & Francis Journals, vol. 20(3), pages 463-482, March.
    • Handle: RePEc:taf:quantf:v:20:y:2020:i:3:p:463-482
    DOI: 10.1080/14697688.2019.1669809
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    Cited by:

    1. Ao, Han & Li, Munan, 2024. "Exploiting the potential of a directional changes-based trading algorithm in the stock market," Finance Research Letters, Elsevier, vol. 60(C).
    2. James B. Glattfelder & Anton Golub, 2022. "Bridging the Gap: Decoding the Intrinsic Nature of Time in Market Data," Papers 2204.02682, arXiv.org.

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