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Measuring Quote Activity with a Rhythm-Adjusted ACD Model

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Summary

This document describes a MetaTrader indicator that measures how quickly quotes arrive relative to the normal pace for that time of day. It converts quote changes into events, combines records stamped in the same millisecond, treats long gaps as session breaks, and learns a smoothed intraday rhythm. An autoregressive conditional duration model then updates expected quote waiting time after each event. The resulting activity ratio is one at the fitted normal pace, higher during unusually rapid quote arrivals, and lower during quieter periods. The author contrasts this live measure with bar-based tick volume, which is affected by time of day and cannot provide a finished count before a bar closes.

A volatility forecasting study compares activity measures with recent volatility as a baseline. Across six symbols and a thirty-day sample, the document reports that mid-bar activity measures add predictive information, including a further contribution from the ACD gauge after live volatility is included. Gains are described as modest and vary by horizon and asset. Caveats include broker-specific parameters, a need for tick history and periodic refitting, feeds whose quotes are timer-driven, and an indicator that can remain elevated during silence until another quote arrives. The results do not establish a trading strategy or out-of-sample profitability.

Key ideas

  • The gauge uses inter-quote waiting times and adjusts them for the normal intraday rhythm.
  • An ACD recursion updates expected waiting time as each quote event arrives, enabling a live activity ratio.
  • Same-millisecond quote records are folded together, while long waits trigger a session reset.
  • The reported forecast gains over recent volatility are modest and depend on symbol and forecast horizon.
  • Parameters are broker- and symbol-sensitive, and the model can misread timer-driven feeds or sudden silence.

Tags

ForexMarket microstructureStatisticsVolatilityTechnical indicatorsBacktesting

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.