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Standardizing Intraday Stock Volume with Time-of-Day Z-Scores

Article Quant Q&A · Author: Tristan
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Summary

The document discusses a volume feature used in a study of flocking behavior among US equities. The feature standardizes a stock’s trading volume for a particular minute of the trading day: compare that minute’s observed volume with its historical average for the same stock and minute, then scale the difference by the historical standard deviation. This accounts for the regular intraday pattern in which trading is typically heavier near the open and close than around midday, and makes volumes more comparable across stocks with different typical activity.

The cited study reports that its genetic individuals often predicted movement when volume had been low three minutes earlier and was high at the current minute. The questioner asks whether the reference averages are calculated across multiple days; the document itself does not resolve that ambiguity or specify the historical sample window. It also gives no independent test of the signal’s predictive value. The explanation clarifies the normalization concept, but readers would need the original study’s implementation details to reproduce it precisely.

Key ideas

  • A volume z-score compares observed volume with a stock’s typical volume for the same minute of the trading day.
  • The deviation from the minute-specific average is scaled by its standard deviation.
  • Minute-specific normalization accounts for recurring intraday volume patterns and differences between stocks.
  • The cited study associates a recent rise from low volume with predicted stock movement, but the document does not establish predictive performance.
  • The historical averaging window is not specified in the document.

Tags

EquitiesStatisticsMomentumTechnical indicators
Full text
# Question about the "VolZScore" in this article about applying the Boids algorith to equities to find flocking behavior


# Question about the "VolZScore" in this article about applying the Boids algorith to equities to find flocking behavior












In this article, "Flocking behavior of US equities":

https://www.cs.dartmouth.edu/~lorenzo/teaching/cs174/Archive/Winter2013/Projects/FinalReportWriteup/ira.r.jenkins.gr/final.html

They use a metric, "VolZScore". They conclude regarding this metric:

> The current volume and volume three minutes ago are important Many of the genetic individuals predicted a movement when the trading volume three minutes in the past was low, but current volume was high. This indicates that volume has recently increased when previously it was low. Something was up with that stock!

However, I don't quite understand what this metric actually is. They say:

> Our approach is to first calculate a Z-score for each minute of trading. This is calculated by first determining the average number of shares traded per minute of each trading day (this varies considerably during the day, where right after the market open and right before the market close average share volume is typically much higher than during the middle of the day) and the standard deviation of the number of shares at each minute. Then for each sample, we take the current shares trades and subtract the average shares traded for that minute. We divide this by the standard deviation of the number of shares traded. VolZScore = (v - μ)/σ Where: v = volume for this minute of the trading day μ = average volume for this stock for this minute of the trading day σ = standard deviation for this stock for this minute of the trading day. In this way we normalize a score for all stocks, whether they trade relatively high volumes or whether they trade relatively low volumes.

And:

> NOTE: we normalized these scores by this formula: VolZScore = (v - μ)/σ Where: v = volume for this minute of the trading day μ = average volume for this stock for this minute of the trading day σ = standard deviation for this stock for this minute of the trading day

I'm not sure what this means. Is this using data only for the current day? Or is this using historical averages?

For μ, the term "average" is confusing me. Is this an average volume over many days for that stock? Since if it was just one minute, there would be no average, just a single volume number.

And if so, σ is hen the standard deviation in the average volume for a stock, in a specific minute of the day? I am not sure if I am understanding this correctly.

If anyone understands what exactly this VolZScore means, please educate me.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

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