quant research // summarizing the paperLOADING
Tim Gebbie · 2026-07-05
The paper argues that at very high frequencies, cross-asset correlation cannot be measured in clock time alone but depends on how you slice time (calendar time, number of trades, or volume buckets) and on market activity and order flow. It proposes an 'uncertainty principle': the more precisely you pin down market activity in time, the worse you can resolve stable correlations between assets, and vice versa. From this it distills six rules of thumb for traders operating faster than human reaction times.
Why it matters: For high-frequency market makers and those arbitraging across books and venues, the framing suggests that measured correlations depend heavily on the clock and window you choose, which can introduce what the paper calls 'clock risk.' It's a conceptual lens that may help practitioners think more carefully about how they estimate short-horizon cross-asset dependence.
⚠ This is a conceptual/theoretical framework aimed at sub-human-reaction-time trading, with no empirical backtest or performance results reported in the abstract.
We propose a Gabor--Epps uncertainty principle for practical trading. The key idea is that high-frequency correlation is not observed in clock time alone, but is resolved through market activity, order-flow overlap, and finite coupling response. This suggests six simple rules of thumb that may be useful to traders and trading programs operating at market-making frequencies, particularly those crossing books and markets below the average human response time. Throughout, the observation window is clock-dependent: in calendar time it is a physical interval, in trade time it is a trade-count interval, and in volume time it is a volume bucket. In summary: at event scales, the more precisely one localises market activity in time, the less well one can resolve stable cross-asset dependence. The more one resolves dependence, the more one has coarse-grained away the event-time structure that generated it. This can generate substantial clock risk.
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AI summary generated from the paper’s public abstract via arXiv; it may miss nuance — read the source before relying on it. Thank you to arXiv for its open-access interoperability; StockTools is not affiliated with arXiv, and all rights remain with the authors. Educational only, not financial advice.