Trend volume_breakout

Volume breakout

Detects unusual volume spikes exceeding N× the rolling average. Bullish: volume spike on a close above the prior day's close. Bearish: volume spike on a close below the prior day's close. A spike with an unchanged close does not trigger.

Signal family

Trend — Signals that fire when price is continuing or reversing an established directional move. Momentum-following by nature.

Parameters

Name Description Default Range
period Average volume lookback (days) 20 5–100
multiplier Volume multiplier threshold 2.0 1.5–5.0

Historical context

3,067,357 triggers on 24,029 tickers, 1995-09-27 → 2026-05-01. Universe: global — all covered exchanges (mcap ≥ $100,000,000, price ≥ $1). Long-only convention: BUY at open T+1, hold the horizon, compare to S&P 500 Equal Weight over the same window.

Methodology footnotes

Benchmarks shown in the detail tables: spxew (S&P 500 Equal Weight — primary, median-stock view, avoids the 2020+ megacap-concentration distortion), spx (S&P 500 cap-weighted, distorted post-2020), msci (MSCI World USD). Per-stock regime tags: trending = ADX(14) ≥ 25, high vol = 20d realized annualized vol ≥ 20%. 1d return = intraday T+1 open→close; 20d = open T+1 to close T+20.

At a glance — alpha vs S&P 500 Equal Weight, global universe

Holding-period sensitivity. Bullish columns: positive = signal worked (long the trigger beat the index). Bearish columns: negative = signal worked (the flagged stock underperformed).

Horizon Bullish α Bearish α
5-day -0.11% +0.03%
20-day +0.28% +0.23%
60-day +0.83% +0.54%
1-year +5.26% +3.87%
Random-date null check (20-day): Bullish: beats random (p=0.005).
Bearish: worse than random (p=1.000).

Where does VOLUME_BREAKOUT actually fire?

The bucket distribution often reveals what the signal really is, regardless of its textbook label. Heavy concentration in "non-trending + high vol" = it's mostly a chop-market event. Heavy in "trending + low vol" = it picks up the smooth grinds. Read the chart before the alpha numbers — context shapes everything that follows.

Volume breakout (volume_breakout) — trigger count distribution by per-stock regime quadrant (trending/non-trending × high/low realized volatility) for bullish and bearish triggers, global universe

Does it work in every regime?

Trigger alpha split by the host stock's own regime on the trigger date — trending or ranging, high-vol or low-vol. The 20d alpha you'd actually capture if you took the trade. Bars matching your direction's "right" sign (positive for bullish, negative for bearish) = the signal worked in that regime; opposite sign = avoid it there. A signal with one strong-positive bar and three flat ones isn't a "20d alpha" signal — it's a "20d alpha when the stock is X" signal.

Volume breakout (volume_breakout) — mean 20-day alpha versus S&P 500 Equal Weight by per-stock regime quadrant, bullish and bearish triggers side by side
Trending + Low vol
Stock in a clean directional move with low realized volatility. Textbook "trend-following paradise" — smooth grind with little whipsaw risk.
Trending + High vol
Violent directional moves — parabolic rallies, crisis selloffs. Trend exists but the path is noisy. Signal timing may be imprecise.
Non-trending + Low vol
Quiet chop, summer doldrums, consolidations. No directional bias but also no big swings — small edges become reliable if they exist at all.
Non-trending + High vol
Choppy and violent — the classical "whipsaw zone" for momentum signals. Crossovers and breakouts fire repeatedly without follow-through.

Does it work in every era?

A multi-year average can hide major instability. The sample splits into three windows: 2015–2019 (pre-COVID), 2020–2022 (pandemic + 2022 bear), and 2023+ (post-ZIRP + AI megacap rally). All three matching your direction's "right" sign = the signal is durable. One era doing all the work = a regime-specific edge that may not repeat. The bigger the variance across eras, the smaller the position you should run.

Volume breakout (volume_breakout) — 20-day alpha split by historical sub-period (2015-2019, 2020-2022, 2023+) to check consistency across market regimes

↑ Bullish triggers

Bench Metric 1d 5d 20d 60d 252d
spxew Stock % -0.03% +0.10% +1.05% +3.10% +15.32%
Bench % +0.04% +0.20% +0.81% +2.28% +10.16%
Alpha % -0.08% -0.11% +0.28% +0.83% +5.26%
Median alpha -0.20% -0.57% -1.15% -2.45% -6.70%
Hit rate (α>0) 45.9% 45.2% 45.1% 43.8% 42.4%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 <0.001 <0.001 <0.001 <0.001
N 1,778,965 1,709,651 1,701,655 1,667,356 1,478,228
spx Stock % -0.03% +0.10% +1.05% +3.10% +15.32%
Bench % +0.02% +0.22% +1.00% +3.05% +13.85%
Alpha % -0.07% -0.14% +0.08% +0.04% +1.40%
Median alpha -0.19% -0.61% -1.38% -3.28% -10.70%
Hit rate (α>0) 45.9% 44.8% 44.0% 41.9% 38.4%
p (naive) <0.001 <0.001 <0.001 0.0169 <0.001
p (HAC) <0.001 <0.001 <0.001 0.2782 <0.001
N 1,793,860 1,731,659 1,722,001 1,689,161 1,498,664
msci Stock % -0.03% +0.10% +1.05% +3.10% +15.32%
Bench % +0.05% +0.22% +0.87% +2.62% +11.41%
Alpha % -0.09% -0.13% +0.21% +0.49% +3.77%
Median alpha -0.22% -0.60% -1.27% -2.86% -8.33%
Hit rate (α>0) 45.3% 44.7% 44.5% 42.8% 40.8%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 <0.001 <0.001 <0.001 <0.001
N 1,783,866 1,721,779 1,714,095 1,677,545 1,489,371
Observed 20-day lift (vertical line) against the null distribution of random-date firing. If the line is deep inside the null cloud, the signal adds no information. If it sits in the right tail, the signal is doing real work in that direction; in the left tail it ran inverted — random dates served the bullish case better than its own triggers did.
Volume breakout (volume_breakout) — bullish 20-day observed lift versus random-date permutation null (200 iterations)
Permutation null detail — all horizons × each benchmark
200-iteration null: for each ticker, sample N random dates from its history (matching observed trigger count) and compute the same alpha. Both observed and null are baseline-centered per ticker (each ticker's own baseline alpha is subtracted), which removes the universe-selection lift that all surviving names share, so the comparison is about the trigger's timing. It does not put the null at zero: that baseline is a median, while a random date's expectation is the ticker's mean, so the null settles at the gap between the two — the right-skew of the ticker's own alpha distribution, positive for equities. Read observed minus null, not the absolute position of either column — which is also why these figures do not match the α columns in the tables above (those are raw, uncentered means). pperm = one-sided fraction of null iters with mean in the "signal was right" tail (right for bullish, left for bearish), so it runs from a floor of 0.005 (trigger dates beat every random draw in the claimed direction) to a 1.000 ceiling (every random draw served the claimed direction better — a reliably inverted signal, not an absent one). The floor is 1/(iterations + 1) and moves with the iteration count; the ceiling does not. Either end says the result was reliable, not that it was large: the gap between the line and the cloud can be a fraction of a percent and still reach an endpoint, and the transaction-cost floor in the caveats below would swallow a gap that small. Read the size off the α and hit-rate columns, the reliability off pperm.
Horizon Bench Observed lift Null mean Null 95% CI pperm
1d spxew +0.09% +0.10% [+0.09%, +0.10%] 0.955
1d spx +0.09% +0.10% [+0.10%, +0.11%] 1.000
1d msci +0.10% +0.11% [+0.10%, +0.11%] 1.000
5d spxew +0.37% +0.43% [+0.42%, +0.44%] 1.000
5d spx +0.38% +0.44% [+0.43%, +0.45%] 1.000
5d msci +0.39% +0.45% [+0.44%, +0.45%] 1.000
20d spxew +1.48% +1.36% [+1.34%, +1.38%] 0.005
20d spx +1.51% +1.39% [+1.37%, +1.40%] 0.005
20d msci +1.52% +1.40% [+1.38%, +1.42%] 0.005
60d spxew +2.91% +2.88% [+2.85%, +2.91%] 0.020
60d spx +2.87% +2.93% [+2.91%, +2.97%] 1.000
60d msci +2.90% +2.95% [+2.93%, +2.99%] 1.000
252d spxew +5.54% +5.05% [+4.96%, +5.13%] 0.005
252d spx +5.85% +5.42% [+5.33%, +5.50%] 0.005
252d msci +5.86% +5.34% [+5.25%, +5.42%] 0.005

Example triggers on US large-caps (2023+, mcap ≥ $30B)

Six recent bullish VOLUME_BREAKOUT triggers on US mega-caps. Top three: the signal's best outcomes. Bottom three: the worst. Extreme outliers (|α| > 25%) excluded. The three best and three worst are still tail outcomes by construction — read them as the range, not the typical result.

Strongest outcomes (what VOLUME_BREAKOUT looks like when it works)
Volume breakout (volume_breakout) — strongest bullish trigger #1 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window Volume breakout (volume_breakout) — strongest bullish trigger #2 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window Volume breakout (volume_breakout) — strongest bullish trigger #3 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window
Weakest outcomes (what VOLUME_BREAKOUT looks like when it fails)
Volume breakout (volume_breakout) — weakest bullish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed Volume breakout (volume_breakout) — weakest bullish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed Volume breakout (volume_breakout) — weakest bullish trigger #3 on a US mega-cap, showing the 20-day forward window where the signal failed
Stock-regime quadrants (2×2 per-stock, 20d alpha detail table)
Each quadrant groups triggers by the stock's own ADX(14) and RV(20) at the trigger date — the textbook conditioning variable (not market-level). Stock %, bench %, alpha %, and HAC p-value shown for each benchmark.
Quadrant N Stock % (spxew) Bench % (spxew) Alpha % (spxew) p (HAC) Stock % (spx) Bench % (spx) Alpha % (spx) p (HAC) Stock % (msci) Bench % (msci) Alpha % (msci) p (HAC)
Trending + Low vol Clean directional grind, low whipsaw 113,550 +0.88% +0.50% +0.42% <0.001 +0.88% +0.78% +0.12% 0.0003 +0.88% +0.63% +0.28% <0.001
Trending + High vol Crisis selloff or parabolic rally 739,669 +1.15% +0.82% +0.35% <0.001 +1.15% +1.03% +0.13% <0.001 +1.15% +0.88% +0.27% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 177,233 +0.75% +0.57% +0.20% <0.001 +0.75% +0.80% -0.04% 0.0649 +0.75% +0.67% +0.10% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 828,750 +1.10% +0.89% +0.25% <0.001 +1.10% +1.04% +0.09% 0.0001 +1.10% +0.94% +0.19% <0.001
Sub-period breakdown table (20d alpha)
Historical clustering check. If alpha concentrates in one era, the signal's robustness is questionable.
Period N Alpha % (spxew) p (HAC) Alpha % (spx) p (HAC) Alpha % (msci) p (HAC)
2015-2019 2015-01-01 → 2020-01-01 580,282 -0.27% <0.001 -0.47% <0.001 -0.27% <0.001
2020-2022 2020-01-01 → 2023-01-01 545,904 +0.31% <0.001 +0.51% <0.001 +0.64% <0.001
2023-2026 2023-01-01 → 2099-01-01 732,448 +0.73% <0.001 +0.22% <0.001 +0.28% <0.001

↓ Bearish triggers negative alpha = signal was right (stock underperformed market)

Bench Metric 1d 5d 20d 60d 252d
spxew Stock % +0.01% +0.19% +1.11% +3.16% +14.38%
Bench % +0.04% +0.16% +0.85% +2.61% +10.58%
Alpha % -0.02% +0.03% +0.23% +0.54% +3.87%
Median alpha -0.09% -0.27% -0.74% -1.76% -6.01%
Hit rate (α>0) 48.0% 47.4% 46.3% 45.0% 42.6%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 <0.001 <0.001 <0.001 <0.001
N 1,156,821 1,116,747 1,107,712 1,082,836 979,077
spx Stock % +0.01% +0.19% +1.11% +3.16% +14.38%
Bench % +0.01% +0.21% +1.13% +3.39% +14.41%
Alpha % -0.01% -0.02% -0.01% -0.21% -0.04%
Median alpha -0.08% -0.31% -0.99% -2.56% -10.01%
Hit rate (α>0) 48.1% 46.9% 45.1% 43.0% 38.4%
p (naive) 0.0003 0.0037 0.2951 <0.001 0.4285
p (HAC) 0.0003 0.0100 0.4374 <0.001 0.7784
N 1,168,053 1,131,719 1,122,261 1,098,698 994,241
msci Stock % +0.01% +0.19% +1.11% +3.16% +14.38%
Bench % +0.04% +0.21% +0.99% +2.98% +12.03%
Alpha % -0.02% -0.00% +0.11% +0.24% +2.16%
Median alpha -0.10% -0.30% -0.87% -2.13% -7.72%
Hit rate (α>0) 47.7% 47.0% 45.6% 44.0% 40.8%
p (naive) <0.001 0.6769 <0.001 <0.001 <0.001
p (HAC) <0.001 0.7116 <0.001 <0.001 <0.001
N 1,162,188 1,126,052 1,114,873 1,092,867 987,174
Observed 20-day lift (vertical line) against the null distribution of random-date firing. If the line is deep inside the null cloud, the signal adds no information. If it sits in the left tail, the signal is doing real work in that direction; in the right tail it ran inverted — random dates served the bearish case better than its own triggers did.
Volume breakout (volume_breakout) — bearish 20-day observed lift versus random-date permutation null (200 iterations)
Permutation null detail — all horizons × each benchmark
200-iteration null: for each ticker, sample N random dates from its history (matching observed trigger count) and compute the same alpha. Both observed and null are baseline-centered per ticker (each ticker's own baseline alpha is subtracted), which removes the universe-selection lift that all surviving names share, so the comparison is about the trigger's timing. It does not put the null at zero: that baseline is a median, while a random date's expectation is the ticker's mean, so the null settles at the gap between the two — the right-skew of the ticker's own alpha distribution, positive for equities. Read observed minus null, not the absolute position of either column — which is also why these figures do not match the α columns in the tables above (those are raw, uncentered means). pperm = one-sided fraction of null iters with mean in the "signal was right" tail (right for bullish, left for bearish), so it runs from a floor of 0.005 (trigger dates beat every random draw in the claimed direction) to a 1.000 ceiling (every random draw served the claimed direction better — a reliably inverted signal, not an absent one). The floor is 1/(iterations + 1) and moves with the iteration count; the ceiling does not. Either end says the result was reliable, not that it was large: the gap between the line and the cloud can be a fraction of a percent and still reach an endpoint, and the transaction-cost floor in the caveats below would swallow a gap that small. Read the size off the α and hit-rate columns, the reliability off pperm.
Horizon Bench Observed lift Null mean Null 95% CI pperm
1d spxew +0.12% +0.08% [+0.07%, +0.08%] 1.000
1d spx +0.12% +0.09% [+0.08%, +0.09%] 1.000
1d msci +0.14% +0.09% [+0.09%, +0.10%] 1.000
5d spxew +0.45% +0.36% [+0.35%, +0.37%] 1.000
5d spx +0.44% +0.37% [+0.36%, +0.39%] 1.000
5d msci +0.45% +0.38% [+0.36%, +0.39%] 1.000
20d spxew +1.35% +1.15% [+1.13%, +1.18%] 1.000
20d spx +1.34% +1.19% [+1.16%, +1.21%] 1.000
20d msci +1.34% +1.19% [+1.17%, +1.22%] 1.000
60d spxew +2.75% +2.45% [+2.42%, +2.49%] 1.000
60d spx +2.74% +2.52% [+2.48%, +2.56%] 1.000
60d msci +2.76% +2.52% [+2.49%, +2.57%] 1.000
252d spxew +5.93% +4.76% [+4.70%, +4.84%] 1.000
252d spx +6.14% +5.12% [+5.06%, +5.19%] 1.000
252d msci +6.02% +5.05% [+4.99%, +5.13%] 1.000

Example triggers on US large-caps (2023+, mcap ≥ $30B)

Six recent bearish VOLUME_BREAKOUT triggers on US mega-caps. Top three: the signal's best outcomes. Bottom three: the worst. Extreme outliers (|α| > 25%) excluded. The three best and three worst are still tail outcomes by construction — read them as the range, not the typical result.

Strongest outcomes (what VOLUME_BREAKOUT looks like when it works)
Volume breakout (volume_breakout) — strongest bearish trigger #1 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window Volume breakout (volume_breakout) — strongest bearish trigger #2 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window Volume breakout (volume_breakout) — strongest bearish trigger #3 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window
Weakest outcomes (what VOLUME_BREAKOUT looks like when it fails)
Volume breakout (volume_breakout) — weakest bearish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed Volume breakout (volume_breakout) — weakest bearish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed Volume breakout (volume_breakout) — weakest bearish trigger #3 on a US mega-cap, showing the 20-day forward window where the signal failed
Stock-regime quadrants (2×2 per-stock, 20d alpha detail table)
Each quadrant groups triggers by the stock's own ADX(14) and RV(20) at the trigger date — the textbook conditioning variable (not market-level). Stock %, bench %, alpha %, and HAC p-value shown for each benchmark.
Quadrant N Stock % (spxew) Bench % (spxew) Alpha % (spxew) p (HAC) Stock % (spx) Bench % (spx) Alpha % (spx) p (HAC) Stock % (msci) Bench % (msci) Alpha % (msci) p (HAC)
Trending + Low vol Clean directional grind, low whipsaw 95,421 +0.26% +0.57% -0.33% <0.001 +0.26% +0.89% -0.64% <0.001 +0.26% +0.71% -0.46% <0.001
Trending + High vol Crisis selloff or parabolic rally 462,507 +1.61% +0.94% +0.64% <0.001 +1.61% +1.26% +0.36% <0.001 +1.61% +1.07% +0.50% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 142,579 +0.40% +0.67% -0.22% <0.001 +0.40% +0.89% -0.47% <0.001 +0.40% +0.75% -0.32% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 507,619 +1.06% +0.92% +0.13% <0.001 +1.06% +1.16% -0.07% 0.0016 +1.06% +1.03% +0.02% 0.3513
Sub-period breakdown table (20d alpha)
Historical clustering check. If alpha concentrates in one era, the signal's robustness is questionable.
Period N Alpha % (spxew) p (HAC) Alpha % (spx) p (HAC) Alpha % (msci) p (HAC)
2015-2019 2015-01-01 → 2020-01-01 382,681 -0.24% <0.001 -0.38% <0.001 -0.15% <0.001
2020-2022 2020-01-01 → 2023-01-01 352,450 +0.15% <0.001 +0.20% <0.001 +0.34% <0.001
2023-2026 2023-01-01 → 2099-01-01 472,499 +0.69% <0.001 +0.15% <0.001 +0.15% <0.001

Methodology and caveats

How to read. Entry at open of T+1 (one trading day after the signal fires on close of T). 20d = open T+1 to close T+20. Alpha = stock return − benchmark return over the same window (Convention A, single-sided, textbook). For bullish triggers, POSITIVE alpha = signal was right. For bearish triggers, NEGATIVE alpha = signal was right (stock underperformed market). No sign-flipping; the direction of the bet determines what "good" looks like. Per-stock regime is each stock's own ADX(14) and RV(20) at the trigger date — not market-wide state.

Three p-values, three robustness tests. (a) p_naive: scipy one-sample t-test on winsorized alphas. Optimistic because overlapping 20d windows on the same ticker inflate effective N. (b) p_hac: Newey-West HAC with lag = horizon — corrects for the overlap and is the academic-finance standard. (c) p_perm: one-sided fraction of 200 random-date null iterations falling in the “signal was right” tail (mean ≥ observed for bullish; mean ≤ observed for bearish). Tests whether the signal beats random date selection at all. A signal that clears all three (pnaive, phac, pperm all < 0.05) has real information; a signal that fails pperm has not beaten random timing whatever the t-test says — and because the test is one-sided, a pperm up at its 1.000 ceiling is not "no edge" but inverted edge: every random draw served the claimed direction better than the trigger dates did.

Caveats. (i) Universe reflects today's active tickers; delisted losers pruned → survivorship bias. (ii) Mcap ≥ $100M filter uses today's snapshot, not point-in-time — mild lookahead on which stocks enter the sample, not on returns. (iii) Means and p-values use winsorized alphas (1/99 percentile) to prevent data errors from dominating. Medians and hit rates use raw data. (iv) Zero transaction costs assumed. Realistic bid-ask + commissions remove 20–40bps from 20d alpha on US large-caps, more on small-cap. Sub-20bps alpha is noise in practice. (v) Past performance does not predict future results.

How to use this

1 · When to reach for this signal

Use Volume breakout bullish as a long-side screening tile. Bullish 20d alpha is +0.28% and beats random (permutation test, 200 iterations). Bearish 20d alpha is +0.23% — worse than random : firing on random dates would have done better.

These verdicts are 20-day holds vs S&P 500 Equal Weight. Longer horizons can differ in either direction — check the permutation detail tables below before extrapolating.

2 · When it works — the setups that drive it

  • Best bullish setup: Trending + Low vol — alpha +0.42% / 20d on 113,550 historical triggers.
  • Best bearish setup: Trending + Low vol — alpha -0.33% / 20d on 95,421 historical triggers.
  • Best era for bullish: 2023-2026 — alpha +0.73% / 20d on 732,448 triggers.
  • Best era for bearish: 2015-2019 — alpha -0.24% / 20d on 382,681 triggers.

3 · When it fails — common false positives

  • Weakest bullish cell: Non-trending + Low vol — alpha +0.20% / 20d on 177,233 triggers.
  • Weakest bearish cell: Trending + High vol — alpha +0.64% / 20d on 462,507 triggers.
  • Worst era for bullish: 2015-2019 — alpha -0.27% / 20d on 580,282 triggers.
  • Worst era for bearish: 2023-2026 — alpha +0.69% / 20d on 472,499 triggers.

Signal-specific failure patterns

A volume spike is an attention event, not a direction event
The trigger is a day whose volume reaches at least 2x the trailing 20-day average, with direction assigned only by whether the close finished above or below the previous day's close (an unchanged close does not trigger). Many spike causes carry no forward return information at all: index rebalances, ETF creation/redemption flows, option expiry, block crossings, secondary offerings. The one-day close direction is a thin filter over that mixed population, so per-trigger information content is structurally diluted. Whether either direction currently clears the random-date baseline is shown by the permutation-null line above — read that, not this prose, for the current verdict.
The 20-day average denominator adapts and mutes follow-on signals
Because the threshold is relative to a rolling 20-day average, the first spike of an episode triggers easily, but the elevated days then feed into the average and raise the bar — the signal goes quiet precisely while the volume episode is still running. The reverse also holds: in seasonally quiet tape, a modest absolute volume day can clear the 2x bar. The signal is therefore best read as 'volume regime changed today relative to the recent past', not as a measure of absolute institutional interest.
Heavy-volume down days are the classic capitulation signature
A structural reason the bearish tag may not behave like a short signal: extreme volume on a down day is the textbook selling-climax pattern — concentrated liquidation absorbed by buyers — which classical technical analysis associates with exhaustion near lows rather than with continuation (the Wyckoff selling-climax concept; Murphy, Technical Analysis of the Financial Markets, 1999). If the bearish side fails the random-date null in the current tables above, treat bearish volume spikes as liquidity and attention context, or even as potential capitulation marks, rather than as short-side triggers; only if it clears the null does a short-side screen tile make sense.

4 · Pairing inside a screen

The statements below describe how this signal relates to others by construction — which indicator family it belongs to, and where same-family redundancy might reduce the independence of evidence inside a Daily Report. These are taxonomic classifications drawn from standard technical-analysis texts; they are not pairing backtests. Measured pair results — same-day co-fires put through the pair backtest — follow under “Measured pairings” below.

Complementary to price signals

Volume confirmation is a complementary principle to price signals, not a same-family redundancy. A price breakout or breakdown accompanied by above-average volume carries more weight in classical technical analysis than the same price move on thin volume (Murphy, Technical Analysis of the Financial Markets, 1999; Kirkpatrick & Dahlquist, Technical Analysis, 3rd ed. 2015). Combining volume_breakout with any price-based signal in the same direction adds weight rather than redundant evidence.

Measured pairings — Bonferroni survivors

Beyond the literature pairings above, these are the same-day co-fire combinations involving Volume breakout that cleared the pair backtest's Bonferroni cut on the full 2016–2026 sample (549 pairs × 5 horizons = 2,745 hypotheses), on universes filtered to ADV ≥ $5M, price ≥ $5 and market cap ≥ $100M. That cut is two-sided: it asks only whether the co-fire's α is reliably different from zero, in either direction, so a pair can survive by reliably underperforming — 12 of the 32 rows below do exactly that (negative full-sample α). The same run holds out 2023+: the Test columns are that held-out window, printed for every row with enough held-out co-fires to measure, so a survivor that did not repeat out of sample is visible rather than hidden. All α figures here are for holding the stock long after the co-fire — no shorting assumed, and no sign flip for bearish legs. So positive α means the co-fire was followed by outperformance and negative α by underperformance, whichever way either leg points — a bearish leg does not flip the reading. Survivors are rare by design — absence of a pair here means it did not clear the cut, not that it was untested. Ranked by held-out (2023+) α. Historical tendencies, not recommendations.

Europe

Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
bullish_trend_breakdown bearish + volume_breakout bearish +1.08% +1.65% 616 0.002
new_20d_high bullish + volume_breakout bullish +0.59% +0.69% 5,813 0.002

2 of this universe's 20 surviving pairs involve this signal · α vs ^STOXX.

Hong Kong — 6 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
macd bearish + volume_breakout bullish +5.41% +6.12% 24 0.052
macd bullish + volume_breakout bullish +1.52% +2.29% 897 0.002
bearish_trend_breakout bullish + volume_breakout bullish +1.69% +2.06% 907 0.002
new_20d_high bullish + volume_breakout bullish +1.15% +1.49% 3,951 0.002
hh_hl_streak bullish + volume_breakout bullish +1.50% +1.32% 710 0.018
volume_breakout bullish + weekly_change bullish +1.10% +0.93% 2,818 0.006

6 of this universe's 23 surviving pairs involve this signal · α vs ^HSI.

China A-shares — 24 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
volume_breakout bullish + weekly_change bearish +7.63% +15.53% 1,349 0.002
volume_breakout bearish + weekly_change bearish +3.53% +9.30% 5,524 0.002
stochastics bullish + volume_breakout bearish +3.81% +7.21% 954 0.002
bollinger bullish + volume_breakout bullish +3.08% +5.99% 2,943 0.002
new_20d_low bearish + volume_breakout bearish +1.32% +3.60% 9,979 0.002
stochastics bullish + volume_breakout bullish +2.02% +3.56% 3,345 0.002
rsi bullish + volume_breakout bullish +1.45% +3.09% 2,122 0.002
hh_hl_streak bearish + volume_breakout bearish +1.13% +3.03% 1,745 0.002
volume_breakout bullish + williams_r bullish +0.95% +2.27% 8,927 0.002
hh_hl_streak bullish + volume_breakout bullish +0.57% +1.76% 17,167 0.002
stochastics bearish + volume_breakout bullish +0.51% +1.67% 8,439 0.002
bearish_trend_breakout bullish + volume_breakout bullish +0.44% +1.35% 18,172 0.002
rsi bearish + volume_breakout bearish -0.53% +0.55% 11,970 0.002
volume_breakout bullish + weekly_change bullish -0.45% +0.52% 61,873 0.002
new_20d_high bullish + volume_breakout bullish -0.28% +0.34% 84,426 0.002
volume_breakout bullish + vwap_cross bullish -0.32% +0.25% 23,932 0.004
volume_breakout bearish + williams_r bearish -0.72% +0.15% 20,640 0.164
volume_breakout bearish + vwap_cross bearish -0.62% +0.06% 7,464 0.625
bollinger bearish + volume_breakout bearish -0.87% +0.05% 18,879 0.593
volume_breakout bearish + weekly_change bullish -1.12% -0.13% 15,550 0.331
cci bearish + volume_breakout bearish -0.90% -0.26% 5,895 0.140
double_top_breakout bullish + volume_breakout bullish -1.10% -0.48% 5,648 0.022
cci bearish + volume_breakout bullish -2.10% -0.58% 330 0.475
new_20d_high bullish + volume_breakout bearish -2.14% -1.85% 1,515 0.002

24 of this universe's 138 surviving pairs involve this signal · α vs 83188.HK.

China A-share survivor α runs large but skews toward small-caps, where trading costs and thin liquidity claim a large share of any measured edge — screening context, not a capturable spread.

What would likely rescue this signal

This block calls out the data or conditions that could turn a technically weak signal into a usable one in a composite screen. Based on signal mechanics and the observed failure patterns above; individual combinations are not yet backtested.

  • Combine with price-level breakouts — Volume-confirmed price breakouts are the textbook institutional-accumulation signature. Pairing this signal with New 20d High or New 52w High in the same report filters for volume spikes attached to a real technical event rather than rebalance or expiry noise. This is the most natural rescue path and requires no new data.
  • Multi-day volume pattern — The signal is currently a single-day event. A sustained multi-day volume pattern (several consecutive sessions well above the rolling average) would reduce one-off mechanical spikes — rebalances and expiries rarely persist for a week — and isolate genuine shifts in participation. A parameter-design opportunity rather than a new data source.

See also Why technical-only signals don't survive on their own for the broader argument.

5 · Before you act — a 5-point checklist

  1. Normal trading day? Rule out earnings (within ±3 days), ex-dividend, or known corporate-action dates — the signal is almost certainly reading noise, not momentum, in those windows.
  2. Where is price vs its own 50 / 200 DMA? A trend signal is only as credible as the underlying trend it claims to confirm. Check the 200DMA orientation before acting.
  3. What's the sector breadth doing? An isolated signal in a broadly down-trending sector is a lower-confidence setup than one firing with the rest of its peer group.
  4. Is ADV20 enough for your size? If the trigger is on a $500M name and you want to move $1M notional, you're the tape. Consider adv20d ≥ 5% of your intended position.
  5. What invalidates you? Define a price level (for longs: a close below the trigger-day low; for shorts: close above the trigger-day high) and honor it. The backtest alpha is an average; any one trade can be at either tail.

Execution notes

This signal earns its keep as a confirmation layer, not a standalone screen: layered onto a structural price trigger (New 20d High, New 52w High, or a pattern breakout), the volume spike distinguishes a participated move from a drift through a level. Consult the at-a-glance table and the permutation-null line above for whether either direction stands apart from random-date firing in the current global run — those values refresh with each backtest and override anything written here. Standalone use should assume high trigger frequency and low specificity; if traded, the convention is entry at the next session's open. Historical tendency, not a recommendation.

See a live screen of this signal

Curated Daily Reports that screen for this signal, refreshed at the open, midday and close — free to view, no account needed: