Trend volume_breakout

Volume breakout

Detects unusual volume spikes exceeding N× the rolling average. Bullish: volume spike with close > open (buying pressure). Bearish: volume spike with close < open (selling pressure).

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: US large-cap (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, US-only

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%

Sign flip across horizons. Bullish triggers go from -0.11% (5d) to +5.26% (1y) — short-term fade but longer holding recovers and wins.

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 , US-only 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 (green) = 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, 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
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
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
Distribution of all 20d alpha outcomes for this direction. Median and winsorized mean shown.
Volume breakout (volume_breakout) — bullish 20-day alpha histogram showing distribution of per-trigger returns
Observed 20d alpha (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 a tail, the signal is doing real work in that direction.
Volume breakout (volume_breakout) — bullish 20-day observed alpha versus random-date permutation null (200 iterations)
Permutation null detail — all horizons × both benchmarks
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), so the null distribution is centered on ~0 and the comparison tests signal effect alone — not the universe-selection lift that all surviving large-caps share. pperm = one-sided fraction of null iters with mean in the "signal was right" tail (right for bullish, left for bearish).
Horizon Bench Observed lift Null mean Null 95% CI pperm
1d spx +0.09% +0.10% [+0.10%, +0.11%] 1.000
1d msci +0.10% +0.11% [+0.10%, +0.11%] 1.000
1d spxew +0.09% +0.10% [+0.09%, +0.10%] 0.955
5d spx +0.38% +0.44% [+0.43%, +0.45%] 1.000
5d msci +0.39% +0.45% [+0.44%, +0.45%] 1.000
5d spxew +0.37% +0.43% [+0.42%, +0.44%] 1.000
20d spx +1.51% +1.39% [+1.37%, +1.40%] 0.005
20d msci +1.52% +1.40% [+1.38%, +1.42%] 0.005
20d spxew +1.48% +1.36% [+1.34%, +1.38%] 0.005
60d spx +2.87% +2.93% [+2.91%, +2.97%] 1.000
60d msci +2.90% +2.95% [+2.93%, +2.99%] 1.000
60d spxew +2.91% +2.88% [+2.85%, +2.91%] 0.020
252d spx +5.85% +5.42% [+5.33%, +5.50%] 0.005
252d msci +5.86% +5.34% [+5.25%, +5.42%] 0.005
252d spxew +5.54% +5.05% [+4.96%, +5.13%] 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. Catalyst-driven outliers (|α| > 25%) excluded so what's left is the signal's own typical good and bad days, not earnings shocks.

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 % (spx) Bench % (spx) Alpha % (spx) p (HAC) Stock % (msci) Bench % (msci) Alpha % (msci) p (HAC) Stock % (spxew) Bench % (spxew) Alpha % (spxew) p (HAC)
Trending + Low vol Clean directional grind, low whipsaw 113,550 +0.88% +0.78% +0.12% 0.0003 +0.88% +0.63% +0.28% <0.001 +0.88% +0.50% +0.42% <0.001
Trending + High vol Crisis selloff or parabolic rally 739,669 +1.15% +1.03% +0.13% <0.001 +1.15% +0.88% +0.27% <0.001 +1.15% +0.82% +0.35% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 177,233 +0.75% +0.80% -0.04% 0.0649 +0.75% +0.67% +0.10% <0.001 +0.75% +0.57% +0.20% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 828,750 +1.10% +1.04% +0.09% 0.0001 +1.10% +0.94% +0.19% <0.001 +1.10% +0.89% +0.25% <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 % (spx) p (HAC) Alpha % (msci) p (HAC) Alpha % (spxew) p (HAC)
2015-2019 2015-01-01 → 2020-01-01 580,282 -0.47% <0.001 -0.27% <0.001 -0.27% <0.001
2020-2022 2020-01-01 → 2023-01-01 545,904 +0.51% <0.001 +0.64% <0.001 +0.31% <0.001
2023-2026 2023-01-01 → 2099-01-01 732,448 +0.22% <0.001 +0.28% <0.001 +0.73% <0.001

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

Bench Metric 1d 5d 20d 60d 252d
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
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
Distribution of all 20d alpha outcomes for this direction. Median and winsorized mean shown.
Volume breakout (volume_breakout) — bearish 20-day alpha histogram showing distribution of per-trigger returns
Observed 20d alpha (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 a tail, the signal is doing real work in that direction.
Volume breakout (volume_breakout) — bearish 20-day observed alpha versus random-date permutation null (200 iterations)
Permutation null detail — all horizons × both benchmarks
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), so the null distribution is centered on ~0 and the comparison tests signal effect alone — not the universe-selection lift that all surviving large-caps share. pperm = one-sided fraction of null iters with mean in the "signal was right" tail (right for bullish, left for bearish).
Horizon Bench Observed lift Null mean Null 95% CI pperm
1d spx +0.12% +0.09% [+0.08%, +0.09%] 1.000
1d msci +0.14% +0.09% [+0.09%, +0.10%] 1.000
1d spxew +0.12% +0.08% [+0.07%, +0.08%] 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
5d spxew +0.45% +0.36% [+0.35%, +0.37%] 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
20d spxew +1.35% +1.15% [+1.13%, +1.18%] 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
60d spxew +2.75% +2.45% [+2.42%, +2.49%] 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
252d spxew +5.93% +4.76% [+4.70%, +4.84%] 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. Catalyst-driven outliers (|α| > 25%) excluded so what's left is the signal's own typical good and bad days, not earnings shocks.

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 % (spx) Bench % (spx) Alpha % (spx) p (HAC) Stock % (msci) Bench % (msci) Alpha % (msci) p (HAC) Stock % (spxew) Bench % (spxew) Alpha % (spxew) p (HAC)
Trending + Low vol Clean directional grind, low whipsaw 95,421 +0.26% +0.89% -0.64% <0.001 +0.26% +0.71% -0.46% <0.001 +0.26% +0.57% -0.33% <0.001
Trending + High vol Crisis selloff or parabolic rally 462,507 +1.61% +1.26% +0.36% <0.001 +1.61% +1.07% +0.50% <0.001 +1.61% +0.94% +0.64% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 142,579 +0.40% +0.89% -0.47% <0.001 +0.40% +0.75% -0.32% <0.001 +0.40% +0.67% -0.22% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 507,619 +1.06% +1.16% -0.07% 0.0016 +1.06% +1.03% +0.02% 0.3513 +1.06% +0.92% +0.13% <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 % (spx) p (HAC) Alpha % (msci) p (HAC) Alpha % (spxew) p (HAC)
2015-2019 2015-01-01 → 2020-01-01 382,681 -0.38% <0.001 -0.15% <0.001 -0.24% <0.001
2020-2022 2020-01-01 → 2023-01-01 352,450 +0.20% <0.001 +0.34% <0.001 +0.15% <0.001
2023-2026 2023-01-01 → 2099-01-01 472,499 +0.15% <0.001 +0.15% <0.001 +0.69% <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: fraction of 200 random-date null iterations with mean ≥ observed. 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 zero edge even if the t-test says "significant."

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. Observed 20d alpha vs S&P 500 Equal Weight is +0.08%, which beats random (permutation test, 200 iterations). The bearish side does not add edge (worse than random ) — treat it as noise, not a short trigger.

2 · When it works — the setups that drive it

  • Best bullish setup: Trending + High vol — alpha +0.13% / 20d on 739,669 historical triggers.
  • Best bearish setup: Trending + High vol — alpha +0.36% / 20d on 462,507 historical triggers.
  • Best era for bullish: 2020-2022 — alpha +0.51% / 20d.
  • Best era for bearish: 2020-2022 — alpha +0.20% / 20d.

3 · When it fails — common false positives

  • Weakest bullish cell: Non-trending + Low vol — alpha -0.04% / 20d on 177,233 triggers.
  • Weakest bearish cell: Trending + Low vol — alpha -0.64% / 20d on 95,421 triggers.
  • Worst era for bullish: 2015-2019 — alpha -0.47% / 20d.
  • Worst era for bearish: 2015-2019 — alpha -0.38% / 20d.

Signal-specific failure patterns

Bullish alpha is nearly zero and fails permutation null
Volume breakout bullish (day with volume > 2× 20d average, up-close) shows α=+0.10 at 20d vs SPX (p(HAC)=0.06, p_perm=1.000). At 60d α=+0.16 (non-significant). The point-estimate alpha is slightly positive but the permutation null says random-date firing would have done better. The signal does not provide information.
evidence: bullish vs SPX: 20d α=+0.10 p_perm=1.000; 60d α=+0.16 p_perm=1.000
Bearish is subtle — point-estimate small but p_perm significant
Bearish α_spx=−0.05 at 20d (p(HAC)=0.26 non-sig) but p_perm=0.005 significant. The small point-estimate combined with a significant left-tail p_perm means: observed is worse than random-date firing but by a tiny amount. Against SPXEW the point-estimate is +0.20 — signal wrong direction. Bearish volume breakouts on their own do not offer tradable alpha under Convention A.
evidence: bearish vs SPX: 20d α=−0.05 p_perm=0.005 (significant but tiny); vs SPXEW: α=+0.20 (wrong direction)
Sub-period shift: bullish flipped positive in 2023-2026
Bullish α: 2015-2019 −0.18, 2020-2022 +0.05, 2023-2026 +0.40. The signal has gotten BETTER recently. May be picking up momentum-driven AI-era breakouts that the 2015-2019 value-era market didn't reward. Interesting but only a 2-period trend — could reverse.
evidence: bullish 20d vs SPX: 2015-19 −0.18, 2020-22 +0.05, 2023-26 +0.40

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. A multi-signal convergence backtest is planned but not yet run.

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.

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 breakouts are the textbook institutional accumulation signature. Pairing with new 20d or 52w highs would filter for real technical events rather than random volume spikes. This is the most natural rescue path.
  • Multi-day volume pattern — Signal is currently a single-day volume event. A 3-day sustained volume pattern (each day > 1.5× average) would reduce noise and might reveal cleaner alpha. Parameter tuning opportunity.

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

Neither direction has strongly tradable alpha on its own under Convention A. The 2023+ bullish sub-period is intriguing but one sub-period is not conclusive. Best use: as a confirmation filter layered onto a structural breakout trigger (new_20d_high, new_52w_high). Entry open T+1.