Trend hh_hl_streak

Highs/Lows streak

Detects sustained trend structure. Bullish: N consecutive days of higher highs AND higher lows. Bearish: N consecutive days of lower lows AND lower highs. Triggers on the day the streak is first confirmed.

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
streak Minimum consecutive days 3 2–10

Historical context

2,703,506 triggers on 23,607 tickers, 1995-10-13 → 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 -0.04% +0.00%
20-day +0.25% +0.04%
60-day +0.54% +0.27%
1-year +3.12% +1.89%
Random-date null check (20-day): Bullish: beats random (p=0.005).
Bearish: beats random (p=0.010).

Where does HH_HL_STREAK 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.

Highs/Lows streak (hh_hl_streak) — 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.

Highs/Lows streak (hh_hl_streak) — 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.

Highs/Lows streak (hh_hl_streak) — 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% +0.16% +1.03% +2.77% +13.26%
Bench % +0.04% +0.21% +0.82% +2.22% +10.20%
Alpha % -0.08% -0.04% +0.25% +0.54% +3.12%
Median alpha -0.11% -0.29% -0.66% -1.66% -5.37%
Hit rate (α>0) 47.3% 47.0% 46.8% 45.5% 43.3%
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 1,281,082 1,238,875 1,227,860 1,204,454 1,058,784
spx Stock % -0.03% +0.16% +1.03% +2.77% +13.26%
Bench % +0.02% +0.27% +1.03% +3.03% +13.97%
Alpha % -0.05% -0.10% +0.03% -0.27% -0.70%
Median alpha -0.10% -0.36% -0.90% -2.50% -9.35%
Hit rate (α>0) 47.3% 46.2% 45.6% 43.3% 38.9%
p (naive) <0.001 <0.001 0.0024 <0.001 <0.001
p (HAC) <0.001 <0.001 0.0120 <0.001 <0.001
N 1,291,960 1,257,419 1,243,373 1,220,910 1,075,767
msci Stock % -0.03% +0.16% +1.03% +2.77% +13.26%
Bench % +0.05% +0.25% +0.91% +2.60% +11.53%
Alpha % -0.08% -0.08% +0.17% +0.17% +1.62%
Median alpha -0.14% -0.35% -0.79% -2.07% -6.99%
Hit rate (α>0) 46.6% 46.4% 46.1% 44.4% 41.5%
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 1,284,988 1,248,979 1,239,570 1,211,624 1,064,550
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.
Highs/Lows streak (hh_hl_streak) — 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 +0.05% +0.07% [+0.06%, +0.07%] 1.000
1d spx +0.06% +0.08% [+0.07%, +0.08%] 1.000
1d msci +0.06% +0.08% [+0.08%, +0.09%] 1.000
5d spxew +0.30% +0.31% [+0.30%, +0.32%] 1.000
5d spx +0.28% +0.33% [+0.32%, +0.34%] 1.000
5d msci +0.30% +0.33% [+0.32%, +0.35%] 1.000
20d spxew +1.15% +1.04% [+1.02%, +1.06%] 0.005
20d spx +1.17% +1.07% [+1.05%, +1.09%] 0.005
20d msci +1.19% +1.08% [+1.07%, +1.10%] 0.005
60d spxew +2.20% +2.30% [+2.27%, +2.34%] 1.000
60d spx +2.14% +2.37% [+2.33%, +2.41%] 1.000
60d msci +2.16% +2.39% [+2.35%, +2.43%] 1.000
252d spxew +4.28% +4.49% [+4.41%, +4.56%] 1.000
252d spx +4.51% +4.83% [+4.75%, +4.89%] 1.000
252d msci +4.50% +4.77% [+4.70%, +4.84%] 1.000

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

Six recent bullish HH_HL_STREAK 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 HH_HL_STREAK looks like when it works)
Highs/Lows streak (hh_hl_streak) — 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 Highs/Lows streak (hh_hl_streak) — 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 Highs/Lows streak (hh_hl_streak) — 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 HH_HL_STREAK looks like when it fails)
Highs/Lows streak (hh_hl_streak) — weakest bullish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed Highs/Lows streak (hh_hl_streak) — weakest bullish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed Highs/Lows streak (hh_hl_streak) — 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 79,621 +0.46% +0.32% +0.16% <0.001 +0.46% +0.65% -0.19% <0.001 +0.46% +0.52% -0.05% 0.0584
Trending + High vol Crisis selloff or parabolic rally 481,979 +1.21% +0.90% +0.37% <0.001 +1.21% +1.12% +0.13% <0.001 +1.21% +0.96% +0.30% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 146,162 +0.58% +0.44% +0.13% <0.001 +0.58% +0.72% -0.17% <0.001 +0.58% +0.59% -0.03% 0.1020
Non-trending + High vol Classical "whipsaw zone" for momentum 622,493 +1.11% +0.92% +0.23% <0.001 +1.11% +1.08% +0.07% 0.0002 +1.11% +0.98% +0.17% <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 → 2020-01-01 368,182 -0.09% <0.001 -0.35% <0.001 -0.17% <0.001
2020-2022 2020-01-01 → 2023-01-01 412,942 +0.14% <0.001 +0.40% <0.001 +0.55% <0.001
2023-2026 2023-01-01 → 2099-01-01 548,959 +0.58% <0.001 +0.02% 0.3192 +0.12% <0.001

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

Bench Metric 1d 5d 20d 60d 252d
spxew Stock % -0.02% +0.19% +1.00% +3.02% +12.46%
Bench % +0.04% +0.19% +1.00% +2.76% +10.57%
Alpha % -0.06% +0.00% +0.04% +0.27% +1.89%
Median alpha -0.08% -0.20% -0.80% -1.93% -6.74%
Hit rate (α>0) 48.3% 48.1% 46.2% 44.9% 42.0%
p (naive) <0.001 0.6486 <0.001 <0.001 <0.001
p (HAC) <0.001 0.6512 0.0002 <0.001 <0.001
N 1,321,148 1,275,289 1,266,679 1,229,786 1,103,964
spx Stock % -0.02% +0.19% +1.00% +3.02% +12.46%
Bench % +0.00% +0.21% +1.21% +3.35% +14.26%
Alpha % -0.03% -0.02% -0.15% -0.33% -1.80%
Median alpha -0.05% -0.22% -1.04% -2.62% -10.51%
Hit rate (α>0) 48.7% 47.9% 45.1% 43.3% 38.2%
p (naive) <0.001 0.0001 <0.001 <0.001 <0.001
p (HAC) <0.001 0.0001 <0.001 <0.001 <0.001
N 1,332,659 1,287,936 1,281,654 1,245,019 1,117,686
msci Stock % -0.02% +0.19% +1.00% +3.02% +12.46%
Bench % +0.04% +0.22% +1.10% +3.02% +11.97%
Alpha % -0.06% -0.02% -0.06% +0.07% +0.24%
Median alpha -0.09% -0.23% -0.95% -2.24% -8.34%
Hit rate (α>0) 48.0% 47.7% 45.5% 44.1% 40.3%
p (naive) <0.001 0.0002 <0.001 0.0003 <0.001
p (HAC) <0.001 0.0002 <0.001 0.0273 0.1232
N 1,325,341 1,281,407 1,269,455 1,239,091 1,111,263
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.
Highs/Lows streak (hh_hl_streak) — 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 +0.08% +0.08% [+0.08%, +0.08%] 0.562
1d spx +0.10% +0.09% [+0.08%, +0.09%] 1.000
1d msci +0.09% +0.09% [+0.09%, +0.10%] 0.692
5d spxew +0.38% +0.36% [+0.35%, +0.37%] 1.000
5d spx +0.40% +0.38% [+0.37%, +0.39%] 1.000
5d msci +0.39% +0.38% [+0.37%, +0.40%] 0.950
20d spxew +1.15% +1.19% [+1.17%, +1.20%] 0.010
20d spx +1.18% +1.21% [+1.19%, +1.23%] 0.010
20d msci +1.16% +1.23% [+1.21%, +1.25%] 0.005
60d spxew +2.51% +2.57% [+2.54%, +2.61%] 0.005
60d spx +2.65% +2.63% [+2.60%, +2.66%] 0.821
60d msci +2.64% +2.66% [+2.63%, +2.70%] 0.129
252d spxew +4.91% +4.99% [+4.92%, +5.07%] 0.020
252d spx +5.26% +5.31% [+5.24%, +5.38%] 0.065
252d msci +5.05% +5.26% [+5.20%, +5.33%] 0.005

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

Six recent bearish HH_HL_STREAK 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 HH_HL_STREAK looks like when it works)
Highs/Lows streak (hh_hl_streak) — 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 Highs/Lows streak (hh_hl_streak) — 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 Highs/Lows streak (hh_hl_streak) — 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 HH_HL_STREAK looks like when it fails)
Highs/Lows streak (hh_hl_streak) — weakest bearish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed Highs/Lows streak (hh_hl_streak) — weakest bearish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed Highs/Lows streak (hh_hl_streak) — 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 65,023 +0.20% +0.73% -0.48% <0.001 +0.20% +1.05% -0.82% <0.001 +0.20% +0.91% -0.68% <0.001
Trending + High vol Crisis selloff or parabolic rally 491,358 +1.55% +0.99% +0.59% <0.001 +1.55% +1.28% +0.34% <0.001 +1.55% +1.11% +0.45% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 131,551 +0.16% +0.77% -0.57% <0.001 +0.16% +1.05% -0.86% <0.001 +0.16% +0.92% -0.72% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 685,298 +0.87% +1.07% -0.16% <0.001 +0.87% +1.22% -0.28% <0.001 +0.87% +1.13% -0.22% <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 → 2020-01-01 359,865 -0.34% <0.001 -0.50% <0.001 -0.32% <0.001
2020-2022 2020-01-01 → 2023-01-01 437,420 -0.06% 0.0079 +0.19% <0.001 +0.30% <0.001
2023-2026 2023-01-01 → 2099-01-01 575,778 +0.37% <0.001 -0.19% <0.001 -0.17% <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 Highs/Lows streak bullish as a long-side screening tile. Bullish 20d alpha is +0.25% and beats random (permutation test, 200 iterations). Bearish beats random on timing, but the raw 20d alpha is +0.04% — the flagged stocks still outperformed the benchmark, so it is not a short trigger on its own.

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 + High vol — alpha +0.37% / 20d on 481,979 historical triggers.
  • Best bearish setup: Non-trending + Low vol — alpha -0.57% / 20d on 131,551 historical triggers.
  • Best era for bullish: 2023-2026 — alpha +0.58% / 20d on 548,959 triggers.
  • Best era for bearish: 2015-2019 — alpha -0.34% / 20d on 359,865 triggers.

3 · When it fails — common false positives

  • Weakest bullish cell: Non-trending + Low vol — alpha +0.13% / 20d on 146,162 triggers.
  • Weakest bearish cell: Trending + High vol — alpha +0.59% / 20d on 491,358 triggers.
  • Worst era for bullish: 2015-2019 — alpha -0.09% / 20d on 368,182 triggers.
  • Worst era for bearish: 2023-2026 — alpha +0.37% / 20d on 575,778 triggers.

Signal-specific failure patterns

A common event, so any per-trigger edge is diluted
The trigger — N consecutive sessions (default 3) where both the high and the low exceed the prior day's, firing on the day the streak is first confirmed — is a frequent occurrence in any trending tape. That makes the trigger population large and ordinary: the signal tallies routine directional persistence at the per-stock level rather than isolating rare setups, so per-trigger magnitudes are structurally small in either direction. See the at-a-glance table and the permutation-null line above for what each side currently shows against the random-date null.
High-correlation regimes scramble short streaks
Three-day range expansions fire indiscriminately during broad-market rebounds and panics, when nearly everything makes higher highs and lows (or lower ones) together. In those regimes the streak stops carrying stock-specific information and inherits the market's path instead. Before weighting conviction on either direction, check the sub-period rows in the live tables for which eras actually carried the signal.

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.

Trend-structure family

Higher-high / higher-low streak encodes the classical Dow-theory definition of an uptrend — a price structure of successively higher swing highs and swing lows (Dow theory as presented in Murphy, Technical Analysis of the Financial Markets, 1999; Edwards & Magee, Technical Analysis of Stock Trends, 11th ed. 2018). This overlaps with HH/HL structure, moving-average crossover, and long-term trend-break signals, which infer the same trend state from different measurements.

Measured pairings — Bonferroni survivors

Beyond the literature pairings above, these are the same-day co-fire combinations involving Highs/Lows streak 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 — every row below happens to be positive on the full sample, but that is not what the test asked. 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.

US (NYSE / NASDAQ / AMEX)

Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
hh_hl_streak bearish + new_20d_low bearish +0.27% +0.20% 19,881 0.004

1 of this universe's 18 surviving pairs involves this signal · α vs ^SPXEW.

Europe — 1 surviving pair
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
hh_hl_streak bearish + new_20d_low bearish +0.54% +0.55% 5,405 0.002

1 of this universe's 20 surviving pairs involves this signal · α vs ^STOXX.

Hong Kong — 3 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
hh_hl_streak bullish + new_20d_high bullish +0.85% +1.45% 2,429 0.002
hh_hl_streak bullish + volume_breakout bullish +1.50% +1.32% 710 0.018
hh_hl_streak bullish + weekly_change bullish +1.47% +1.18% 1,411 0.004

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

China A-shares — 19 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
hh_hl_streak bullish + rsi bullish +5.43% +10.50% 210 0.002
cci bearish + hh_hl_streak bearish +2.53% +4.75% 4,169 0.002
hh_hl_streak bullish + stochastics bearish +2.33% +3.77% 3,278 0.002
hh_hl_streak bullish + ma_crossover bearish +2.54% +3.44% 244 0.002
hh_hl_streak bearish + volume_breakout bearish +1.13% +3.03% 1,745 0.002
hh_hl_streak bearish + weekly_change bearish +2.33% +2.87% 14,066 0.002
failed_double_top bearish + hh_hl_streak bearish +1.65% +2.18% 939 0.002
hh_hl_streak bullish + weekly_change bullish +0.92% +2.06% 22,970 0.002
failed_double_bottom bullish + hh_hl_streak bullish +1.85% +1.89% 644 0.002
hh_hl_streak bullish + volume_breakout bullish +0.57% +1.76% 17,167 0.002
hh_hl_streak bearish + rsi bullish +1.09% +1.36% 889 0.002
hh_hl_streak bullish + williams_r bullish +1.33% +1.27% 1,189 0.002
bearish_trend_breakout bullish + hh_hl_streak bullish +0.82% +1.20% 5,170 0.002
hh_hl_streak bearish + vwap_cross bearish +0.71% +1.10% 11,436 0.002
hh_hl_streak bullish + vwap_cross bullish +1.08% +1.04% 8,593 0.002
hh_hl_streak bullish + macd bullish +1.01% +0.83% 11,383 0.002
hh_hl_streak bullish + new_20d_high bullish +0.26% +0.78% 32,300 0.002
cci bullish + hh_hl_streak bullish +2.01% +0.68% 1,787 0.040
hh_hl_streak bearish + new_20d_low bearish +0.72% +0.45% 44,009 0.002

19 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.

  • Reverse-engineer the bullish thesis — If the bullish side fires late, a streak-RESET signal (first HH+HL after a downtrend break) might capture the bullish turn earlier. Separate signal design task.
  • Match the holding window to the horizon columns — Before fixing a holding period, compare the 20d and 60d columns in the live tables for the side traded. If alpha grows with horizon there, time stops above profit stops; if it decays, take the swing and exit. Do not hard-code either rule — the horizon profile is a property of the current tables, not of the signal's construction.

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

Entry open T+1. Read the per-direction verdict from the at-a-glance table and the permutation-null line above; even where a side clears the random-date null, the per-trigger effect is small and the trigger frequency high, so standalone trading means high turnover for thin margin. Most useful as a regime confirmation tile layered with other triggers.