Trend new_high_low

20-Day New High / New Low

Detects when price makes a new rolling high or low. Bullish: today's high = highest high over N days AND close >= open. Bearish: today's low = lowest low over N days AND close <= open. The candle-direction filter removes false signals from intraday wicks.

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 Lookback period (days) 20 5–252

Historical context

7,744,906 triggers on 24,073 tickers, 1988-03-14 → 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 -0.06% +0.03%
20-day +0.13% +0.08%
60-day +0.41% +0.20%
1-year +3.08% +1.80%
Random-date null check (20-day): Bullish: inside null (p=0.507).
Bearish: worse than random (p=1.000).

Where does NEW_HIGH_LOW 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.

20-Day New High / New Low (new_high_low) — trigger count distribution by per-stock regime quadrant (trending/non-trending × high/low realized volatility) for bullish and bearish triggers, global universe — bullish half — measured on new_20d_high
Bullish half — measured on new_20d_high
20-Day New High / New Low (new_high_low) — trigger count distribution by per-stock regime quadrant (trending/non-trending × high/low realized volatility) for bullish and bearish triggers, global universe — bearish half — measured on new_20d_low
Bearish half — measured on new_20d_low

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.

20-Day New High / New Low (new_high_low) — mean 20-day alpha versus S&P 500 Equal Weight by per-stock regime quadrant, bullish and bearish triggers side by side — bullish half — measured on new_20d_high
Bullish half — measured on new_20d_high
20-Day New High / New Low (new_high_low) — mean 20-day alpha versus S&P 500 Equal Weight by per-stock regime quadrant, bullish and bearish triggers side by side — bearish half — measured on new_20d_low
Bearish half — measured on new_20d_low
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.

20-Day New High / New Low (new_high_low) — 20-day alpha split by historical sub-period (2015-2019, 2020-2022, 2023+) to check consistency across market regimes — bullish half — measured on new_20d_high
Bullish half — measured on new_20d_high
20-Day New High / New Low (new_high_low) — 20-day alpha split by historical sub-period (2015-2019, 2020-2022, 2023+) to check consistency across market regimes — bearish half — measured on new_20d_low
Bearish half — measured on new_20d_low

↑ Bullish triggers

Bench Metric 1d 5d 20d 60d 252d
spxew Stock % -0.00% +0.12% +0.79% +2.50% +12.85%
Bench % +0.04% +0.18% +0.69% +2.11% +9.88%
Alpha % -0.04% -0.06% +0.13% +0.41% +3.08%
Median alpha -0.09% -0.31% -0.81% -1.98% -6.20%
Hit rate (α>0) 47.2% 46.3% 45.5% 44.1% 41.9%
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 3,932,787 3,775,570 3,757,841 3,692,389 3,249,414
spx Stock % -0.00% +0.12% +0.79% +2.50% +12.85%
Bench % +0.02% +0.22% +0.89% +2.95% +13.63%
Alpha % -0.03% -0.09% -0.08% -0.44% -0.83%
Median alpha -0.08% -0.35% -1.09% -2.89% -10.42%
Hit rate (α>0) 47.2% 45.6% 44.1% 41.6% 37.4%
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 3,967,057 3,832,673 3,800,120 3,741,473 3,294,451
msci Stock % -0.00% +0.12% +0.79% +2.50% +12.85%
Bench % +0.05% +0.20% +0.78% +2.50% +11.13%
Alpha % -0.05% -0.08% +0.05% +0.02% +1.63%
Median alpha -0.11% -0.34% -0.96% -2.42% -7.98%
Hit rate (α>0) 46.5% 45.7% 44.7% 42.7% 40.2%
p (naive) <0.001 <0.001 <0.001 0.1252 <0.001
p (HAC) <0.001 <0.001 0.0002 0.6532 <0.001
N 3,940,348 3,802,594 3,789,418 3,713,092 3,273,623
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.
20-Day New High / New Low (new_high_low) — 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 +0.07% +0.07% [+0.07%, +0.08%] 0.239
1d spx +0.08% +0.08% [+0.08%, +0.08%] 0.995
1d msci +0.08% +0.09% [+0.08%, +0.09%] 1.000
5d spxew +0.28% +0.32% [+0.32%, +0.33%] 1.000
5d spx +0.30% +0.34% [+0.34%, +0.35%] 1.000
5d msci +0.30% +0.35% [+0.34%, +0.35%] 1.000
20d spxew +1.06% +1.06% [+1.05%, +1.07%] 0.507
20d spx +1.09% +1.10% [+1.09%, +1.11%] 0.851
20d msci +1.10% +1.11% [+1.10%, +1.12%] 0.881
60d spxew +2.00% +2.26% [+2.24%, +2.28%] 1.000
60d spx +1.91% +2.35% [+2.32%, +2.37%] 1.000
60d msci +1.94% +2.36% [+2.33%, +2.37%] 1.000
252d spxew +2.98% +3.87% [+3.83%, +3.92%] 1.000
252d spx +3.25% +4.31% [+4.27%, +4.36%] 1.000
252d msci +3.33% +4.24% [+4.20%, +4.30%] 1.000

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

Six recent bullish NEW_HIGH_LOW 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 NEW_HIGH_LOW looks like when it works)
20-Day New High / New Low (new_high_low) — 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 20-Day New High / New Low (new_high_low) — 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 20-Day New High / New Low (new_high_low) — 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 NEW_HIGH_LOW looks like when it fails)
20-Day New High / New Low (new_high_low) — weakest bullish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed 20-Day New High / New Low (new_high_low) — weakest bullish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed 20-Day New High / New Low (new_high_low) — 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 616,012 +0.51% +0.55% +0.04% 0.2442 +0.51% +0.79% -0.23% <0.001 +0.51% +0.67% -0.09% 0.0017
Trending + High vol Crisis selloff or parabolic rally 1,397,458 +0.95% +0.69% +0.30% <0.001 +0.95% +0.92% +0.06% 0.0186 +0.95% +0.80% +0.20% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 601,562 +0.48% +0.50% +0.01% 0.6576 +0.48% +0.74% -0.24% <0.001 +0.48% +0.61% -0.10% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 1,429,939 +0.94% +0.82% +0.14% <0.001 +0.94% +0.96% -0.01% 0.5698 +0.94% +0.87% +0.09% <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 1,357,451 -0.37% <0.001 -0.60% <0.001 -0.41% <0.001
2020-2022 2020-01-01 → 2023-01-01 1,153,081 +0.09% 0.0011 +0.30% <0.001 +0.42% <0.001
2023-2026 2023-01-01 → 2099-01-01 1,580,739 +0.62% <0.001 +0.12% <0.001 +0.20% <0.001

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

Bench Metric 1d 5d 20d 60d 252d
spxew Stock % -0.04% +0.20% +1.18% +3.23% +12.49%
Bench % +0.03% +0.16% +1.09% +2.99% +10.66%
Alpha % -0.07% +0.03% +0.08% +0.20% +1.80%
Median alpha -0.07% -0.16% -0.72% -1.94% -7.08%
Hit rate (α>0) 48.3% 48.3% 46.3% 44.5% 41.2%
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 3,516,452 3,391,570 3,370,262 3,288,889 3,008,497
spx Stock % -0.04% +0.20% +1.18% +3.23% +12.49%
Bench % +0.01% +0.22% +1.35% +3.55% +14.54%
Alpha % -0.05% -0.01% -0.13% -0.30% -2.06%
Median alpha -0.05% -0.20% -0.96% -2.53% -11.03%
Hit rate (α>0) 48.6% 47.8% 45.2% 43.1% 37.2%
p (naive) <0.001 0.0101 <0.001 <0.001 <0.001
p (HAC) <0.001 0.0563 <0.001 <0.001 <0.001
N 3,542,428 3,424,653 3,414,718 3,330,792 3,044,877
msci Stock % -0.04% +0.20% +1.18% +3.23% +12.49%
Bench % +0.03% +0.21% +1.19% +3.21% +12.23%
Alpha % -0.06% -0.00% -0.01% +0.09% -0.00%
Median alpha -0.07% -0.20% -0.84% -2.17% -8.87%
Hit rate (α>0) 48.1% 47.8% 45.7% 43.9% 39.4%
p (naive) <0.001 0.6018 0.0353 <0.001 0.9209
p (HAC) <0.001 0.6989 0.2819 0.0052 0.9835
N 3,529,517 3,410,352 3,384,231 3,311,081 3,026,706
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.
20-Day New High / New Low (new_high_low) — 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 +0.07% +0.08% [+0.08%, +0.09%] 0.005
1d spx +0.08% +0.09% [+0.09%, +0.09%] 0.005
1d msci +0.10% +0.09% [+0.09%, +0.10%] 0.766
5d spxew +0.45% +0.37% [+0.36%, +0.38%] 1.000
5d spx +0.45% +0.39% [+0.38%, +0.39%] 1.000
5d msci +0.45% +0.39% [+0.38%, +0.40%] 1.000
20d spxew +1.30% +1.19% [+1.18%, +1.21%] 1.000
20d spx +1.33% +1.22% [+1.21%, +1.24%] 1.000
20d msci +1.33% +1.24% [+1.22%, +1.25%] 1.000
60d spxew +2.78% +2.54% [+2.52%, +2.56%] 1.000
60d spx +3.02% +2.61% [+2.59%, +2.63%] 1.000
60d msci +2.99% +2.63% [+2.61%, +2.65%] 1.000
252d spxew +5.78% +4.90% [+4.86%, +4.95%] 1.000
252d spx +6.02% +5.25% [+5.21%, +5.30%] 1.000
252d msci +5.85% +5.20% [+5.17%, +5.25%] 1.000

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

Six recent bearish NEW_HIGH_LOW 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 NEW_HIGH_LOW looks like when it works)
20-Day New High / New Low (new_high_low) — 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 20-Day New High / New Low (new_high_low) — 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 20-Day New High / New Low (new_high_low) — 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 NEW_HIGH_LOW looks like when it fails)
20-Day New High / New Low (new_high_low) — weakest bearish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed 20-Day New High / New Low (new_high_low) — weakest bearish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed 20-Day New High / New Low (new_high_low) — 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 339,418 +0.01% +0.88% -0.80% <0.001 +0.01% +1.13% -1.07% <0.001 +0.01% +0.98% -0.91% <0.001
Trending + High vol Crisis selloff or parabolic rally 1,171,420 +2.13% +1.22% +0.88% <0.001 +2.13% +1.53% +0.65% <0.001 +2.13% +1.33% +0.79% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 485,147 +0.04% +0.88% -0.78% <0.001 +0.04% +1.14% -1.05% <0.001 +0.04% +1.01% -0.92% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 1,647,129 +1.09% +1.15% -0.04% 0.0284 +1.09% +1.34% -0.21% <0.001 +1.09% +1.22% -0.12% <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 1,094,023 -0.15% <0.001 -0.24% <0.001 -0.02% 0.2556
2020-2022 2020-01-01 → 2023-01-01 1,106,761 -0.14% <0.001 +0.06% 0.0114 +0.20% <0.001
2023-2026 2023-01-01 → 2099-01-01 1,441,394 +0.43% <0.001 -0.18% <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

Not a standalone entry trigger at 20 days. Bullish 20d alpha is +0.13% — inside the null : indistinguishable from random timing. Bearish 20d alpha is +0.08% — worse than random : firing on random dates would have done better. Fires are screening context inside a composite (section 4), not entries.

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 +0.30% / 20d on 1,397,458 historical triggers.
  • Best bearish setup: Trending + Low vol — alpha -0.80% / 20d on 339,418 historical triggers.
  • Best era for bullish: 2023-2026 — alpha +0.62% / 20d on 1,580,739 triggers.
  • Best era for bearish: 2015-2019 — alpha -0.15% / 20d on 1,094,023 triggers.

3 · When it fails — common false positives

  • Weakest bullish cell: Non-trending + Low vol — alpha +0.01% / 20d on 601,562 triggers.
  • Weakest bearish cell: Trending + High vol — alpha +0.88% / 20d on 1,171,420 triggers.
  • Worst era for bullish: 2015-2019 — alpha -0.37% / 20d on 1,357,451 triggers.
  • Worst era for bearish: 2023-2026 — alpha +0.43% / 20d on 1,441,394 triggers.

Signal-specific failure patterns

High trigger frequency dilutes the signal content
The largest sample in the suite (~3.7M bullish triggers). On the equal-weight benchmark the alpha is small and the random-date null check sits inside the null distribution — see the at-a-glance table. Each ticker fires ~180 times per decade, roughly once every two weeks on average. A signal that common is not identifying exceptional events; it is flagging that price rose above its 20-day trailing high, which happens routinely in any modestly trending stock.
Useful as a universe filter, weak as a standalone trigger
The natural use of new_20d_high is as a screen filter — stocks currently making 20-day highs is a reasonable universe shortcut. As an entry trigger on its own the alpha is too small to overcome transaction costs and slippage at any meaningful position size.
Bearish edge is small and direction-dependent on the benchmark
20-day new low bearish is marginal against equal-weight — see the at-a-glance table for current numbers. Against cap-weighted SPX the recent sub-periods showed clearer underperformance, but on the equal-weight benchmark the difference between the signal cohort and a random-date sample is small. Treat it as a watchlist tile rather than a standalone short trigger.
Strong period dispersion
Pre-COVID, COVID era, and post-2023 windows produce very different alpha for the bearish side. Which era helped and which hurt has flipped across runs — read the sub-period breakdown on this page rather than assuming the current regime resembles any earlier one.
Bounce dynamics grow with horizon
Beaten-down names mean-revert, so bounce dynamics increasingly dominate at 60-day-plus horizons. If you use the bearish side at all, keep the evaluation window short and check the short-horizon permutation row first. Optimal hold is short; longer holds give back the edge.

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.

Breakout-family redundancy

New 20-day high, new 52-week high, and fresh 52-week high are breakout signals at different lookbacks — all fire when price exceeds the maximum of the prior N bars (Edwards & Magee, Technical Analysis of Stock Trends, 11th ed. 2018; Kirkpatrick & Dahlquist, Technical Analysis, 3rd ed. 2015; Bulkowski, Encyclopedia of Chart Patterns, 3rd ed. 2021). Stacking two or more in the same direction within a single Daily Report produces correlated rather than independent evidence.

Breakdown-family redundancy

New 20-day low, new 52-week low, and fresh 52-week low are breakdown signals at different lookbacks — all fire when price falls below the minimum of the prior N bars (Edwards & Magee, Technical Analysis of Stock Trends, 11th ed. 2018; Kirkpatrick & Dahlquist, Technical Analysis, 3rd ed. 2015; Bulkowski, Encyclopedia of Chart Patterns, 3rd ed. 2021). Stacking two or more in the same direction within a single Daily Report produces correlated rather than independent evidence.

Measured pairings — Bonferroni survivors

Beyond the literature pairings above, these are the same-day co-fire combinations involving 20-Day New High / New Low 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 42 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.

Pairs carry the underlying split names: new_20d_high is this signal's bullish side, new_20d_low its bearish side.

US (NYSE / NASDAQ / AMEX)

Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
new_20d_low bearish + weekly_change bearish +0.61% +1.06% 25,567 0.002
macd bearish + new_20d_low bearish +0.55% +0.85% 9,573 0.002
bullish_trend_breakdown bearish + new_20d_low bearish +0.23% +0.62% 10,886 0.002
bollinger bullish + new_20d_low bearish +0.73% +0.46% 4,001 0.010
hh_hl_streak bearish + new_20d_low bearish +0.27% +0.20% 19,881 0.004
double_top_breakout bullish + new_20d_high bullish -0.56% -0.22% 4,680 0.164
fresh_52w_high bullish + new_20d_low bearish -3.37% — — —

7 of this universe's 18 surviving pairs involve this signal · α vs ^SPXEW.

Europe — 4 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
bullish_trend_breakdown bearish + new_20d_low bearish +0.74% +1.22% 3,197 0.002
new_20d_high bullish + volume_breakout bullish +0.59% +0.69% 5,813 0.002
hh_hl_streak bearish + new_20d_low bearish +0.54% +0.55% 5,405 0.002
macd bullish + new_20d_high bullish +0.37% +0.23% 4,112 0.110

4 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 bullish + new_20d_high bullish +0.94% +1.56% 1,255 0.002
new_20d_high bullish + volume_breakout bullish +1.15% +1.49% 3,951 0.002
hh_hl_streak bullish + new_20d_high bullish +0.85% +1.45% 2,429 0.002
bearish_trend_breakout bullish + new_20d_high bullish +1.04% +1.32% 2,925 0.002
new_20d_high bullish + weekly_change bullish +0.89% +1.05% 5,551 0.002
new_20d_low bearish + weekly_change bearish +1.09% +0.33% 2,979 0.200

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

China A-shares — 25 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
new_20d_low bearish + weekly_change bearish +3.22% +3.68% 50,447 0.002
new_20d_low bearish + volume_breakout bearish +1.32% +3.60% 9,979 0.002
failed_double_top bearish + new_20d_low bearish +2.36% +2.20% 1,860 0.002
bollinger bearish + new_20d_low bearish -2.26% +2.00% 147 0.032
new_20d_low bearish + stochastics bullish +1.37% +1.91% 16,120 0.002
cci bearish + new_20d_low bearish +0.96% +1.47% 881 0.002
bearish_trend_breakout bullish + new_20d_high bullish +0.70% +1.43% 38,486 0.002
ma_crossover bearish + new_20d_low bearish +1.19% +1.38% 1,372 0.002
new_20d_low bearish + vwap_cross bearish +0.91% +1.17% 3,909 0.002
new_20d_low bearish + rsi bullish +2.15% +1.08% 411 0.090
hh_hl_streak bullish + new_20d_high bullish +0.26% +0.78% 32,300 0.002
new_20d_high bullish + stochastics bearish +0.41% +0.78% 14,587 0.002
macd bearish + new_20d_low bearish +0.41% +0.50% 16,288 0.002
double_bottom_breakdown bearish + new_20d_low bearish +0.79% +0.46% 6,655 0.004
hh_hl_streak bearish + new_20d_low bearish +0.72% +0.45% 44,009 0.002
new_20d_high bullish + volume_breakout bullish -0.28% +0.34% 84,426 0.002
new_20d_high bullish + weekly_change bullish -0.56% +0.15% 83,483 0.010
bollinger bullish + new_20d_low bearish +0.58% +0.02% 7,647 0.836
new_20d_high bullish + vwap_cross bullish -0.75% -0.21% 12,388 0.078
macd bullish + new_20d_high bullish -0.61% -0.55% 18,940 0.002
double_top_breakout bullish + new_20d_high bullish -1.07% -0.73% 7,771 0.002
new_20d_low bearish + williams_r bullish -0.60% -1.54% 4,763 0.002
new_20d_high bullish + volume_breakout bearish -2.14% -1.85% 1,515 0.002
new_20d_high bullish + vwap_cross bearish -4.52% — — —
new_20d_low bearish + rsi bearish -3.37% — — —

25 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.

“—” in the test columns means the held-out 2023+ sample fell below the 20-observation minimum this run requires before it computes any statistic, so no out-of-sample figure exists for that pair — not that it never co-fired again. Those pairs rank last.

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.

  • Volume-filter to cut the trigger noise — Fresh 20d highs are too common. Requiring volume above 1.5-2x the 20d average would reduce triggers by 60-80% and concentrate on real accumulation events.
  • Combine with structural-breakout level — A 20d high that is also a 52w high or a multi-year resistance break is a structurally different event than a 20d high inside a sideways range. Compound filter should concentrate the alpha.
  • Time-limit the hold to 20-30 days max — Past 20d, alpha reverts. A strict 20d time stop preserves the signal edge.
  • Pair with trend filter — New 20d low in an uptrend is noise; in a downtrend it is continuation. 50DMA filter separates the two populations cleanly.

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

Use primarily as a screen filter, not as a primary trigger. Entry open T+1 if used. Pair with volume + market-cap filters to cut the trigger rate substantially before evaluating any per-name decision. New lows side: Marginal short-side tile. Entry open T+1, exit within 20 trading days. Most useful as a universe filter for short candidates, paired with structural filters (50DMA, sector trend) for directional conviction.