Trend new_52w_high_low

52-Week New High / New Low

Detects when price makes a new 52-week (252-day) high or low. Standard institutional definition: today's high ≥ prior 252-day max (bullish), or today's low ≤ prior 252-day min (bearish). Used for market breadth and regime analysis (Hindenburg Omen, etc.).

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) 252 126–504

Historical context

2,273,612 triggers on 21,080 tickers, 1989-02-08 → 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 +0.04% +0.09%
20-day +0.52% +0.39%
60-day +1.60% +0.79%
1-year +7.25% +3.06%
Random-date null check (20-day): Bullish: beats random (p=0.005).
Bearish: —.

Where does NEW_52W_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.

52-Week New High / New Low (new_52w_high_low) — 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.

52-Week New High / New Low (new_52w_high_low) — 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. Long-history signal: requires 260 trading days of prior data per ticker. The earliest era may show fewer triggers as a result.

52-Week New High / New Low (new_52w_high_low) — 20-day alpha split by historical sub-period (2015-2019, 2020-2022, 2023+) to check consistency across market regimes

Longer-horizon views

This signal carries a long lookback window (260 trading days of prior history required per ticker), suggesting it's designed to catch moves that play out over months, not days. The charts below repeat the quadrant and sub-period analyses at the 60-day and 1-year (252-day) horizons so you can see how the signal's relationship with the benchmark evolves with holding period.

60-day alpha by stock regime

52-Week New High / New Low (new_52w_high_low) — mean 60-day alpha versus S&P 500 Equal Weight by per-stock regime quadrant

60-day alpha by era

52-Week New High / New Low (new_52w_high_low) — 60-day alpha split by historical sub-period

1-year alpha by stock regime

52-Week New High / New Low (new_52w_high_low) — mean 1-year (252 trading day) alpha versus S&P 500 Equal Weight by per-stock regime quadrant

1-year alpha by era

52-Week New High / New Low (new_52w_high_low) — 1-year alpha split by historical sub-period

1-year observed alpha vs random-date null

52-Week New High / New Low (new_52w_high_low) — bullish 1-year observed alpha versus the random-date permutation null distribution

↑ Bullish triggers

Bench Metric 1d 5d 20d 60d 252d
spx Stock % -0.03% +0.20% +1.06% +3.56% +16.03%
Bench % +0.01% +0.17% +0.85% +2.81% +12.27%
Alpha % -0.04% +0.03% +0.27% +0.74% +3.54%
Median alpha -0.08% -0.28% -0.92% -2.14% -7.73%
Hit rate (α>0) 47.4% 46.7% 45.1% 43.8% 40.0%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 0.0013 <0.001 <0.001 <0.001
N 1,301,253 1,258,669 1,248,137 1,210,590 1,032,379
msci Stock % -0.03% +0.20% +1.06% +3.56% +16.03%
Bench % +0.03% +0.16% +0.69% +2.29% +9.35%
Alpha % -0.07% +0.04% +0.44% +1.27% +6.42%
Median alpha -0.11% -0.27% -0.73% -1.57% -4.73%
Hit rate (α>0) 46.7% 46.8% 46.0% 45.3% 43.8%
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 1,292,012 1,249,741 1,244,155 1,195,538 1,026,576
spxew Stock % -0.03% +0.20% +1.06% +3.56% +16.03%
Bench % +0.03% +0.16% +0.62% +1.96% +8.68%
Alpha % -0.06% +0.04% +0.52% +1.60% +7.25%
Median alpha -0.09% -0.23% -0.59% -1.15% -3.89%
Hit rate (α>0) 47.2% 47.3% 46.8% 46.6% 44.7%
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 1,290,043 1,242,906 1,237,259 1,192,246 1,019,669
Distribution of all 20d alpha outcomes for this direction. Median and winsorized mean shown.
52-Week New High / New Low (new_52w_high_low) — 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.
52-Week New High / New Low (new_52w_high_low) — 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 +0.06% +0.07% [+0.07%, +0.08%] 1.000
1d msci +0.07% +0.08% [+0.07%, +0.08%] 1.000
1d spxew +0.06% +0.06% [+0.06%, +0.07%] 1.000
5d spx +0.35% +0.32% [+0.31%, +0.33%] 0.005
5d msci +0.35% +0.33% [+0.32%, +0.34%] 0.005
5d spxew +0.32% +0.30% [+0.29%, +0.31%] 0.005
20d spx +1.12% +1.05% [+1.03%, +1.07%] 0.005
20d msci +1.16% +1.06% [+1.04%, +1.08%] 0.005
20d spxew +1.12% +1.01% [+0.98%, +1.03%] 0.005
60d spx +2.02% +2.32% [+2.29%, +2.36%] 1.000
60d msci +2.09% +2.32% [+2.28%, +2.35%] 1.000
60d spxew +2.11% +2.23% [+2.19%, +2.27%] 1.000
252d spx +1.88% +3.91% [+3.79%, +4.01%] 1.000
252d msci +2.28% +3.79% [+3.68%, +3.90%] 1.000
252d spxew +1.41% +3.43% [+3.31%, +3.53%] 1.000

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

Six recent bullish NEW_52W_HIGH_LOW 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 NEW_52W_HIGH_LOW looks like when it works)
52-Week New High / New Low (new_52w_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 52-Week New High / New Low (new_52w_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 52-Week New High / New Low (new_52w_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_52W_HIGH_LOW looks like when it fails)
52-Week New High / New Low (new_52w_high_low) — weakest bullish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed 52-Week New High / New Low (new_52w_high_low) — weakest bullish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed 52-Week New High / New Low (new_52w_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 % (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 236,307 +0.67% +0.64% +0.09% 0.0249 +0.67% +0.46% +0.28% <0.001 +0.67% +0.29% +0.45% <0.001
Trending + High vol Crisis selloff or parabolic rally 727,791 +1.32% +0.89% +0.49% <0.001 +1.32% +0.74% +0.64% <0.001 +1.32% +0.67% +0.73% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 111,905 +0.54% +0.70% -0.13% 0.0006 +0.54% +0.52% +0.07% 0.0608 +0.54% +0.43% +0.18% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 238,443 +1.17% +0.95% +0.26% <0.001 +1.17% +0.80% +0.40% <0.001 +1.17% +0.82% +0.40% <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 → 2020-01-01 335,648 -0.40% <0.001 -0.19% <0.001 -0.09% 0.0226
2020-2022 2020-01-01 → 2023-01-01 404,735 +0.49% <0.001 +0.70% <0.001 +0.36% <0.001
2023-2026 2023-01-01 → 2099-01-01 601,192 +0.53% <0.001 +0.63% <0.001 +1.00% <0.001

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

Bench Metric 1d 5d 20d 60d 252d
spx Stock % -0.10% +0.11% +1.87% +4.50% +15.77%
Bench % -0.02% +0.08% +1.69% +4.10% +16.49%
Alpha % -0.09% +0.01% +0.18% +0.51% -0.46%
Median alpha -0.08% -0.26% -0.85% -1.96% -11.15%
Hit rate (α>0) 48.1% 47.6% 46.2% 45.2% 37.7%
p (naive) <0.001 0.4604 <0.001 <0.001 <0.001
p (HAC) <0.001 0.6043 <0.001 <0.001 0.1446
N 905,478 875,963 870,891 854,579 816,508
msci Stock % -0.10% +0.11% +1.87% +4.50% +15.77%
Bench % -0.00% +0.07% +1.50% +3.79% +14.31%
Alpha % -0.09% +0.01% +0.32% +0.89% +1.39%
Median alpha -0.10% -0.26% -0.70% -1.58% -9.02%
Hit rate (α>0) 47.7% 47.5% 46.8% 46.0% 39.6%
p (naive) <0.001 0.2456 <0.001 <0.001 <0.001
p (HAC) <0.001 0.4148 <0.001 <0.001 <0.001
N 901,092 870,367 862,786 848,505 810,057
spxew Stock % -0.10% +0.11% +1.87% +4.50% +15.77%
Bench % -0.02% -0.04% +1.37% +3.80% +12.87%
Alpha % -0.09% +0.09% +0.39% +0.79% +3.06%
Median alpha -0.10% -0.20% -0.62% -1.62% -7.24%
Hit rate (α>0) 47.8% 48.2% 47.2% 45.9% 41.3%
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 897,334 865,852 855,360 840,537 803,794
Distribution of all 20d alpha outcomes for this direction. Median and winsorized mean shown.
52-Week New High / New Low (new_52w_high_low) — 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.
52-Week New High / New Low (new_52w_high_low) — 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

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

Six recent bearish NEW_52W_HIGH_LOW 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 NEW_52W_HIGH_LOW looks like when it works)
52-Week New High / New Low (new_52w_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 52-Week New High / New Low (new_52w_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 52-Week New High / New Low (new_52w_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_52W_HIGH_LOW looks like when it fails)
52-Week New High / New Low (new_52w_high_low) — weakest bearish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed 52-Week New High / New Low (new_52w_high_low) — weakest bearish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed 52-Week New High / New Low (new_52w_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 % (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 124,333 -0.48% +1.16% -1.58% <0.001 -0.48% +1.03% -1.45% <0.001 -0.48% +0.91% -1.35% <0.001
Trending + High vol Crisis selloff or parabolic rally 498,175 +3.14% +2.07% +1.04% <0.001 +3.14% +1.87% +1.21% <0.001 +3.14% +1.75% +1.27% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 56,541 -0.90% +1.05% -1.91% <0.001 -0.90% +0.93% -1.78% <0.001 -0.90% +0.81% -1.67% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 248,993 +1.14% +1.33% -0.18% 0.0006 +1.14% +1.19% -0.08% 0.1135 +1.14% +1.05% +0.00% 0.9760
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 → 2020-01-01 285,844 +0.10% 0.0412 +0.33% <0.001 +0.09% 0.0721
2020-2022 2020-01-01 → 2023-01-01 312,377 +0.12% 0.0390 +0.37% <0.001 +0.27% <0.001
2023-2026 2023-01-01 → 2099-01-01 331,155 +0.33% <0.001 +0.27% <0.001 +0.78% <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 52-Week New High / New Low bullish as a long-side screening tile. Observed 20d alpha vs S&P 500 Equal Weight is +0.52%, which beats random (permutation test, 200 iterations). The bearish side does not add edge (unknown) — treat it as noise, not a short trigger.

2 · When it works — the setups that drive it

  • Best bullish setup: Trending + High vol — alpha +0.73% / 20d on 727,791 historical triggers.
  • Best bearish setup: Trending + High vol — alpha +1.27% / 20d on 498,175 historical triggers.
  • Best era for bullish: 2023-2026 — alpha +1.00% / 20d.
  • Best era for bearish: 2023-2026 — alpha +0.78% / 20d.

3 · When it fails — common false positives

  • Weakest bullish cell: Non-trending + Low vol — alpha +0.18% / 20d on 111,905 triggers.
  • Weakest bearish cell: Non-trending + Low vol — alpha -1.67% / 20d on 56,541 triggers.
  • Worst era for bullish: 2015-2019 — alpha -0.09% / 20d.
  • Worst era for bearish: 2015-2019 — alpha +0.09% / 20d.

Signal-specific failure patterns

52-week new high fails the permutation null broadly
Bullish 52w new high: α=−0.36 at 20d (p(HAC)<1e-14, p_perm=1.000), deepening to −0.62 at 60d. Random-date firing in the same universe would have produced higher alpha — the signal actively selects names that UNDER-perform the broader market once they make new highs. The 'momentum buys winners' intuition fails at this sample size (235k triggers).
evidence: bullish 20d α=−0.36 p_perm=1.000; 60d α=−0.62 p_perm=1.000
The 2015-2019 era was worst (−0.49), confirming this isn't a post-QE anomaly
Unlike oscillators that broke in 2020+, new 52w high bullish was already producing negative alpha in 2015-2019 (α=−0.49). The failure is structural to the signal's design: by the time a stock prints a 52w new high, the move is mature. Forward returns revert to broad market or below.
evidence: bullish 20d by period: 2015-19 −0.49, 2020-22 −0.25, 2023-26 −0.34
Related signals (fresh_52w_high) show the same pattern
fresh_52w_high — which adds a 20-day cooldown to avoid consecutive-day triggers — produces α=−0.24 at 20d, −0.66 at 60d. The cooldown filter reduces triggers ~5x but the alpha stays negative. The issue is not trigger-frequency, it's the signal's core thesis.
Bearish 52w new low has real but fragile 20d edge
α=−0.20 at 20d (p(HAC)=0.03, p_perm=0.005). The signal does pick underperformers over the next month. But 60d α=+1.10 (p_hac<1e-5 but p_perm=0.93 — signal fails in the correct direction). At 60d stocks that made fresh 52w lows reverse hard — likely base-building and initial recovery.
evidence: bearish 20d α=−0.20 p_perm=0.005; bearish 60d α=+1.10 p_perm=0.93 (wrong direction)
Massive period dispersion — worked 2020-2026, inverted 2015-2019
Sub-period bearish 20d: 2015-2019 α=+0.95 (signal inverted — new lows bounced strongly), 2020-2022 α=−0.48, 2023-2026 α=−0.55. Pre-2020 the signal was a bounce indicator; post-2020 it's a weakness indicator. The regime change is dramatic — treat the pre-2020 backtest as irrelevant to current usage.
evidence: bearish 20d by period: +0.95, −0.48, −0.55
The 60d reversion is the 'dead-cat bounce' phenomenon
Stocks making fresh 52w lows often become squeeze candidates when institutional short interest is high. Forced-cover rallies during the 2-3 month window after the low are classic; this is what the +1.10% 60d alpha is picking up. Don't hold short positions past 30d.
evidence: 60d α=+1.10 (wrong direction for bearish) — short squeeze dynamics

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.

Breakout-family redundancy

New 52-week high, new 20-day 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 52-week low, new 20-day 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.

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.

  • Require consolidation structure — Breakouts from tight ranges (last 20d trading range < 5%) historically outperform straight-line continuation breakouts. Measurable from the same OHLC data; testable without new sources.
  • Add fundamental filter — A 52w new high with trailing EPS growth > 20% YoY is a structurally different trade than one without. Requires commercial fundamentals data. The plausible-rescue path for most trend signals on US large-caps.
  • Sector-relative filter — New high that's ALSO a sector-relative high (stock outperforming its sector ETF over trailing 20d) is a cleaner leadership signal than absolute new high. Derivable from existing data.
  • Short-horizon only — Exit at 20d regardless of price. Past 20d, short-squeeze risk dominates the alpha.
  • Regime-gate on breadth — Bearish 52w new low worked in 2020+ narrow-breadth market; may reverse in a broad-breadth market. Conditioning on 'market breadth < 55%' would make the signal regime-adaptive. Testable.
  • Skip low-mcap names — Microcap 52w lows are mostly liquidity-driven not fundamental. Require mcap > $500M (or use LIQ variant of the universe) to filter out noise.

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

The signal's best use is as a UNIVERSE FILTER for a broader screen, not a standalone trigger. Use it to identify the 'leadership' subset, then apply a secondary filter (fundamentals, sector breadth, volume). Entry open T+1. As a pure entry trigger on US large-caps, expect slow relative losses vs passive index. New lows side: Tradable ONLY at short horizons (20d). 60d holds get caught in the recovery. Strict time stop at 20-30 days. Entry open T+1. Recent (2020+) sub-period is more relevant than full-history; skip the 2015-2019 inversion as regime-irrelevant. Note: the signal's edge has emerged in the post-concentration-rally era — it may fade if market breadth normalizes.