Pattern double_bottom_breakdown

Double Bottom Breakdown

Bearish: two troughs test the same support level, then price closes below it by the breakdown margin (default 2%). Tolerance is normalized by daily volatility (z-scores). Requires minimum 8% rally between troughs.

Signal family

Pattern — Formal chart-pattern detectors (double tops / bottoms, failed breakouts, HH/HL structure).

Parameters

Name Description Default Range
peak_order Peak detection window 15 5–25
tolerance_zscore Tolerance (z-scores of daily vol) 1.5 0.5–3.0
min_separation Min days between troughs 25 10–60
max_separation Max days between troughs 252 60–504

Historical context

110,750 triggers on 21,113 tickers, 1989-03-31 → 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 Bearish α
5-day +0.24%
20-day +0.57%
60-day +0.48%
1-year +1.86%
Random-date null check (20-day): Bearish: worse than random (p=1.000).

Double Bottom Breakdown is a single-direction signal — only the bearish side is meaningful.

Where does DOUBLE_BOTTOM_BREAKDOWN 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.

Double Bottom Breakdown (double_bottom_breakdown) — trigger count distribution by per-stock regime quadrant (trending/non-trending × high/low realized volatility) for 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.

Double Bottom Breakdown (double_bottom_breakdown) — mean 20-day alpha versus S&P 500 Equal Weight by per-stock regime quadrant, 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.

Double Bottom Breakdown (double_bottom_breakdown) — 20-day alpha split by historical sub-period (2015-2019, 2020-2022, 2023+) to check consistency across market regimes

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

Bench Metric 1d 5d 20d 60d 252d
spxew Stock % +0.06% +0.34% +1.95% +3.84% +13.47%
Bench % +0.08% +0.09% +1.31% +3.33% +11.60%
Alpha % -0.02% +0.24% +0.57% +0.48% +1.86%
Median alpha -0.01% +0.15% -0.10% -1.49% -7.17%
Hit rate (α>0) 49.7% 51.2% 49.5% 46.0% 41.5%
p (naive) 0.0839 <0.001 <0.001 <0.001 <0.001
p (HAC) 0.0846 <0.001 <0.001 <0.001 <0.001
N 107,429 103,985 102,317 98,881 93,585
spx Stock % +0.06% +0.34% +1.95% +3.84% +13.47%
Bench % +0.04% +0.24% +1.65% +3.81% +15.32%
Alpha % +0.02% +0.13% +0.29% -0.00% -1.65%
Median alpha +0.01% +0.07% -0.32% -2.01% -10.72%
Hit rate (α>0) 50.2% 50.6% 48.5% 44.9% 37.9%
p (naive) 0.0435 <0.001 <0.001 0.9834 <0.001
p (HAC) 0.0440 <0.001 <0.001 0.9863 <0.001
N 108,291 104,979 103,915 100,223 94,978
msci Stock % +0.06% +0.34% +1.95% +3.84% +13.47%
Bench % +0.10% +0.23% +1.48% +3.53% +12.96%
Alpha % -0.01% +0.10% +0.39% +0.46% -0.07%
Median alpha -0.01% +0.04% -0.23% -1.60% -8.70%
Hit rate (α>0) 49.7% 50.3% 48.9% 45.8% 39.8%
p (naive) 0.1726 <0.001 <0.001 <0.001 0.6863
p (HAC) 0.1740 <0.001 <0.001 <0.001 0.8639
N 107,775 104,351 102,132 99,543 93,669
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.
Double Bottom Breakdown (double_bottom_breakdown) — 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 +0.13% +0.08% [+0.07%, +0.10%] 1.000
1d spx +0.14% +0.09% [+0.08%, +0.11%] 1.000
1d msci +0.14% +0.10% [+0.08%, +0.11%] 1.000
5d spxew +0.66% +0.38% [+0.34%, +0.42%] 1.000
5d spx +0.58% +0.39% [+0.35%, +0.43%] 1.000
5d msci +0.55% +0.40% [+0.36%, +0.44%] 1.000
20d spxew +1.82% +1.24% [+1.16%, +1.31%] 1.000
20d spx +1.76% +1.26% [+1.19%, +1.34%] 1.000
20d msci +1.74% +1.28% [+1.20%, +1.35%] 1.000
60d spxew +3.24% +2.65% [+2.52%, +2.79%] 1.000
60d spx +3.48% +2.72% [+2.60%, +2.85%] 1.000
60d msci +3.50% +2.73% [+2.61%, +2.86%] 1.000
252d spxew +6.98% +5.43% [+5.19%, +5.66%] 1.000
252d spx +7.37% +5.74% [+5.50%, +5.98%] 1.000
252d msci +6.82% +5.65% [+5.41%, +5.89%] 1.000

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

Six recent bearish DOUBLE_BOTTOM_BREAKDOWN 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 DOUBLE_BOTTOM_BREAKDOWN looks like when it works)
Weakest outcomes (what DOUBLE_BOTTOM_BREAKDOWN looks like when it fails)
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 8,020 +0.29% +1.09% -0.77% <0.001 +0.29% +1.40% -1.07% <0.001 +0.29% +1.24% -0.90% <0.001
Trending + High vol Crisis selloff or parabolic rally 38,766 +2.35% +1.27% +0.98% <0.001 +2.35% +1.76% +0.56% <0.001 +2.35% +1.56% +0.70% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 8,718 +0.33% +1.32% -0.91% <0.001 +0.33% +1.47% -1.09% <0.001 +0.33% +1.36% -0.98% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 55,246 +2.17% +1.37% +0.73% <0.001 +2.17% +1.67% +0.52% <0.001 +2.17% +1.50% +0.58% <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 32,427 -0.24% <0.001 -0.26% <0.001 -0.01% 0.8301
2020-2022 2020-01-01 → 2023-01-01 35,740 +0.84% <0.001 +0.71% <0.001 +0.86% <0.001
2023-2026 2023-01-01 → 2099-01-01 42,512 +0.95% <0.001 +0.34% <0.001 +0.29% <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. This signal fires bearish-only — there is no bullish variant. Bearish 20d alpha is +0.57%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 bearish setup: Non-trending + Low vol — alpha -0.91% / 20d on 8,718 historical triggers.
  • Best era for bearish: 2015-2019 — alpha -0.24% / 20d on 32,427 triggers.

3 · When it fails — common false positives

  • Weakest bearish cell: Trending + High vol — alpha +0.98% / 20d on 38,766 triggers.
  • Worst era for bearish: 2023-2026 — alpha +0.95% / 20d on 42,512 triggers.

Signal-specific failure patterns

The entry is structurally late
The trigger demands a lot of confirmation before it prints: two local troughs (15 bars each side) at the same volatility-adjusted support level (within 1.5 z-scores of daily volatility, clamped to a 1.5-12% band), at least 25 trading days apart, an 8%+ rally between them, and finally a close 2% below the lower trough. By the time every condition is satisfied, price has already given back the full intervening bounce plus the breakdown margin. Whether persistent weakness remains after that toll — or the sellers are exhausted by it — is an empirical question; read the at-a-glance table and the permutation-null line above for the current answer at each horizon rather than assuming the textbook continuation.
Broken support attracts two opposing flows
A support level defined by two prior lows is visible to every chart reader, and the close that finally breaks it by 2% often coincides with stop-loss cascades, forced liquidation, and capitulation selling — flows that argue for continuation. The same prints, however, attract value buyers and short covering — flows that argue for a bounce. 'The breakdown starts a new down-leg' and 'the breakdown was the flush that ended the move' are both live hypotheses, and which one dominates has differed across market regimes; the live tables on this page adjudicate between them for the current sample.
Rare by construction, so single fires carry little weight
The pattern geometry (trough matching within tolerance, minimum 25-day separation, minimum 8% intervening rally) plus a 20-day exclusion window that suppresses overlapping patterns keep per-ticker trigger frequency low by design — the breakdown must also arrive within roughly a year of the second trough or the pattern lapses. A single fire on a single stock is an anecdote, not evidence; the signal's statistical properties only show up in aggregate. Treat any one breakdown as a chart annotation, not a standalone thesis.

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.

Reversal-pattern family

Double bottom and double top are canonical two-swing reversal patterns (Edwards & Magee, Technical Analysis of Stock Trends, 11th ed. 2018; Bulkowski, Encyclopedia of Chart Patterns, 3rd ed. 2021; Lo, Mamaysky, and Wang, "Foundations of Technical Analysis", Journal of Finance 55(4), 2000). A completed double-bottom breakdown and a failed-double-bottom signal on the same stock fire in sequence rather than concurrently — they represent different stages of the same pattern.

Measured pairings — Bonferroni survivors

Beyond the literature pairings above, these are the same-day co-fire combinations involving Double Bottom Breakdown 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 — 1 of the 4 rows below does 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.

US (NYSE / NASDAQ / AMEX)

Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
bollinger bearish + double_bottom_breakdown bearish -3.89%

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

China A-shares — 3 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
double_bottom_breakdown bearish + weekly_change bearish +2.40% +1.39% 2,563 0.002
double_bottom_breakdown bearish + new_20d_low bearish +0.79% +0.46% 6,655 0.004
double_bottom_breakdown bearish + fresh_52w_low bearish +0.87% -0.74% 1,186 0.058

3 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 gate on the breakdown dayBreakdowns on light volume are structurally suspect — thin prints through a visible support level often reverse as short squeezes, while a break on 1.5-2x average volume looks more like genuine distribution. The gate discards most triggers, which is the point — it concentrates the remaining sample into a plausibly different population. Testable within the platform's own screens.
  • Use the failure as the signalIf the breakdown closes back above the double-bottom level within days, that reversal is captured by the failed_double_bottom module. One coherent way to use this signal is as a watchlist feeder for the failure event rather than as a short entry in its own right.
  • Condition on the breadth regimeWhether broken-support names keep underperforming plausibly depends on the market regime — narrow, risk-off tapes treat breakdowns differently from broad recoveries. Rather than hard-coding a regime verdict, check the regime split in the tables above and the platform's breadth dashboard before leaning on the signal; a breadth-conditioned version of the screen is directly testable.

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? Pattern signals carry their own structural context; check that the implied support/resistance levels have historical relevance, not just the most-recent 3-month range.
  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

Direction is nominally bearish, but treat tradability as an empirical question: if the bearish side beats the random-date null in the current tables at your horizon, the signal can serve as a short-side or avoid-list screen tile; if it does not, treat fires as context — a marker that a widely watched support level just failed — rather than a short entry. If traded, entry at the open T+1 with a defined invalidation: a close back above the broken support is the pattern failing, and that event is itself captured by the failed_double_bottom signal. Everything here describes historical tendency, not a recommendation.