Pattern failed_double_bottom

Failed Double Bottom Breakdown

Bullish reversal: price broke below support (double bottom breakdown) but then rises back above the support level. Bears are trapped. Failure threshold normalized by daily volatility.

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
failure_window Max days for failure after breakdown 60 20–120

Historical context

77,180 triggers on 20,144 tickers, 1993-01-29 → 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
5-day -0.32%
20-day -0.34%
60-day -0.59%
1-year +0.85%

Sign flip across horizons. Bullish raw alpha moves from -0.32% (5d) to +0.85% (1y). Check the permutation rows for those horizons before reading the longer-hold number as edge — raw alpha alone does not distinguish signal timing from universe drift.

Random-date null check (20-day): Bullish: worse than random (p=1.000)

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

Where does FAILED_DOUBLE_BOTTOM 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.

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

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

Failed Double Bottom Breakdown (failed_double_bottom) — 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 % -0.06% -0.09% +0.69% +2.04% +12.26%
Bench % +0.04% +0.23% +0.98% +2.56% +10.90%
Alpha % -0.12% -0.32% -0.34% -0.59% +0.85%
Median alpha -0.17% -0.55% -1.37% -2.85% -7.73%
Hit rate (α>0) 46.6% 44.9% 43.9% 42.5% 40.7%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 <0.001 <0.001 <0.001 0.0701
N 74,461 71,265 70,149 68,334 62,433
spx Stock % -0.06% -0.09% +0.69% +2.04% +12.26%
Bench % +0.03% +0.31% +1.21% +3.34% +14.74%
Alpha % -0.11% -0.40% -0.53% -1.36% -2.47%
Median alpha -0.15% -0.66% -1.53% -3.50% -11.32%
Hit rate (α>0) 46.6% 44.1% 43.2% 40.9% 37.1%
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 75,016 72,384 71,522 69,310 64,153
msci Stock % -0.06% -0.09% +0.69% +2.04% +12.26%
Bench % +0.06% +0.28% +1.00% +2.84% +12.12%
Alpha % -0.12% -0.38% -0.33% -0.82% -0.61%
Median alpha -0.20% -0.65% -1.36% -3.04% -9.17%
Hit rate (α>0) 45.8% 44.2% 43.8% 42.1% 39.0%
p (naive) <0.001 <0.001 <0.001 <0.001 0.0025
p (HAC) <0.001 <0.001 <0.001 <0.001 0.1939
N 74,445 71,544 70,580 68,957 62,640
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.
Failed Double Bottom Breakdown (failed_double_bottom) — 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 +0.03% +0.08% [+0.07%, +0.10%] 1.000
1d spx +0.02% +0.09% [+0.08%, +0.11%] 1.000
1d msci +0.04% +0.10% [+0.08%, +0.11%] 1.000
5d spxew +0.11% +0.37% [+0.33%, +0.42%] 1.000
5d spx +0.07% +0.39% [+0.34%, +0.44%] 1.000
5d msci +0.08% +0.39% [+0.35%, +0.44%] 1.000
20d spxew +0.86% +1.22% [+1.12%, +1.30%] 1.000
20d spx +0.89% +1.25% [+1.14%, +1.33%] 1.000
20d msci +0.98% +1.26% [+1.16%, +1.35%] 1.000
60d spxew +1.89% +2.62% [+2.46%, +2.77%] 1.000
60d spx +1.86% +2.69% [+2.54%, +2.83%] 1.000
60d msci +1.96% +2.70% [+2.56%, +2.86%] 1.000
252d spxew +5.15% +5.25% [+5.02%, +5.49%] 0.756
252d spx +5.67% +5.59% [+5.35%, +5.86%] 0.264
252d msci +5.38% +5.50% [+5.28%, +5.76%] 0.836

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

Six recent bullish FAILED_DOUBLE_BOTTOM 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 FAILED_DOUBLE_BOTTOM looks like when it works)
Weakest outcomes (what FAILED_DOUBLE_BOTTOM 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 2,212 -0.24% +0.33% -0.54% 0.0007 -0.24% +0.59% -0.78% <0.001 -0.24% +0.44% -0.65% <0.001
Trending + High vol Crisis selloff or parabolic rally 31,904 +0.80% +1.18% -0.49% <0.001 +0.80% +1.45% -0.70% <0.001 +0.80% +1.12% -0.42% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 4,710 +0.19% +0.38% -0.20% 0.0749 +0.19% +0.52% -0.34% 0.0027 +0.19% +0.41% -0.22% 0.0486
Non-trending + High vol Classical "whipsaw zone" for momentum 38,354 +0.71% +0.88% -0.22% 0.0013 +0.71% +1.14% -0.40% <0.001 +0.71% +0.95% -0.24% 0.0004
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 20,632 -0.99% <0.001 -1.07% <0.001 -0.87% <0.001
2020-2022 2020-01-01 → 2023-01-01 25,424 +0.30% 0.0032 +0.37% 0.0002 +0.66% <0.001
2023-2026 2023-01-01 → 2099-01-01 31,100 -0.48% <0.001 -0.95% <0.001 -0.81% <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 -0.34%worse than random : firing on random dates would have done better. This signal fires bullish-only — there is no bearish variant. 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

  • Least-bad bullish cell: Non-trending + Low vol — alpha -0.20% / 20d on 4,710 triggers — still wrong-signed; no bullish cell produced positive alpha.
  • Best era for bullish: 2020-2022 — alpha +0.30% / 20d on 25,424 triggers.

3 · When it fails — common false positives

  • Weakest bullish cell: Trending + Low vol — alpha -0.54% / 20d on 2,212 triggers.
  • Worst era for bullish: 2015-2019 — alpha -0.99% / 20d on 20,632 triggers.

Signal-specific failure patterns

The trigger fires after the bounce, not before it
The signal requires a completed double-bottom breakdown first — two troughs testing the same support (within a tolerance of 1.5 z-scores of daily volatility), a minimum 8% rally between them, then a close below support by the 2% breakdown margin — followed by a close back above the support level by a volatility-scaled failure margin within 60 trading days. By construction the trigger prints only after the recovery through support has already happened, so the sharpest leg of any short-covering squeeze sits inside the pattern, before the forward-return window opens. Whatever the holder captures after the trigger day is the residual of the move, not the move itself.
'Bears trapped' is a positioning story; breakdowns usually had a reason
Names that break a twice-tested support level generally do so because something deteriorated. A recovery back above support can be genuine accumulation, but it can equally be a short-cover rally with no new buyers behind it — and price geometry alone cannot distinguish the two. Once the squeeze exhausts, the weakness that produced the breakdown is free to reassert. Durable bottoms tend to be anchored by a fundamental change (earnings inflection, balance-sheet repair), which is exactly the input a purely technical pattern does not see.
Vol-scaled thresholds make the trigger population heterogeneous
Both the pattern tolerance (1.5 z-scores of trailing 252-day daily volatility, clamped between 1.5% and 12%) and the failure margin (1 z-score, clamped between 1% and 8%) adapt to each stock's volatility. In a quiet name a shallow drift back above support qualifies as a failed breakdown; in a volatile name the recovery must be far larger. A screen of these triggers therefore mixes marginal recoveries with violent squeezes, and there is no reason their forward behavior should match. Judge the direction verdict from the at-a-glance table and the permutation-null line above, not from the pattern's textbook story.

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.

Sequential with completed pattern

Failed double bottom and double-bottom breakdown are two stages of the same underlying structure: the breakdown signal fires when price closes below the shared support by the breakdown margin; the failed version fires when that breakdown is negated — price closes back above the support within the failure window (Edwards & Magee, Technical Analysis of Stock Trends, 11th ed. 2018; Bulkowski, Encyclopedia of Chart Patterns, 3rd ed. 2021). They are sequential rather than concurrent — one signal replacing the other as the setup evolves, so seeing both on the same chart is one piece of evidence, not two.

Measured pairings — Bonferroni survivors

Beyond the literature pairings above, these are the same-day co-fire combinations involving Failed 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 — 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.

China A-shares

Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
failed_double_bottom bullish + weekly_change bearish +9.65% +10.09% 73 0.002
failed_double_bottom bullish + ma_crossover bearish +4.44% +5.28% 38 0.054
failed_double_bottom bullish + vwap_cross bullish +1.31% +2.14% 1,368 0.002
failed_double_bottom bullish + hh_hl_streak bullish +1.85% +1.89% 644 0.002
failed_double_bottom bullish + macd bullish +1.42% +1.82% 756 0.002

5 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.

  • Require a fundamental anchorA failed double bottom in a name with improving fundamentals is a structurally different bet than a bare pattern completion. The fundamentals filter on Daily Reports (live) can restrict triggers to names clearing profitability or valuation thresholds, separating recoveries with a real anchor from purely technical short-cover bounces.
  • Check the shortest horizons firstIf a trapped-bears squeeze carries any edge, it should show in the shortest horizon columns and fade from there — the mechanical bounce plays out in days, not months. A profile that decays or flips between the 1-5d and 20d+ columns in the live tables is consistent with a squeeze fading and the underlying weakness reasserting.
  • Use as the failure diagnostic of another patternEven when it is not an entry trigger, the signal has diagnostic value: it marks the exact moment a bearish breakdown thesis is invalidated. For anyone positioned short on the double-bottom breakdown, the failed version is the mechanical exit bell — and for docs purposes it is a clean illustration of why classical pattern completions need out-of-sample verification.

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

Read tradability off the live tables, not the textbook: if the bullish side beats the random-date null in the current at-a-glance table, failed double bottoms can serve as a long-side candidate screen; if it does not, treat fires as context on names already under coverage. Any squeeze edge is mechanically front-loaded, so weigh the short-horizon columns before the 60-day ones. Triggers are computed on closing prices; the earliest realistic entry is the next session's open. Historical tendency, not a recommendation.