Pattern failed_double_top

Failed Double Top Breakout

Bearish reversal: price broke above resistance (double top breakout) but then falls back below the resistance level. Bulls 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 breakout 60 20–120

Historical context

72,982 triggers on 19,843 tickers, 1989-02-28 → 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 +0.31%
20-day +0.53%
60-day +0.37%
1-year +3.43%
Random-date null check (20-day): Bearish: worse than random (p=1.000).

Failed Double Top Breakout is a single-direction signal — only the bearish side is meaningful.

Where does FAILED_DOUBLE_TOP 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 Top Breakout (failed_double_top) — 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.

Failed Double Top Breakout (failed_double_top) — 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.

Failed Double Top Breakout (failed_double_top) — 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 % +0.13% +0.48% +1.25% +2.89% +13.78%
Bench % +0.03% +0.17% +0.72% +2.46% +10.21%
Alpha % +0.10% +0.31% +0.53% +0.37% +3.43%
Median alpha +0.03% -0.04% -0.56% -2.10% -6.03%
Hit rate (α>0) 50.5% 49.6% 47.4% 44.4% 42.8%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 <0.001 <0.001 0.0002 <0.001
N 70,547 68,303 67,835 64,962 57,602
spx Stock % +0.13% +0.48% +1.25% +2.89% +13.78%
Bench % +0.01% +0.25% +1.11% +3.33% +14.32%
Alpha % +0.12% +0.23% +0.17% -0.53% -0.72%
Median alpha +0.04% -0.13% -0.94% -3.12% -10.38%
Hit rate (α>0) 50.8% 48.8% 45.7% 41.9% 38.3%
p (naive) <0.001 <0.001 0.0002 <0.001 0.0009
p (HAC) <0.001 <0.001 0.0003 <0.001 0.2296
N 71,065 68,947 68,569 65,687 58,223
msci Stock % +0.13% +0.48% +1.25% +2.89% +13.78%
Bench % +0.02% +0.24% +0.94% +3.00% +11.75%
Alpha % +0.11% +0.26% +0.30% -0.06% +1.32%
Median alpha +0.03% -0.10% -0.81% -2.70% -8.01%
Hit rate (α>0) 50.5% 49.1% 46.3% 42.9% 40.6%
p (naive) <0.001 <0.001 <0.001 0.4441 <0.001
p (HAC) <0.001 <0.001 <0.001 0.5331 0.0294
N 70,813 68,650 67,998 65,408 57,727
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.
Failed Double Top Breakout (failed_double_top) — 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 +0.23% +0.08% [+0.06%, +0.10%] 1.000
1d spx +0.23% +0.09% [+0.07%, +0.11%] 1.000
1d msci +0.25% +0.09% [+0.07%, +0.11%] 1.000
5d spxew +0.68% +0.35% [+0.30%, +0.40%] 1.000
5d spx +0.64% +0.37% [+0.32%, +0.42%] 1.000
5d msci +0.67% +0.37% [+0.33%, +0.42%] 1.000
20d spxew +1.56% +1.13% [+1.04%, +1.22%] 1.000
20d spx +1.42% +1.16% [+1.07%, +1.25%] 1.000
20d msci +1.44% +1.17% [+1.08%, +1.26%] 1.000
60d spxew +2.29% +2.37% [+2.21%, +2.52%] 0.149
60d spx +2.13% +2.45% [+2.30%, +2.60%] 0.005
60d msci +2.17% +2.46% [+2.31%, +2.61%] 0.005
252d spxew +5.02% +4.65% [+4.33%, +4.92%] 0.995
252d spx +4.91% +5.00% [+4.67%, +5.30%] 0.284
252d msci +4.70% +4.92% [+4.61%, +5.22%] 0.095

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

Six recent bearish FAILED_DOUBLE_TOP 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_TOP looks like when it works)
Weakest outcomes (what FAILED_DOUBLE_TOP 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 2,228 +0.54% +0.51% -0.00% 0.9945 +0.54% +1.03% -0.46% 0.0040 +0.54% +0.81% -0.25% 0.0983
Trending + High vol Crisis selloff or parabolic rally 39,552 +1.64% +0.70% +0.98% <0.001 +1.64% +1.11% +0.58% <0.001 +1.64% +0.96% +0.72% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 4,189 +0.28% +0.66% -0.36% 0.0005 +0.28% +1.11% -0.80% <0.001 +0.28% +0.91% -0.61% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 27,012 +0.91% +0.72% +0.12% 0.0940 +0.91% +1.07% -0.18% 0.0105 +0.91% +0.88% -0.07% 0.3463
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 17,841 +0.03% 0.6911 -0.19% 0.0151 +0.04% 0.5605
2020-2022 2020-01-01 → 2023-01-01 22,296 +0.26% 0.0053 +0.33% 0.0004 +0.50% <0.001
2023-2026 2023-01-01 → 2099-01-01 32,817 +1.01% <0.001 +0.27% 0.0004 +0.32% <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 +0.53%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 -0.36% / 20d on 4,189 historical triggers.
  • Least-bad era for bearish: 2015-2019 — alpha +0.03% / 20d on 17,841 triggers — still wrong-signed; no era produced negative alpha.

3 · When it fails — common false positives

  • Weakest bearish cell: Trending + High vol — alpha +0.98% / 20d on 39,552 triggers.
  • Worst era for bearish: 2023-2026 — alpha +1.01% / 20d on 32,817 triggers.

Signal-specific failure patterns

A trap and a shakeout look identical at the trigger
The signal fires when a completed double-top breakout (a close at least 2% above the twin-peak resistance) reverses: a later close falls back below the resistance by roughly one z-score of daily volatility (clamped to a 1-8% band) within 60 trading days of the breakout. The textbook reading is bulls trapped — late buyers stranded above a level that failed. But the identical price path also describes a shakeout inside an intact uptrend, where the dip below resistance gets bought and the advance resumes. Both resolutions occur in practice; which dominates in aggregate is an empirical question — read the at-a-glance table and the permutation-null line above for the current answer rather than assuming the trap thesis.
The fire is late relative to the reversal it describes
By construction the trigger prints only after a full round trip: the breakout margin (2% above resistance) plus the volatility-scaled failure margin back below it. On a high-volatility name that round trip can be a large percentage move that has already happened before the signal exists. Whatever tendency the live tables show applies to the period after the reversal is established, not to catching the top — set expectations per horizon from the table columns, not from the pattern's reputation.
Not independent of the breakout signal
Every failed_double_top fire is preceded, within 60 trading days, by a double_top_breakout fire on the same structure. The two are sequential stages of one pattern, not two independent pieces of evidence — a screen that scores both as separate confirmations is double-counting. A 20-day exclusion window also suppresses overlapping fires on the same ticker, so per-ticker frequency is low by design.
Single-direction by design
'Failed double top' is definitionally bearish — there is no bullish variant of this event. The bullish mirror image (a double-bottom breakdown that reverses back above support, trapping bears) is its own signal, failed_double_bottom, documented separately.

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-top and double-top-breakout fire on the same underlying pattern structure at different points: the breakout signal fires when price closes above the twin-peak resistance level by the breakout margin; failed_double_top fires when, after that breakout, price falls back below the level by a volatility-scaled threshold 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, not two independent pieces of evidence.

Measured pairings — Bonferroni survivors

Beyond the literature pairings above, these are the same-day co-fire combinations involving Failed Double Top Breakout 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_top bearish + weekly_change bearish +3.04% +4.34% 1,298 0.002
failed_double_top bearish + rsi bearish +2.12% +2.86% 749 0.002
failed_double_top bearish + new_20d_low bearish +2.36% +2.20% 1,860 0.002
failed_double_top bearish + hh_hl_streak bearish +1.65% +2.18% 939 0.002
failed_double_top bearish + macd bearish +1.57% +1.38% 887 0.002
failed_double_top bearish + vwap_cross bearish +1.05% +1.20% 1,850 0.002

6 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.

  • Volume-gate the failure dayA failure day on heavy volume reads as distribution — size exiting through a level the crowd is watching; on light volume it reads as noise that often reverts. The filter is derivable from OHLC plus volume and testable within the platform's own screens.
  • Demand a decisive failureThe default failure threshold is one z-score of daily volatility below the resistance (clamped to 1-8%). Requiring a deeper close below the level, or several consecutive closes below it, filters one-day shakeouts at the cost of an even later entry — a trade-off worth testing rather than assuming.
  • Condition on trend contextA failed breakout inside a deteriorating trend structure (for example, a bearish HH/HL reading) is plausibly a different population from a failed breakout inside an intact long-term uptrend, where dips below old resistance tend to get bought. Pairing the fire with a trend-structure filter is testable within the platform.

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 definitionally 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 screen tile; if it does not, treat fires as context — a note that a widely watched breakout just failed — rather than a short entry. If traded, entry at the open T+1; the natural invalidation is a close back above the resistance level, which would mean the failure itself failed and the breakout re-asserted. Everything here describes historical tendency, not a recommendation.