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% |
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.
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. This is the 20-day alpha a trade taken on the trigger would have captured. This signal is bearish-only, so negative bars mark the regimes where it worked — a bearish trigger is right when the stock underperforms. Positive bars mark regimes to avoid. One strong bar beside three flat ones is not a "20-day alpha" signal — it is a "20-day alpha when the stock is X" signal. Bar labels carry the sample size; a cell built on a handful of triggers is noise, not a regime finding.
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 carrying the sign that favours the trade means the signal is durable; one era doing all the work means a regime-specific edge that may not repeat. The greater the variance across eras, the smaller the position it justifies.
↓ 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 |
Permutation null detail — all horizons × each benchmark
| 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, ranked within this sample of six: the top three and the bottom three, with extreme outliers excluded. Ranking is relative, not absolute — where the signal did well across the sampled names, even the bottom three can have beaten the benchmark, so the alpha printed on each panel is what settles it. Both groups are tail outcomes by construction; read them as the range, not the typical result.
Best three of the six sampled
Weakest three of the six sampled — not necessarily losses
Stock-regime quadrants (2×2 per-stock, 20d alpha detail table)
| 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)
| 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
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 day — Breakdowns 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 signal — If 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 regime — Whether 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 acting — a 5-point checklist
- 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.
- 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.
- 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.
- Is ADV20 enough for the intended size? A $1M notional order in a $500M name moves the tape by itself. A useful floor is adv20d ≥ 5% of the intended position.
- What invalidates the trade? Define a price level in advance (for longs: a close below the trigger-day low; for shorts: a close above the trigger-day high) and honour it. The backtest alpha is an average; any single trade can land 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.