bearish_trend_breakout
Bearish Trend Breakout
Identifies stocks trading near short-term highs but within long-term lows, confirmed by a 20-day new high. Triggers when price is above the Nth percentile of the short range AND below the Nth percentile of the long range AND makes a new N-day high.
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 |
|---|---|---|---|
| short_months | Short range (calendar months) | 3 | 1–6 |
| short_percentile | Short range percentile | 80 | 50–99 |
| long_years | Long range (calendar years) | 5 | 2–10 |
| long_percentile | Long range percentile | 25 | 1–50 |
| breakout_period | New high lookback (days) | 20 | 5–60 |
Historical context
27,548 valid triggers on 1,476 distinct tickers between 2020-05-01 and 2026-04-22. Universe: us_only · mcap ≥ $100,000,000 · price ≥ $1 (2,367 tickers). Entry at open T+1. 1d = intraday T+1; 20d = open T+1 to close T+20.
Benchmarks: spxew (S&P 500 Equal Weight — the primary benchmark here; a median-stock view that avoids the 2020+ megacap-concentration distortion), spx (S&P 500, cap-weighted), and msci (MSCI World USD). Per-stock regime: trending = ADX(14) ≥ 25, high vol = 20d ann. vol ≥ 20%.
At a glance (20d alpha vs S&P 500 Equal Weight, US-only)
Bearish Trend Breakout is a single-direction signal — only the bullish side is meaningful. (The trigger condition only describes one side of the move.)
Reading this: the random-date null is: for each ticker, sample N random dates and compute the same alpha — what alpha does a signal with no information produce? If the signal's observed alpha beats the null (pperm≤0.05), it's adding real information. If it's inside or worse than the null, the signal doesn't add value over random firing — any observed alpha is either noise or a universe artifact.
How often does BEARISH_TREND_BREAKOUT fire in each regime?
The signal's bucket distribution is itself informative. If 50%+ of all BEARISH_TREND_BREAKOUT triggers fire in the "non-trending + high vol" quadrant, the signal is structurally a chop-market event — regardless of what its textbook definition claims. Bullish and bearish are shown separately; counts are across the full US-only sample after the mcap and price floor.
Per-stock regime quadrant — 20d alpha
Each trigger is tagged with the host stock's own technical regime on the trigger date: is the stock itself in a trend (ADX(14) ≥ 25) or ranging? And is its realized 20-day volatility high (≥ 20% annualized) or low? This is the textbook conditioning variable — "does this signal work better in trending stocks?" — answered at the level of the individual stock, not the market. Positive bars are good for the signal; negative bars mean alpha vanishes into the benchmark or worse.
Sub-period check — does the signal work in every era?
A multi-year average can hide major instability. We split the sample into three non-overlapping windows: 2015–2019 (pre-COVID, normalized monetary policy), 2020–2022 (pandemic crash + recovery + rate-shock bear), and 2023+ (post-ZIRP, AI megacap rally). If a signal's alpha is positive overall but comes entirely from one era, that's a red flag — the conditions that produced it may not repeat. A robust signal shows a consistent sign across all non-empty buckets. Note: this signal requires 1260 trading days of prior history per ticker. Triggers on tickers with less history are excluded, which is why the earliest bucket may have zero observations.
Longer-horizon views
This signal carries a long lookback window (1260 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
60-day alpha by era
1-year alpha by stock regime
1-year alpha by era
1-year observed alpha vs random-date null
↑ Bullish triggers
| Bench | Metric | 1d | 5d | 20d | 60d | 252d |
|---|---|---|---|---|---|---|
| spx | Stock % | -0.03% | +0.12% | +0.48% | +1.19% | +9.35% |
| Bench % | +0.01% | +0.18% | +0.90% | +2.99% | +16.71% | |
| Alpha % | -0.03% | -0.06% | -0.43% | -1.78% | -7.31% | |
| Median alpha | -0.10% | -0.40% | -1.82% | -5.33% | -17.81% | |
| Hit rate (α>0) | 47.8% | 46.9% | 43.6% | 40.0% | 34.0% | |
| p (naive) | 0.1942 | 0.2769 | <0.001 | <0.001 | <0.001 | |
| p (HAC) | 0.1901 | 0.4135 | 0.0331 | 0.0002 | <0.001 | |
| N | 27,534 | 27,169 | 26,779 | 25,583 | 17,920 | |
| msci | Stock % | -0.03% | +0.12% | +0.48% | +1.19% | +9.35% |
| Bench % | +0.04% | +0.18% | +0.79% | +2.71% | +14.57% | |
| Alpha % | -0.07% | -0.07% | -0.31% | -1.49% | -5.23% | |
| Median alpha | -0.12% | -0.41% | -1.72% | -5.01% | -15.72% | |
| Hit rate (α>0) | 47.6% | 47.0% | 43.9% | 40.6% | 35.3% | |
| p (naive) | 0.0042 | 0.1891 | 0.0027 | <0.001 | <0.001 | |
| p (HAC) | 0.0039 | 0.3230 | 0.1169 | 0.0020 | 0.0031 | |
| N | 27,290 | 27,019 | 26,668 | 25,389 | 17,845 | |
| spxew | Stock % | -0.03% | +0.12% | +0.48% | +1.19% | +9.35% |
| Bench % | +0.01% | +0.12% | +0.49% | +1.40% | +8.37% | |
| Alpha % | -0.03% | +0.01% | -0.02% | -0.20% | +1.01% | |
| Median alpha | -0.08% | -0.31% | -1.29% | -3.81% | -9.61% | |
| Hit rate (α>0) | 48.4% | 47.5% | 45.0% | 42.6% | 40.8% | |
| p (naive) | 0.1594 | 0.9178 | 0.8692 | 0.2758 | 0.0277 | |
| p (HAC) | 0.1556 | 0.9380 | 0.9319 | 0.6728 | 0.5687 | |
| N | 27,534 | 27,169 | 26,779 | 25,583 | 17,920 |
Permutation null detail — all horizons × both benchmarks
| Horizon | Bench | Observed α | Null mean | Null 95% CI | pperm |
|---|---|---|---|---|---|
| 1d | spx | -0.03% | -0.02% | [-0.07%, +0.03%] | 0.622 |
| 1d | msci | -0.07% | -0.05% | [-0.09%, +0.01%] | 0.746 |
| 1d | spxew | -0.03% | -0.05% | [-0.10%, +0.00%] | 0.249 |
| 5d | spx | -0.06% | +0.34% | [-0.08%, +1.89%] | 0.925 |
| 5d | msci | -0.07% | +0.35% | [-0.08%, +1.91%] | 0.965 |
| 5d | spxew | +0.01% | +0.36% | [-0.06%, +1.94%] | 0.861 |
| 20d | spx | -0.43% | +0.40% | [-0.10%, +2.13%] | 1.000 |
| 20d | msci | -0.31% | +0.53% | [+0.03%, +2.27%] | 1.000 |
| 20d | spxew | -0.02% | +0.58% | [+0.07%, +2.34%] | 0.990 |
| 60d | spx | -1.78% | +0.65% | [-0.17%, +2.66%] | 1.000 |
| 60d | msci | -1.49% | +1.12% | [+0.29%, +3.15%] | 1.000 |
| 60d | spxew | -0.20% | +1.27% | [+0.46%, +3.30%] | 1.000 |
| 252d | spx | -7.31% | -1.30% | [-2.82%, +0.17%] | 1.000 |
| 252d | msci | -5.23% | +1.08% | [-0.38%, +2.50%] | 1.000 |
| 252d | spxew | +1.01% | +2.14% | [+0.69%, +3.69%] | 0.945 |
Example triggers on US large-caps (2023+, mcap ≥ $30B)
Six recent bullish BEARISH_TREND_BREAKOUT triggers on US mega-caps, filtered to |alpha| ≤ 25% to exclude catalyst-driven outliers (earnings surprises, M&A, binary events). The first three are the strongest outcomes — what the signal looks like when it works. The last three are the weakest — what the signal looks like when it fails. Each chart shows the stock's price with signal-appropriate technical overlays (e.g. MACD subpanel on MACD pages, Bollinger Bands on Bollinger pages, the 52-week trailing max line on 52w-high pages), a dot marking the trigger date, and the forward window shaded (green when the signal was right, red when it wasn't). Click any chart to open full-size.
Strongest outcomes (what BEARISH_TREND_BREAKOUT looks like when it works)
Weakest outcomes (what BEARISH_TREND_BREAKOUT looks like when it fails)
Stock-regime quadrants (2×2 per-stock, 20d alpha detail table)
| 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 | 1,237 | -0.68% | +0.61% | -1.26% | 0.0724 | -0.68% | +0.54% | -1.19% | 0.0766 | -0.68% | +0.34% | -1.03% | 0.1279 |
| Trending + High vol Crisis selloff or parabolic rally | 13,229 | +0.51% | +0.98% | -0.45% | 0.1445 | +0.51% | +0.85% | -0.33% | 0.2870 | +0.51% | +0.48% | +0.04% | 0.9101 |
| Non-trending + Low vol Quiet chop, summer doldrums | 907 | +0.22% | +0.24% | -0.04% | 0.9313 | +0.22% | +0.15% | +0.00% | 0.9955 | +0.22% | +0.00% | +0.21% | 0.6190 |
| Non-trending + High vol Classical "whipsaw zone" for momentum | 12,175 | +0.54% | +0.89% | -0.36% | 0.1501 | +0.54% | +0.78% | -0.24% | 0.3389 | +0.54% | +0.56% | -0.02% | 0.9209 |
Sub-period breakdown table (20d alpha)
| Period | N | Alpha % (spx) | p (HAC) | Alpha % (msci) | p (HAC) | Alpha % (spxew) | p (HAC) |
|---|---|---|---|---|---|---|---|
| 2015-2019 2015-01-01 → 2020-01-01 | 0 | — | — | — | — | — | — |
| 2020-2022 2020-01-01 → 2023-01-01 | 3,675 | -1.51% | 0.0042 | -1.52% | 0.0035 | -1.86% | 0.0004 |
| 2023-2026 2023-01-01 → 2099-01-01 | 23,873 | -0.25% | 0.2369 | -0.13% | 0.5503 | +0.27% | 0.2066 |
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
Caution recommended. Bullish 20d alpha is -0.43% and worse than random — triggering on random dates would have produced better long-side returns. Either direction fails the "beats random" test. Don't use Bearish Trend Breakout as a standalone entry trigger. It may still be useful as part of a composite (section 4).
2 · When it works — the setups that drive it
- Best bullish setup: Non-trending + Low vol — alpha -0.04% / 20d on 907 historical triggers.
- Best era for bullish: 2023-2026 — alpha -0.25% / 20d.
3 · When it fails — common false positives
- Weakest bullish cell: Trending + Low vol — alpha -1.26% / 20d on 1,237 triggers.
- Worst era for bullish: 2020-2022 — alpha -1.51% / 20d.
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. A multi-signal convergence backtest is planned but not yet run.
No classical-TA family-redundancy claim applies to this signal. Pairing behaviour is a backtest question and has not been measured yet.
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.
- Fundamental-improvement filter — BTB identifies reversal-attempt candidates. Without fundamentals to distinguish real reversals (earnings improving, revenue reaccelerating, balance sheet repairing) from bear-rally bounces, the signal catches mostly the latter. Required layer: commercial fundamentals feed with rolling EPS revision trend, YoY revenue growth, and debt/cash delta — require all three trending positively alongside the BTB trigger.
- Catalyst confirmation — A 5-year low breakout is more likely real when paired with an identifiable event: new management, divestiture, regulatory approval, major contract, strategic pivot. Catalyst-tagged BTB triggers are plausibly a different population than the no-catalyst ones. Needs a news / event data source layered on top of the technical trigger.
- Peer / sector breadth filter — Isolated reversals inside a still-declining sector rarely stick. Require the stock's sector to also be broadening (>60% of sector members within 10% of their 200DMA) before the BTB trigger counts. This is data we already have via the breadth engine; wiring it into the screen filter layer is implementation work, not a new data source.
- Valuation anchor — Stocks breaking out of multi-year lows AND trading in the cheapest decile of their sector by P/E or P/B are a structurally different bet than those still at premium multiples. Value-anchored BTB triggers would be testable with a fundamentals feed, and would likely cut the sample significantly while improving the alpha profile.
See also Why technical-only signals don't survive on their own for the broader argument.
5 · Before you act — 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? A trend signal is only as credible as the underlying trend it claims to confirm. Check the 200DMA orientation before acting.
- 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 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.
- 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 worst damage IS against cap-weighted SPX. Against equal-weight SPXEW the signal is roughly flat — so if your opportunity cost is a broad equal-weight basket rather than QQQ/SPY, BTB picks are roughly a wash in aggregate. 252d is the horizon with the most extreme SPX underperformance (−7.31%); 20d is closer to breakeven vs SPXEW (−0.02%). Short-horizon tactical trades (1-5 days) are essentially zero alpha. If you must trade BTB triggers, consider tight time stops (exit at 20 sessions) and firm price invalidation (close back below trigger-day low). As a standalone long-only screen it is unlikely to beat a passive equal-weight basket after costs.