Trend turnaround_cross

Turnaround Cross

A stock that has fallen a long way finally turns up. The short-term trend crosses above the long-term trend while the stock is still far below its multi-year peak, and the turn arrives with real momentum rather than a drift. Ordinary trend crossovers fire on anything resuming an uptrend; this one only fires on a recovery from a deep decline, so it is rare.

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
depth_ratio Depth: SMA200 at most this share of its 3y peak 0.7 0.3–0.95
thrust_pct Thrust: SMA50 rise over the window 0.12 0.02–0.4
thrust_window Thrust window (days) 20 5–60

Historical context

13,491 triggers on 8,769 tickers, 2001-02-13 → 2026-09-07. 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 -0.02%
20-day +0.55%
60-day +1.41%
1-year +19.22%
Random-date null check (20-day): Bullish: beats random (p=0.005)

Turnaround Cross is a single-direction signal — only the bullish side is meaningful.

Where does TURNAROUND_CROSS 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.

Turnaround Cross (turnaround_cross) — 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. This is the 20-day alpha a trade taken on the trigger would have captured. This signal is bullish-only, so positive bars mark the regimes where it worked and negative 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.

Turnaround Cross (turnaround_cross) — 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 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. Long-history signal: requires 956 trading days of prior data per ticker. The earliest era may show fewer triggers as a result.

Turnaround Cross (turnaround_cross) — 20-day alpha split by historical sub-period (2015-2019, 2020-2022, 2023+) to check consistency across market regimes

Longer-horizon views

This signal carries a long lookback window (956 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, showing how the signal's relationship with the benchmark evolves with holding period.

60-day alpha by stock regime

Turnaround Cross (turnaround_cross) — mean 60-day alpha versus S&P 500 Equal Weight by per-stock regime quadrant

60-day alpha by era

Turnaround Cross (turnaround_cross) — 60-day alpha split by historical sub-period

1-year alpha by stock regime

Turnaround Cross (turnaround_cross) — mean 1-year (252 trading day) alpha versus S&P 500 Equal Weight by per-stock regime quadrant

1-year alpha by era

Turnaround Cross (turnaround_cross) — 1-year alpha split by historical sub-period

1-year observed lift vs random-date null — bullish side

Observed 1-year 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.
Turnaround Cross (turnaround_cross) — bullish 1-year observed lift versus the random-date permutation null distribution

↑ Bullish triggers

Bench Metric 1d 5d 20d 60d 252d
spxew Stock % -0.03% +0.25% +1.21% +6.90% +34.08%
Bench % +0.05% +0.23% +0.88% +2.40% +13.54%
Alpha % -0.14% -0.02% +0.55% +1.41% +19.22%
Median alpha -0.27% -0.64% -1.99% -4.81% -4.17%
Hit rate (α>0) 45.7% 45.9% 43.8% 41.8% 46.7%
p (naive) 0.0044 0.8581 0.0199 0.0005 <0.001
p (HAC) 0.0058 0.8738 0.0922 0.0837 <0.001
N 7,228 7,001 6,939 6,864 6,444
spx Stock % -0.03% +0.25% +1.21% +6.90% +34.08%
Bench % +0.03% +0.34% +1.34% +3.45% +17.26%
Alpha % -0.11% -0.12% -0.02% +0.28% +15.07%
Median alpha -0.24% -0.72% -2.53% -5.84% -8.92%
Hit rate (α>0) 46.0% 45.4% 42.4% 40.3% 43.4%
p (naive) 0.0213 0.3143 0.9427 0.4958 <0.001
p (HAC) 0.0248 0.3716 0.9585 0.7521 0.0009
N 7,277 7,080 7,026 6,923 6,503
msci Stock % -0.03% +0.25% +1.21% +6.90% +34.08%
Bench % +0.05% +0.30% +1.16% +3.03% +15.19%
Alpha % -0.12% -0.08% +0.17% +0.73% +17.14%
Median alpha -0.27% -0.72% -2.35% -5.53% -6.90%
Hit rate (α>0) 45.9% 45.6% 42.9% 41.0% 44.8%
p (naive) 0.0077 0.4760 0.4519 0.0692 <0.001
p (HAC) 0.0094 0.5216 0.5808 0.3940 <0.001
N 7,294 7,102 7,048 6,944 6,523
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.
Turnaround Cross (turnaround_cross) — 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 +0.05% +0.11% [+0.03%, +0.18%] 0.950
1d spx +0.05% +0.12% [+0.04%, +0.20%] 0.950
1d msci +0.06% +0.12% [+0.04%, +0.19%] 0.930
5d spxew +0.63% +0.53% [+0.36%, +0.73%] 0.169
5d spx +0.56% +0.54% [+0.37%, +0.75%] 0.393
5d msci +0.59% +0.55% [+0.38%, +0.75%] 0.313
20d spxew +2.25% +1.74% [+1.38%, +2.06%] 0.005
20d spx +1.90% +1.76% [+1.41%, +2.06%] 0.299
20d msci +1.96% +1.78% [+1.43%, +2.09%] 0.199
60d spxew +4.90% +3.99% [+3.42%, +4.59%] 0.005
60d spx +4.46% +4.03% [+3.51%, +4.61%] 0.090
60d msci +4.39% +4.05% [+3.47%, +4.60%] 0.124
252d spxew +16.78% +7.68% [+6.69%, +8.75%] 0.005
252d spx +16.31% +7.94% [+6.98%, +9.06%] 0.005
252d msci +15.66% +7.78% [+6.87%, +8.80%] 0.005

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

Six recent bullish TURNAROUND_CROSS 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)
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 133 +0.08% +1.76% +1.00% 0.5455 +0.08% +1.85% +0.81% 0.5608 +0.08% +1.79% +0.86% 0.5477
Trending + High vol Crisis selloff or parabolic rally 11,175 +1.23% +0.85% +0.59% 0.0939 +1.23% +1.34% +0.00% 0.9958 +1.23% +1.17% +0.20% 0.5511
Non-trending + Low vol Quiet chop, summer doldrums 19 -2.61% +2.60% -5.49% -2.61% +2.23% -5.12% -2.61% +2.72% -5.61%
Non-trending + High vol Classical "whipsaw zone" for momentum 2,164 +1.23% +0.93% +0.28% 0.7086 +1.23% +1.25% -0.17% 0.8240 +1.23% +1.07% -0.06% 0.9403
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 1,976 -1.58% 0.0231 -1.84% 0.0089 -1.59% 0.0213
2020-2022 2020-01-01 → 2023-01-01 2,190 +1.41% 0.0064 +1.33% 0.0097 +1.47% 0.0030
2023-2026 2023-01-01 → 2099-01-01 3,304 +1.19% 0.0140 +0.20% 0.6676 +0.39% 0.4067

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

Use Turnaround Cross bullish as a long-side screening tile. Bullish 20d alpha is +0.55% and beats random (permutation test, 200 iterations). This signal fires bullish-only — there is no bearish variant.

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 bullish setup: Trending + High vol — alpha +0.59% / 20d on 11,175 historical triggers.
  • Best era for bullish: 2020-2022 — alpha +1.41% / 20d on 2,190 triggers.

3 · When it fails — common false positives

  • Weakest bullish cell: Non-trending + High vol — alpha +0.28% / 20d on 2,164 triggers.
  • Worst era for bullish: 2015-2019 — alpha -1.58% / 20d on 1,976 triggers.

Signal-specific failure patterns

Most triggers never produce the big move
Two different questions are answered on this page and they give different numbers. Beating the index: 46.7% of triggers did so over one year - the hit-rate row in the table above. Doubling: the research study asked whether price ever reached twice the trigger level within two years, and 33.0% did in the held-out window against a 26.24% rate for the pool. Doubling is the test this signal was selected on, and two thirds of triggers fail it. Neither number is close to a majority, so this is not a high-accuracy signal and should not be sized as one.
The edge is a tail, not a typical outcome
The measured advantage lives in the right tail, not in the median trigger. Against the equal-weight benchmark the median alpha is negative at every horizon (-1.99% at 20 days, -4.81% at 60, -4.17% at 252) and fewer than half of triggers beat the benchmark at any horizon. The only large positive is the 252-day mean, +19.22%, which a small number of very large winners carries. Part of that is the universe rather than the signal: buying the same stocks on random days, matched year for year to when this signal actually fired, returns +7.49% over the same horizon, so the genuine excess is +11.74 points, not +19.22. Note also that over 1 to 3 months this signal picks winners LESS often than those random dates do (-1.3 points at 20 days, -2.6 at 60); it makes its return on the size of the winners, not their frequency. Read these numbers as skew, not as expected return, and size accordingly.
Rare by construction, and slow to arm
The signal needs roughly 956 trading sessions of history before it can fire at all, because the 200-day average must itself have a 756-session maximum to be measured against. Recent listings, recent re-listings and names with gappy history will never trigger regardless of their chart. Absence of a trigger is often absence of history, not absence of the pattern.
Production universe is wider than the tested universe
The measured numbers come from a research study run on 29,231 tickers with a point-in-time liquidity gate of $10M/day and known data-defect names excluded. Production applies neither filter: the screen runs on the full active universe, so it will fire on illiquid and defect-prone names the study never measured. Treat a fire on a thinly traded name as outside the tested set.

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. This signal was not part of the tested set in the pair backtest run, so its pairing behaviour remains unmeasured.

Position in the multi-year range

In the study, requiring price to sit in the bottom third of its 5-year range at the trigger improved the result consistently, and depth-as-position-in-range beat its no-depth control monotonically across every window tested. This is not applied automatically by the screen. If you want it, add a range filter to the report or check the chart before acting.

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.

  • Treat it as a candidate generator, not an entryA 33% doubling rate over two years is a shortlist, not a trade. The useful workflow is to let the signal surface deeply depressed names that have started to turn, then apply separate fundamental or catalyst work before committing.
  • Check liquidity before actingBecause production does not apply the study's $10M/day liquidity gate, sort or filter the report by turnover. Triggers on names below that level are outside the measured set and carry execution risk on top of signal risk.

See also Why technical-only signals don't survive on their own for the broader argument.

5 · Before acting — 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? A trend signal is only as credible as the underlying trend it claims to confirm. Check the 200DMA orientation before acting.
  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 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.
  5. 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

Long-only: the signal has no bearish side. It fires when the 50-day average crosses above the 200-day while the 200-day is still at or below 0.70x its own 756-session maximum, and the 50-day has risen at least 12% over the preceding 20 sessions - that is, a cross that arrives with thrust rather than drift, on a stock still far below its multi-year peak. The 12% thrust threshold was swept and sits on a smooth plateau (neighbour gap 0.012 lift, rank correlation 1.00 between windows), so it is not a fitted spike. It is also deliberately conservative: lift kept rising past it in the selection window, but the held-out window peaked around 0.15 and the hit rate moved the wrong way out-of-sample, so the threshold was not pushed further.