Mean reversion cci

Commodity Channel Index

CCI = (HLC3 - SMA(HLC3)) / (0.015 * MeanDev(HLC3)). Bullish: CCI crosses above -threshold (leaving oversold). Bearish: CCI crosses below +threshold (leaving overbought).

Signal family

Mean reversion — Oscillator-based signals that fire at overbought or oversold extremes — typically fade the prevailing move.

Parameters

Name Description Default Range
period CCI period 20 5–100
threshold Threshold 100 50–200

Historical context

4,031,287 triggers on 24,246 tickers, 1988-04-08 → 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 Bearish α
5-day -0.11% +0.03%
20-day -0.16% +0.15%
60-day +0.07% +0.47%
1-year +1.43% +2.83%
Random-date null check (20-day): Bullish: worse than random (p=1.000).
Bearish: worse than random (p=1.000).

Where does CCI 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.

Commodity Channel Index (cci) — trigger count distribution by per-stock regime quadrant (trending/non-trending × high/low realized volatility) for bullish and 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.

Commodity Channel Index (cci) — mean 20-day alpha versus S&P 500 Equal Weight by per-stock regime quadrant, bullish and 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.

Commodity Channel Index (cci) — 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 % +0.01% +0.16% +0.99% +2.92% +11.91%
Bench % +0.06% +0.26% +1.17% +2.81% +10.29%
Alpha % -0.06% -0.11% -0.16% +0.07% +1.43%
Median alpha -0.12% -0.32% -0.97% -2.04% -6.90%
Hit rate (α>0) 47.0% 46.5% 45.1% 44.2% 41.4%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 <0.001 <0.001 0.0055 <0.001
N 1,907,198 1,837,656 1,824,776 1,777,851 1,604,449
spx Stock % +0.01% +0.16% +0.99% +2.92% +11.91%
Bench % +0.03% +0.27% +1.36% +3.35% +14.12%
Alpha % -0.04% -0.13% -0.34% -0.45% -2.27%
Median alpha -0.09% -0.36% -1.20% -2.64% -10.76%
Hit rate (α>0) 47.4% 46.1% 43.9% 42.7% 37.4%
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 1,918,030 1,852,353 1,853,132 1,797,529 1,629,945
msci Stock % +0.01% +0.16% +0.99% +2.92% +11.91%
Bench % +0.07% +0.30% +1.20% +2.97% +11.74%
Alpha % -0.07% -0.15% -0.21% -0.06% -0.20%
Median alpha -0.14% -0.39% -1.08% -2.28% -8.55%
Hit rate (α>0) 46.4% 45.8% 44.5% 43.6% 39.7%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 <0.001 <0.001 0.0151 0.1564
N 1,905,920 1,837,883 1,825,413 1,782,977 1,606,960
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.
Commodity Channel Index (cci) — 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 +0.08% +0.08% [+0.08%, +0.08%] 0.910
1d spx +0.09% +0.09% [+0.08%, +0.09%] 0.910
1d msci +0.08% +0.09% [+0.09%, +0.10%] 1.000
5d spxew +0.28% +0.36% [+0.35%, +0.37%] 1.000
5d spx +0.31% +0.37% [+0.36%, +0.38%] 1.000
5d msci +0.29% +0.38% [+0.37%, +0.39%] 1.000
20d spxew +0.98% +1.15% [+1.14%, +1.17%] 1.000
20d spx +1.02% +1.18% [+1.17%, +1.20%] 1.000
20d msci +1.04% +1.20% [+1.18%, +1.21%] 1.000
60d spxew +2.41% +2.47% [+2.44%, +2.50%] 1.000
60d spx +2.63% +2.53% [+2.50%, +2.56%] 0.005
60d msci +2.61% +2.55% [+2.52%, +2.58%] 0.005
252d spxew +4.96% +4.79% [+4.72%, +4.84%] 0.005
252d spx +5.30% +5.13% [+5.06%, +5.18%] 0.005
252d msci +5.13% +5.08% [+5.01%, +5.13%] 0.040

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

Six recent bullish CCI 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 CCI looks like when it works)
Commodity Channel Index (cci) — strongest bullish trigger #1 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window Commodity Channel Index (cci) — strongest bullish trigger #2 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window Commodity Channel Index (cci) — strongest bullish trigger #3 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window
Weakest outcomes (what CCI looks like when it fails)
Commodity Channel Index (cci) — weakest bullish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed Commodity Channel Index (cci) — weakest bullish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed Commodity Channel Index (cci) — weakest bullish trigger #3 on a US mega-cap, showing the 20-day forward window where the signal failed
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 141,103 +0.29% +0.85% -0.50% <0.001 +0.29% +1.08% -0.75% <0.001 +0.29% +0.93% -0.60% <0.001
Trending + High vol Crisis selloff or parabolic rally 650,882 +1.54% +1.33% +0.16% <0.001 +1.54% +1.56% -0.02% 0.2102 +1.54% +1.34% +0.14% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 249,928 +0.31% +0.80% -0.46% <0.001 +0.31% +1.04% -0.71% <0.001 +0.31% +0.92% -0.58% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 933,602 +0.93% +1.16% -0.23% <0.001 +0.93% +1.35% -0.39% <0.001 +0.93% +1.20% -0.29% <0.001
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 → 2020-01-01 601,150 -0.39% <0.001 -0.47% <0.001 -0.27% <0.001
2020-2022 2020-01-01 → 2023-01-01 589,943 -0.38% <0.001 -0.08% <0.001 +0.03% 0.0917
2023-2026 2023-01-01 → 2099-01-01 783,813 +0.21% <0.001 -0.44% <0.001 -0.35% <0.001

↓ Bearish triggers negative alpha = signal was right (stock underperformed market)

Bench Metric 1d 5d 20d 60d 252d
spxew Stock % +0.01% +0.23% +0.83% +2.69% +12.75%
Bench % +0.04% +0.21% +0.74% +2.28% +10.03%
Alpha % -0.04% +0.03% +0.15% +0.47% +2.83%
Median alpha -0.08% -0.25% -0.76% -1.75% -5.74%
Hit rate (α>0) 47.9% 47.3% 46.1% 45.0% 42.7%
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 1,968,940 1,895,319 1,887,942 1,843,619 1,625,651
spx Stock % +0.01% +0.23% +0.83% +2.69% +12.75%
Bench % +0.02% +0.22% +0.93% +3.06% +13.79%
Alpha % -0.01% +0.02% -0.05% -0.35% -1.08%
Median alpha -0.07% -0.27% -1.00% -2.61% -9.77%
Hit rate (α>0) 48.2% 47.0% 44.9% 42.7% 38.2%
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 1,991,110 1,926,333 1,906,751 1,868,433 1,646,663
msci Stock % +0.01% +0.23% +0.83% +2.69% +12.75%
Bench % +0.04% +0.21% +0.82% +2.65% +11.36%
Alpha % -0.03% +0.04% +0.06% +0.09% +1.29%
Median alpha -0.09% -0.26% -0.90% -2.19% -7.38%
Hit rate (α>0) 47.7% 47.2% 45.4% 43.8% 40.9%
p (naive) <0.001 <0.001 <0.001 <0.001 <0.001
p (HAC) <0.001 <0.001 <0.001 0.0027 <0.001
N 1,977,514 1,913,828 1,903,877 1,856,953 1,640,328
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.
Commodity Channel Index (cci) — 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 +0.09% +0.07% [+0.07%, +0.08%] 1.000
1d spx +0.10% +0.08% [+0.08%, +0.09%] 1.000
1d msci +0.11% +0.09% [+0.08%, +0.09%] 1.000
5d spxew +0.38% +0.33% [+0.32%, +0.33%] 1.000
5d spx +0.41% +0.34% [+0.33%, +0.35%] 1.000
5d msci +0.42% +0.35% [+0.34%, +0.36%] 1.000
20d spxew +1.10% +1.06% [+1.04%, +1.08%] 1.000
20d spx +1.13% +1.09% [+1.07%, +1.11%] 1.000
20d msci +1.13% +1.10% [+1.09%, +1.12%] 1.000
60d spxew +2.28% +2.30% [+2.27%, +2.33%] 0.055
60d spx +2.21% +2.37% [+2.34%, +2.40%] 0.005
60d msci +2.23% +2.39% [+2.36%, +2.42%] 0.005
252d spxew +4.44% +4.46% [+4.40%, +4.52%] 0.264
252d spx +4.64% +4.81% [+4.76%, +4.87%] 0.005
252d msci +4.67% +4.76% [+4.71%, +4.82%] 0.005

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

Six recent bearish CCI 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 CCI looks like when it works)
Commodity Channel Index (cci) — strongest bearish trigger #1 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window Commodity Channel Index (cci) — strongest bearish trigger #2 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window Commodity Channel Index (cci) — strongest bearish trigger #3 on a US mega-cap, showing the stock's OHLC candles, moving averages, signal-specific overlays, and the 20-day forward window
Weakest outcomes (what CCI looks like when it fails)
Commodity Channel Index (cci) — weakest bearish trigger #1 on a US mega-cap, showing the 20-day forward window where the signal failed Commodity Channel Index (cci) — weakest bearish trigger #2 on a US mega-cap, showing the 20-day forward window where the signal failed Commodity Channel Index (cci) — weakest bearish trigger #3 on a US mega-cap, showing the 20-day forward window where the signal failed
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 174,695 +0.50% +0.41% +0.12% <0.001 +0.50% +0.72% -0.20% <0.001 +0.50% +0.57% -0.05% 0.0139
Trending + High vol Crisis selloff or parabolic rally 822,005 +1.06% +0.73% +0.40% <0.001 +1.06% +0.96% +0.15% <0.001 +1.06% +0.83% +0.28% <0.001
Non-trending + Low vol Quiet chop, summer doldrums 253,820 +0.48% +0.53% -0.01% 0.4378 +0.48% +0.78% -0.27% <0.001 +0.48% +0.64% -0.13% <0.001
Non-trending + High vol Classical "whipsaw zone" for momentum 805,246 +0.84% +0.88% -0.01% 0.5512 +0.84% +0.99% -0.12% <0.001 +0.84% +0.92% -0.04% 0.0369
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 → 2020-01-01 623,605 -0.32% <0.001 -0.56% <0.001 -0.36% <0.001
2020-2022 2020-01-01 → 2023-01-01 607,741 +0.13% <0.001 +0.38% <0.001 +0.48% <0.001
2023-2026 2023-01-01 → 2099-01-01 823,869 +0.54% <0.001 +0.03% 0.1666 +0.09% <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 -0.16% — worse than random : firing on random dates would have done better. Bearish 20d alpha is +0.15% — 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 bullish setup: Trending + High vol — alpha +0.16% / 20d on 650,882 historical triggers.
  • Best bearish setup: Non-trending + Low vol — alpha -0.01% / 20d on 253,820 historical triggers.
  • Best era for bullish: 2023-2026 — alpha +0.21% / 20d on 783,813 triggers.
  • Best era for bearish: 2015-2019 — alpha -0.32% / 20d on 623,605 triggers.

3 · When it fails — common false positives

  • Weakest bullish cell: Trending + Low vol — alpha -0.50% / 20d on 141,103 triggers.
  • Weakest bearish cell: Trending + High vol — alpha +0.40% / 20d on 822,005 triggers.
  • Worst era for bullish: 2015-2019 — alpha -0.39% / 20d on 601,150 triggers.
  • Worst era for bearish: 2023-2026 — alpha +0.54% / 20d on 823,869 triggers.

Signal-specific failure patterns

±100 crossings are routine by construction — each fire carries less information
Lambert's 0.015 scaling constant was chosen so that roughly 70-80% of CCI values fall inside the ±100 band, which makes excursions beyond the thresholds — and the crosses back through them that fire this signal — ordinary events rather than rare extremes. A 20-period CCI on the typical price ((high + low + close) / 3) fires far more often than a comparable RSI 30/70 cross. Treat a single CCI fire as one weak vote, best AND-composed with other dimensions in a report rather than used standalone. The permutation-null line above tells you whether the aggregate of those votes currently beats random dates.
Bullish fires select recent losers
The bullish trigger is CCI crossing back above -100 from below, meaning the typical price has spent recent sessions well beneath its 20-day mean. As with the other mean-reversion oscillators, that pool skews toward names falling for identifiable reasons, and in markets with narrow leadership the anticipated snap-back frequently fails to complete. The at-a-glance table and sub-period breakdown above show how this side is scoring in the current data.
Trend embedding produces premature bearish fires
In a strong advance CCI can hold above +100 for extended stretches and re-enter the band repeatedly. The bearish fire — CCI crossing back below +100 from above — therefore often marks a pause in a working trend rather than a top, the same structural weakness as RSI's exit-from-overbought cross. Whether the bearish side nonetheless clears the random-date null right now is a question for the permutation line above, not for the mechanics.

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.

Oscillator-family redundancy

CCI belongs to the momentum-oscillator family alongside RSI, Stochastics, and Williams %R — each is a short-lookback price oscillator read against reference bands (their constructions differ — CCI scales typical price (H+L+C)/3 around its own mean and is unbounded, RSI smooths close-to-close changes into a 0-100 scale, Stochastics and Williams %R place the close inside the recent high-low range — but they respond to the same underlying move) (Murphy, Technical Analysis of the Financial Markets, 1999; Pring, Technical Analysis Explained, 5th ed. 2014; Kirkpatrick & Dahlquist, Technical Analysis, 3rd ed. 2015). Stacking two or more of these in the same direction within a single Daily Report produces correlated rather than independent evidence.

Measured pairings — Bonferroni survivors

Beyond the literature pairings above, these are the same-day co-fire combinations involving Commodity Channel Index 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 — 3 of the 24 rows below do 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
cci bullish + stochastics bullish +0.30% +0.45% 18,538 0.002

1 of this universe's 18 surviving pairs involves this signal · α vs ^SPXEW.

Europe — 5 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
cci bearish + rsi bearish +0.60% +0.77% 3,073 0.002
cci bearish + vwap_cross bearish +0.46% +0.42% 3,165 0.010
cci bearish + williams_r bearish +0.33% +0.35% 11,506 0.002
cci bearish + stochastics bearish +0.37% +0.34% 6,544 0.002
cci bullish + williams_r bullish +0.35% +0.08% 9,070 0.321

5 of this universe's 20 surviving pairs involve this signal · α vs ^STOXX.

Hong Kong — 1 surviving pair
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
cci bearish + williams_r bearish +0.58% +0.86% 3,398 0.002

1 of this universe's 23 surviving pairs involves this signal · α vs ^HSI.

China A-shares — 17 surviving pairs
Pair (same-day co-fire, long) Full α Test α (2023+) Test N p_perm test
cci bearish + hh_hl_streak bearish +2.53% +4.75% 4,169 0.002
cci bullish + weekly_change bearish +2.67% +3.62% 1,244 0.002
cci bullish + rsi bullish +2.33% +3.00% 7,856 0.002
cci bearish + ma_crossover bullish +1.65% +2.10% 743 0.002
cci bearish + new_20d_low bearish +0.96% +1.47% 881 0.002
bollinger bullish + cci bullish +1.24% +1.38% 4,902 0.002
cci bullish + macd bullish +0.74% +1.01% 9,273 0.002
cci bearish + rsi bearish +0.88% +0.92% 8,915 0.002
cci bullish + hh_hl_streak bullish +2.01% +0.68% 1,787 0.040
cci bullish + williams_r bullish +0.48% +0.67% 55,921 0.002
cci bearish + williams_r bearish +0.35% +0.62% 40,420 0.002
cci bullish + stochastics bullish +0.35% +0.56% 35,021 0.002
cci bearish + stochastics bearish +0.22% +0.47% 25,460 0.002
cci bullish + vwap_cross bullish +0.32% +0.38% 13,463 0.002
cci bearish + volume_breakout bearish -0.90% -0.26% 5,895 0.140
cci bearish + volume_breakout bullish -2.10% -0.58% 330 0.475
cci bullish + williams_r bearish -4.02% — — —

17 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.

  • Regime-gate bullish on breadth — Bullish CCI is a bet that beaten-down typical prices revert, which historically depends on how broad market participation is. Gating bullish fires on a breadth threshold, or on the benchmark trading some distance below its high, is a testable refinement — check the sub-period breakdown above for whether the current data motivates it.
  • Let the table set the bearish hold — Compare the 20d and 60d columns in the current tables before choosing exits. Alpha that builds with horizon argues for time-stops over profit targets; flat or reversing columns argue for shorter holds. Because CCI fires frequently, per-fire position sizing matters more than for rarer signals — its triggers are many small correlated bets, not a few independent ones.

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? A mean-reversion signal firing against the long-term trend (e.g. oversold in a clean uptrend) is much more reliable than one firing with it.
  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

Entry convention in the tables above is next-day open (open T+1). CCI here is Lambert's original 1980 construction: (typical price minus its 20-day simple moving average) / (0.015 × mean deviation), with thresholds at ±100. Under the single-sided long convention used in the tables, a bearish fire 'works' when post-trigger alpha is negative — the stock lags the benchmark after firing. Take direction from the current data: a side that clears the random-date permutation null can serve as a screen tile in that direction; a side that does not is context, not a trade prompt. Historical tendency, not a recommendation.