+1 sessions
Median return -1.42%Completed observations: 22
- Middle 50%
- -2.91% … +0.72%
- Positive returns
- 36%
Datadog · Sigma Moves
Closed-period price moves, measured against their own history. One engine. Five markets. No forecasts.
Latest closed period
Datadog's latest move against its own history.
DDOG Rare
-11.28%
-2.77σ
About once every 52 trading sessions
24 comparable moves / 1,255 observations
What happened afterwards
All history-qualified moves of at least 2.5σ. Results after the event are descriptive statistics, not trading instructions.
+7 sessions
Median return -1.53%Completed observations: 22
- Middle 50%
- -8.23% … +3.82%
- Positive returns
- 41%
+30 sessions
Median return -1.42%Completed observations: 22
- Middle 50%
- -9.64% … +13.33%
- Positive returns
- 50%
Every rare move, in context
Instrument: DDOG (price return)
| Date | σ | Move | Observed rarity | +1 sessions | +7 sessions | +30 sessions |
|---|---|---|---|---|---|---|
| 23 Feb 2026 | -2.77σ | -11.28% | About once every 52 trading sessions24 comparable moves / 1,255 observations | +1.77% | +15.31% | +13.57% |
| 10 Feb 2026 | +3.09σ | +13.74% | About once every 84 trading sessions15 comparable moves / 1,255 observations | -1.80% | -10.80% | -4.92% |
| 29 Jan 2026 | -2.95σ | -8.81% | About once every 74 trading sessions17 comparable moves / 1,255 observations | +0.89% | -11.05% | -2.86% |
| 8 Jan 2026 | -3.25σ | -7.61% | About once every 97 trading sessions13 comparable moves / 1,255 observations | -3.97% | -10.47% | -21.48% |
| 6 Nov 2025 | +8.81σ | +23.13% | 2 times in 5 years2 comparable moves / 1,255 observations | +0.22% | -5.53% | -26.43% |
| 1 Oct 2025 | +3.08σ | +7.23% | About once every 97 trading sessions13 comparable moves / 1,255 observations | -0.74% | +3.96% | +25.01% |
| 28 Aug 2025 | +2.67σ | +7.01% | About once every 52 trading sessions24 comparable moves / 1,240 observations | -3.04% | -0.35% | +12.61% |
| 3 Jul 2025 | +7.29σ | +14.92% | 2 times in 5 years2 comparable moves / 1,201 observations | -1.77% | -9.40% | -17.98% |
| 9 Apr 2025 | +3.41σ | +12.00% | About once every 114 trading sessions10 comparable moves / 1,143 observations | -4.37% | -8.74% | +18.71% |
| 3 Apr 2025 | -2.78σ | -7.12% | About once every 67 trading sessions17 comparable moves / 1,139 observations | -6.92% | -2.74% | +24.56% |
| 10 Mar 2025 | -2.86σ | -7.28% | About once every 75 trading sessions15 comparable moves / 1,121 observations | +0.30% | +2.73% | -10.06% |
| 13 Feb 2025 | -3.95σ | -8.24% | About once every 221 trading sessions5 comparable moves / 1,105 observations | -3.59% | -15.39% | -25.60% |
| 28 Jan 2025 | +3.58σ | +6.84% | About once every 137 trading sessions8 comparable moves / 1,093 observations | -4.06% | -4.63% | -32.83% |
| 22 Nov 2024 | +2.58σ | +7.63% | About once every 50 trading sessions21 comparable moves / 1,051 observations | +1.16% | +7.14% | -8.36% |
| 19 Nov 2024 | +2.60σ | +5.91% | About once every 52 trading sessions20 comparable moves / 1,048 observations | +1.53% | +14.50% | +8.56% |
| 4 Oct 2024 | +2.69σ | +4.39% | About once every 60 trading sessions17 comparable moves / 1,016 observations | -0.25% | +3.42% | +2.77% |
| 17 Jul 2024 | -3.74σ | -7.35% | About once every 160 trading sessions6 comparable moves / 960 observations | -1.93% | -2.35% | -6.39% |
| 7 May 2024 | -5.74σ | -11.48% | 3 times in 4 years3 comparable moves / 912 observations | +4.34% | +7.30% | +3.27% |
| 11 Apr 2024 | +2.51σ | +3.96% | About once every 50 trading sessions18 comparable moves / 894 observations | -2.52% | -6.67% | -6.64% |
| 5 Mar 2024 | -2.65σ | -5.46% | About once every 58 trading sessions15 comparable moves / 868 observations | +0.86% | -0.71% | +0.02% |
| 7 Nov 2023 | +9.36σ | +28.47% | Not previously observed in 3 years0 comparable moves / 788 observations | -2.16% | +6.77% | +18.02% |
| 25 Oct 2023 | -3.03σ | -7.14% | About once every 111 trading sessions7 comparable moves / 779 observations | -1.07% | +0.55% | +40.95% |
The number has a method behind it
Sigma measures the size of a log return relative to volatility estimated before the period. Rarity is counted from actual historical standardized moves, not inferred from a normal distribution.
σt = ln(Ct / Ct−1) / vtvt ← t−1, t−2, …
Volatility adapts to the market regime with EWMA (λ = 0.94 for daily and weekly observations). Current-period returns are excluded. Each historical σ uses its own prior volatility.
Both directions count toward rarity. Reference history spans up to five years. A period with no prior exceedances is labelled unprecedented in the observed sample; it is never given an invented recurrence interval.
Stock observations use split-adjusted price returns, without dividend reinvestment. Commodities are explicitly labelled ETF price proxies; they do not represent spot commodity prices.
Questions behind the sigma
What does a 3σ move mean?
The period log return is three times the volatility estimated from earlier periods. Sigma is signed: negative for declines and positive for rises.
Why not calculate rarity from a normal distribution?
Market returns have heavy tails and changing volatility. We count actual past absolute sigma exceedances for the same instrument and period.
Does “once every 200 days” predict the next event?
No. It is the number of historical observed periods divided by comparable moves. Events can cluster and the market regime can change.
How much history is required?
At least three years of valid standardized observations, after a one-year volatility warm-up. This normally requires approximately four years of source history.
Are all instruments directly comparable?
The engine is shared, but each instrument has its own prices, calendar, volatility and reference sample. Commodity cards use explicitly labelled ETF proxies.
What happens on quiet days?
The page shows the largest covered standardized move, the complete rarity scale and recent records. Missing data is reported separately from market calm.
For information only. Historical observations are not investment advice and do not predict future moves. A rare move can be followed by another rare move.