+1 sessions
Median return +0.45%Completed observations: 21
- Middle 50%
- -0.75% … +2.00%
- Positive returns
- 57%
Vertiv · Sigma Moves
Closed-period price moves, measured against their own history. One engine. Five markets. No forecasts.
Latest closed period
Vertiv's latest move against its own history.
VRT Below threshold
-2.63%
-0.79σ
Common move: this size or larger in 38% of observations
474 comparable moves / 1,254 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 +3.09%Completed observations: 21
- Middle 50%
- -5.14% … +15.37%
- Positive returns
- 57%
+30 sessions
Median return +12.30%Completed observations: 20
- Middle 50%
- -1.28% … +31.35%
- Positive returns
- 65%
Every rare move, in context
Instrument: VRT (price return)
| Date | σ | Move | Observed rarity | +1 sessions | +7 sessions | +30 sessions |
|---|---|---|---|---|---|---|
| 9 Sep 2026 | -2.58σ | -9.61% | About once every 63 trading sessions20 comparable moves / 1,254 observations | -5.61% | -5.14% | — |
| 29 Jul 2026 | -4.65σ | -17.26% | About once every 209 trading sessions6 comparable moves / 1,254 observations | +2.00% | +22.13% | +11.25% |
| 23 Jun 2026 | -2.83σ | -11.07% | About once every 84 trading sessions15 comparable moves / 1,254 observations | -0.59% | -5.59% | -12.69% |
| 11 Feb 2026 | +6.09σ | +24.49% | 4 times in 5 years4 comparable moves / 1,255 observations | -4.83% | -1.24% | +1.57% |
| 6 Feb 2026 | +3.20σ | +10.03% | About once every 114 trading sessions11 comparable moves / 1,255 observations | +3.28% | +24.35% | +30.89% |
| 12 Dec 2025 | -3.24σ | -9.73% | About once every 114 trading sessions11 comparable moves / 1,255 observations | +0.29% | +3.09% | +20.15% |
| 10 Sep 2025 | +3.39σ | +8.89% | About once every 157 trading sessions8 comparable moves / 1,255 observations | -0.75% | +5.02% | +25.49% |
| 27 Jan 2025 | -10.13σ | -29.88% | 2 times in 5 years2 comparable moves / 1,257 observations | +3.85% | +16.02% | -18.99% |
| 19 Nov 2024 | +4.95σ | +14.57% | About once every 210 trading sessions6 comparable moves / 1,258 observations | -2.41% | -9.47% | -10.83% |
| 3 Sep 2024 | -2.72σ | -9.43% | About once every 55 trading sessions23 comparable moves / 1,258 observations | -0.19% | +15.37% | +42.91% |
| 24 Jul 2024 | -4.05σ | -13.64% | About once every 125 trading sessions10 comparable moves / 1,249 observations | -2.68% | -11.62% | -4.38% |
| 17 Jul 2024 | -2.95σ | -8.85% | About once every 62 trading sessions20 comparable moves / 1,244 observations | +0.95% | -5.70% | -1.54% |
| 6 Jun 2024 | -2.82σ | -9.35% | About once every 61 trading sessions20 comparable moves / 1,217 observations | -0.36% | +1.76% | -0.17% |
| 19 Apr 2024 | -2.55σ | -7.41% | About once every 46 trading sessions26 comparable moves / 1,184 observations | +1.41% | +23.98% | +28.13% |
| 2 Aug 2023 | +12.21σ | +29.25% | 1 times in 4 years1 comparable moves / 1,004 observations | +0.61% | -2.27% | +12.10% |
| 25 May 2023 | +4.29σ | +13.98% | About once every 120 trading sessions8 comparable moves / 958 observations | +6.65% | +8.05% | +36.74% |
| 26 Apr 2023 | +3.74σ | +11.12% | About once every 94 trading sessions10 comparable moves / 937 observations | +6.62% | +10.23% | +51.43% |
| 29 Dec 2022 | +3.12σ | +9.55% | About once every 61 trading sessions14 comparable moves / 857 observations | +0.96% | +7.32% | +12.49% |
| 3 Oct 2022 | +3.24σ | +15.74% | About once every 66 trading sessions12 comparable moves / 796 observations | +6.31% | -3.02% | +32.71% |
| 23 Sep 2022 | -2.61σ | -9.79% | About once every 44 trading sessions18 comparable moves / 790 observations | -1.61% | +20.20% | +42.51% |
| 9 Sep 2022 | +2.58σ | +9.32% | About once every 43 trading sessions18 comparable moves / 780 observations | +0.45% | -8.75% | -1.20% |
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.