+1 sessions
Median return -0.20%Completed observations: 19
- Middle 50%
- -0.99% … +1.02%
- Positive returns
- 47%
Oracle · Sigma Moves
Closed-period price moves, measured against their own history. One engine. Five markets. No forecasts.
Latest closed period
Oracle's latest move against its own history.
ORCL Very rare
-4.18%
-3.31σ
About once every 79 trading sessions
16 comparable moves / 1,257 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 +2.69%Completed observations: 19
- Middle 50%
- -1.68% … +4.00%
- Positive returns
- 63%
+30 sessions
Median return +8.58%Completed observations: 19
- Middle 50%
- +3.21% … +12.40%
- Positive returns
- 79%
Every rare move, in context
Instrument: ORCL (price return)
| Date | σ | Move | Observed rarity | +1 sessions | +7 sessions | +30 sessions |
|---|---|---|---|---|---|---|
| 24 Aug 2023 | -3.31σ | -4.18% | About once every 79 trading sessions16 comparable moves / 1,257 observations | +2.79% | +9.80% | -2.61% |
| 12 Jun 2023 | +3.47σ | +5.99% | About once every 74 trading sessions17 comparable moves / 1,258 observations | +0.21% | +3.56% | -0.80% |
| 25 May 2023 | +4.46σ | +6.07% | About once every 180 trading sessions7 comparable moves / 1,258 observations | -0.20% | +2.69% | +10.15% |
| 23 May 2023 | -2.82σ | -3.17% | About once every 43 trading sessions29 comparable moves / 1,258 observations | -0.22% | +7.46% | +16.31% |
| 10 Mar 2023 | -2.52σ | -3.22% | About once every 31 trading sessions40 comparable moves / 1,258 observations | +1.02% | +4.18% | +13.52% |
| 5 Dec 2022 | -2.94σ | -4.70% | About once every 45 trading sessions28 comparable moves / 1,258 observations | -0.65% | +3.01% | +8.20% |
| 14 Sep 2022 | -3.89σ | -5.16% | About once every 96 trading sessions13 comparable moves / 1,244 observations | -2.61% | -10.50% | +3.74% |
| 14 Jun 2022 | +4.23σ | +10.41% | About once every 118 trading sessions10 comparable moves / 1,181 observations | -1.44% | -0.03% | +8.94% |
| 18 May 2022 | -2.65σ | -4.98% | About once every 35 trading sessions33 comparable moves / 1,163 observations | -1.84% | +6.56% | +3.76% |
| 22 Apr 2022 | -2.82σ | -4.11% | About once every 37 trading sessions31 comparable moves / 1,145 observations | +1.01% | -3.83% | -4.25% |
| 17 Feb 2022 | -2.64σ | -4.62% | About once every 34 trading sessions32 comparable moves / 1,101 observations | -1.27% | +0.64% | +8.58% |
| 10 Dec 2021 | +12.62σ | +15.61% | Not previously observed in 4 years0 comparable moves / 1,054 observations | -1.70% | -10.84% | -21.01% |
| 30 Sep 2021 | -4.32σ | -4.52% | About once every 126 trading sessions8 comparable moves / 1,004 observations | +3.00% | +9.37% | +7.93% |
| 14 Sep 2021 | -3.14σ | -2.81% | About once every 52 trading sessions19 comparable moves / 992 observations | +1.55% | +3.51% | +12.26% |
| 16 Jun 2021 | -4.61σ | -5.59% | About once every 186 trading sessions5 comparable moves / 930 observations | +0.62% | +1.79% | +13.69% |
| 11 Mar 2021 | -3.19σ | -6.53% | About once every 62 trading sessions14 comparable moves / 863 observations | -0.37% | -1.62% | +11.21% |
| 5 Mar 2021 | +4.17σ | +6.65% | About once every 123 trading sessions7 comparable moves / 859 observations | +3.13% | -4.46% | +12.55% |
| 22 Feb 2021 | +4.92σ | +5.43% | 3 times in 3 years3 comparable moves / 850 observations | +0.08% | +3.82% | +15.25% |
| 26 Oct 2020 | -3.82σ | -4.02% | About once every 110 trading sessions7 comparable moves / 770 observations | -0.71% | -1.74% | +2.68% |
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.