+1 sessions
Median return +2.23%Completed observations: 10
- Middle 50%
- +1.55% … +4.03%
- Positive returns
- 80%
AppLovin · Sigma Moves
Closed-period price moves, measured against their own history. One engine. Five markets. No forecasts.
Latest closed period
AppLovin's latest move against its own history.
APP Below threshold
+0.90%
+0.26σ
Common move: this size or larger in 74% of observations
826 comparable moves / 1,123 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 +0.55%Completed observations: 10
- Middle 50%
- -5.15% … +6.03%
- Positive returns
- 60%
+30 sessions
Median return -0.37%Completed observations: 10
- Middle 50%
- -8.20% … +11.15%
- Positive returns
- 50%
Every rare move, in context
Instrument: APP (price return)
| Date | σ | Move | Observed rarity | +1 sessions | +7 sessions | +30 sessions |
|---|---|---|---|---|---|---|
| 6 Aug 2026 | -5.70σ | -19.66% | About once every 216 trading sessions5 comparable moves / 1,080 observations | +3.32% | -7.06% | -8.23% |
| 13 Jul 2026 | -3.16σ | -12.65% | About once every 48 trading sessions22 comparable moves / 1,062 observations | +1.38% | -6.86% | -32.58% |
| 12 Feb 2026 | -3.18σ | -19.68% | About once every 46 trading sessions21 comparable moves / 960 observations | +6.44% | +7.17% | +3.89% |
| 4 Feb 2026 | -3.19σ | -16.12% | About once every 50 trading sessions19 comparable moves / 954 observations | -3.13% | +0.83% | +13.57% |
| 30 Jan 2026 | -5.13σ | -16.89% | About once every 136 trading sessions7 comparable moves / 951 observations | +2.09% | -0.04% | -4.19% |
| 2 Jan 2026 | -2.74σ | -8.24% | About once every 41 trading sessions23 comparable moves / 932 observations | +2.36% | +8.14% | -39.13% |
| 11 Nov 2025 | -2.56σ | -8.66% | About once every 35 trading sessions26 comparable moves / 897 observations | -1.69% | -12.45% | +22.29% |
| 6 Oct 2025 | -4.71σ | -14.03% | About once every 124 trading sessions7 comparable moves / 871 observations | +7.64% | +2.61% | -8.13% |
| 8 Sep 2025 | +3.28σ | +11.59% | About once every 61 trading sessions14 comparable moves / 851 observations | +2.03% | +10.90% | +3.45% |
| 7 Aug 2025 | +3.26σ | +11.97% | About once every 59 trading sessions14 comparable moves / 830 observations | +4.26% | +0.27% | +48.53% |
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.