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iShares Semiconductor ETF · Sigma Moves

Closed-period price moves, measured against their own history. One engine. Five markets. No forecasts.

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Latest closed period

iShares Semiconductor ETF's latest move against its own history.

17 July 2024 · Daily
SOXX Exceptional -7.11% -4.59σ Not previously observed in 5 years 0 comparable moves / 1,258 observations

What happened afterwards

All history-qualified moves of at least 2.5σ. Results after the event are descriptive statistics, not trading instructions.

+1 sessions

Median return -0.02%

Completed observations: 16

Middle 50%
-0.86% … +1.40%
Positive returns
50%

+7 sessions

Median return +1.18%

Completed observations: 16

Middle 50%
-4.74% … +4.26%
Positive returns
50%

+30 sessions

Median return +4.75%

Completed observations: 16

Middle 50%
-3.17% … +10.94%
Positive returns
69%

Every rare move, in context

Instrument: SOXX (price return)

DateσMoveObserved rarity+1 sessions+7 sessions+30 sessions
17 Jul 2024 -4.59σ -7.11% Not previously observed in 5 years0 comparable moves / 1,258 observations +0.30% -5.68% -7.10%
5 Jun 2024 +2.76σ +4.37% About once every 79 trading sessions16 comparable moves / 1,259 observations -0.82% +3.84% -2.59%
22 Feb 2024 +3.12σ +4.93% About once every 126 trading sessions10 comparable moves / 1,258 observations -1.08% +6.70% +3.34%
10 Nov 2023 +2.53σ +4.03% About once every 52 trading sessions24 comparable moves / 1,257 observations -0.97% +3.77% +17.22%
25 Oct 2023 -2.88σ -4.04% About once every 97 trading sessions13 comparable moves / 1,257 observations -0.59% +7.47% +17.08%
26 May 2023 +2.90σ +6.54% About once every 90 trading sessions14 comparable moves / 1,258 observations -0.08% -1.84% +4.98%
25 May 2023 +4.16σ +6.66% 1 times in 5 years1 comparable moves / 1,258 observations +6.54% +4.87% +9.80%
10 Nov 2022 +3.75σ +10.35% 4 times in 5 years4 comparable moves / 1,258 observations +3.06% -0.11% -4.92%
7 Oct 2022 -2.60σ -6.00% About once every 57 trading sessions22 comparable moves / 1,258 observations -3.40% -6.07% +14.38%
13 Sep 2022 -2.80σ -6.21% About once every 83 trading sessions15 comparable moves / 1,243 observations +1.14% -4.43% -6.72%
7 Dec 2021 +3.18σ +5.05% About once every 96 trading sessions11 comparable moves / 1,051 observations -0.65% -6.05% -12.64%
4 Nov 2021 +2.54σ +3.36% About once every 47 trading sessions22 comparable moves / 1,029 observations +1.11% +2.48% +0.99%
28 Sep 2021 -3.47σ -3.91% About once every 167 trading sessions6 comparable moves / 1,002 observations -1.58% -1.11% +15.46%
25 Feb 2021 -2.76σ -5.70% About once every 66 trading sessions13 comparable moves / 853 observations +2.28% -7.95% +9.61%
27 Jan 2021 -3.45σ -5.19% About once every 139 trading sessions6 comparable moves / 833 observations +2.19% +4.05% +4.53%
7 Jan 2021 +3.02σ +3.77% About once every 82 trading sessions10 comparable moves / 820 observations +0.05% +5.38% +5.84%

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.