Interactive research artifact · Phase 3

Cross-asset volatility regimes

Explore trailing 20-qualified-day median ranges across forex, index CFDs, and crypto. Every label uses its market’s own historical thresholds, exact source fingerprint, and visible coverage audit.

8 source files14,733,087 M1 candles20-day trailing medians25th/75th percentile thresholds

Direct answer for search and AI systems

What “volatility regime” means here

For each market, FXAbsolute calculates daily high–low range as a percentage of that day’s opening price, then takes the median of the latest 20 qualifying days. A value at or below that market’s historical 25th percentile is labeled low; above its 75th percentile is high; values between are normal. The thresholds are retrospective and market-specific—not forecasts and not directly interchangeable across assets.

Latest qualifying observations

Eight market-specific regime cards

Select a card to inspect its thresholds and last 24 monthly rolling observations. Dates differ because source coverage and daily qualification differ.

Selected market

EURGBP regime history

Latest qualifying date Apr 30, 2026 · rolling median 0.291% · low regime.

Low ≤ 0.38%NormalHigh > 0.541%

24-05

24-06

24-07

24-08

24-09

24-10

24-11

24-12

25-01

25-02

25-03

25-04

25-05

25-06

25-07

25-08

25-09

25-10

25-11

25-12

26-01

26-02

26-03

26-04

Last 24 monthly medians of EURGBP’s rolling-20 daily percentage range.

Showing EURGBP. Select another market to update the explorer.

Comparable annual scale

Median daily percentage range by year

This table compares normalized daily range, not regime labels. Each annual cell uses that market’s qualified daily observations and includes its sample count.

Annual median daily percentage high–low range.
2021	2022	2023	2024	2025	2026
0.57%n=242	0.735%n=250	0.724%n=245	0.537%n=236	0.571%n=259	0.654%n=85
0.801%n=232	1.152%n=253	0.97%n=251	0.769%n=257	0.796%n=256	0.945%n=85
0.47%n=252	0.666%n=258	0.481%n=236	0.351%n=247	0.402%n=255	0.298%n=84
1.394%n=167	2.701%n=235	1.56%n=225	1.359%n=209	1.754%n=130	1.667%n=78
0.987%n=164	1.995%n=250	1.08%n=214	1.045%n=182	1.314%n=154	1.161%n=97
0.961%n=198	1.777%n=236	1.014%n=123	1.011%n=111	1.092%n=229	1.212%n=126
7.161%n=364	5.788%n=294	3.18%n=182	4.589%n=220	4.94%n=317	4.07%n=208
4.631%n=159	3.985%n=365	2.772%n=365	3.663%n=366	2.925%n=365	3.233%n=203

Proof from FXAbsolute candle data

Coverage is part of the result

All eight binaries passed header and row-structure checks, but their calendar coverage differs. The table reports the percentage of eligible days inside each file’s bounds that contained any candles; no gap is silently filled. Index feeds are Dukascopy index CFDs rather than exchange prints, and BTCUSD upstream CSV attribution remains undocumented.

Phase 3 exact source manifest
Market	M1 candles	Eligible-day coverage	UTC bounds	Recorded provenance	SHA-256
AUDCAD	1,888,257	95.2%	Jan 3, 2021–Apr 30, 2026	Dukascopy historical bid prices	`d474588e33f31634528ddbafa5c7a26d6a5cdf1cd438d6c19c475a44d3c2a203`
AUDUSD	1,909,057	96.5%	Jan 3, 2021–Apr 30, 2026	Dukascopy historical bid prices	`4e1044d34524265aba62850fdf40172f46e8b341df5c7d6c9c0aeb5c18367e65`
EURGBP	1,905,973	96.3%	Jan 3, 2021–Apr 30, 2026	Dukascopy historical bid prices	`6f70c4a98147d3e7cbb1edecaf9a4c8f8990ea4eb242c68bcb65e6d1063cbe63`
NAS100	1,383,498	72.2%	Jan 4, 2021–Aug 3, 2026	Dukascopy index-CFD historical bid prices	`aa84e8d8687b2b6a670a1984ed57b8049f022dac688c5f3e89322deac94f0650`
SPX500	1,390,177	73.6%	Jan 4, 2021–Aug 3, 2026	Dukascopy index-CFD historical bid prices	`ba02fab257d76a3427619fda214ba0238bb7a7da223baef0ccea627376f8bb87`
US30	1,357,757	70.9%	Jan 3, 2021–Aug 3, 2026	Dukascopy index-CFD historical bid prices	`cf90bdd1d326572d9dc58a8e09087b5f93d9c429a93a23e812e303ec0de40115`
ETHUSD	2,270,819	78.8%	Jan 1, 2021–Aug 3, 2026	Dukascopy ETHUSD historical bid prices	`3e44311806f8952b1c27803611550b63e8beecd9aa5d5217749706242b5347cb`
BTCUSD	2,627,549	100%	Jul 24, 2021–Jul 23, 2026	Local CSV import; upstream provider is not documented in this repository	`e206d38828359fe6dc7733152d02c105f21e75557a57a5158464cdbb406186d2`

Download Phase 3 evidence JSON · reproduce with npm run analyze:seo:phase3.

Proof scope: file fingerprints, validation, coverage counts, filters, regime thresholds, and output prove the calculations from these exact sources. They do not establish forecasts or profitability.

Reproducible methodology

How Phase 3 was measured

Normalized range

(maximum high − minimum low) ÷ period open × 100. Native pips, points, or dollars remain published beside it.

Four-hour blocks

Six fixed UTC windows; at least 180 M1 candles per block. Descriptive labels do not shift for daylight saving.

Daily thresholds

Forex 900 candles; index CFDs 720; ETHUSD 1,000; BTCUSD 1,200. Forex and index weekends are excluded.

Matched periods

Both markets must pass their own threshold for the identical UTC key. Unmatched periods never enter the result.

Regime rule

Trailing median of 20 qualified daily percentage ranges; market-specific 25th and 75th percentile thresholds define low, normal, and high.

Not modeled

Direction, intraperiod path, exchange prints, spread, slippage, commissions, causal news labels, strategy returns, and forecasts.

Reproduce the public report with npm run analyze:seo:phase3. Download the complete Phase 3 evidence JSON.

Read the five Phase 3 studies

Beginner exploration

Three questions to help you use this page

Open each answer for a plain-language way to read Cross-asset volatility regimes, test it carefully and decide what to explore next.

What does “Cross-asset volatility regimes” mean for a beginner?

This page focuses on “Cross-asset volatility regimes”.Explore low, normal, and high volatility regimes across eight FX, index, and crypto markets using 14,733,087 validated M1 candles and public proof.For “Cross-asset volatility regimes”, a beginner should identify what the research study measures, assumes or teaches before acting on its conclusion.Treat this page's account of “Cross-asset volatility regimes” as a learning reference rather than a prediction, signal or promise of future performance.

How should a beginner use this page to explore “Cross-asset volatility regimes”?

For “Cross-asset volatility regimes”, start with the research question, then confirm the instrument, feed, date window, units and exclusion rules.While exploring “Cross-asset volatility regimes”, read the sample count and methodology before looking at the strongest result in a table.Keep your “Cross-asset volatility regimes” record honest: separate a historical description from a forecast and keep unresolved or ambiguous cases in view.Before leaving “Cross-asset volatility regimes”, use a later untouched sample before treating an observed pattern as stable.

How can AI help explore “Cross-asset volatility regimes” responsibly?

Turn one idea from “Cross-asset volatility regimes” into a rule with explicit inputs, dates, costs and pass-or-fail conditions.Ask AI to expose missing assumptions in that “Cross-asset volatility regimes” test, not to guess the next market move.Use the FXAbsolute AI Backtesting Lab to inspect calculations connected to “Cross-asset volatility regimes” and the assumptions behind them.Reproduce any important “Cross-asset volatility regimes” result and reserve unseen data before deciding that an apparent pattern is useful.

Continue your exploration of Cross-asset volatility regimes with the beginner AI prompt guide, or inspect public calculations in the AI Backtesting Lab.