Range state · forward distribution · robustness
6B Compression and Expansion: A Reproducible Test
Suppose the last twelve five-minute bars span 18 ticks while the same clock window’s trailing median span is 42 ticks. The observed ratio is 0.43. That calculation can describe compression. It does not say expansion is next, choose a direction, or prove a tradable edge.
- Input
- Past-only range
- Output
- Forward distribution
- Direction
- Separate test
- Original result
- None
Example onlyNo forecast
Direct calculation
Start With the Range, Not the Story
Fact: realized movement can be summarized from consistent price observations. Observation: a declared recent window can be small relative to a relevant historical distribution. Hypothesis: that state may change the later distribution of movement or execution quality. “Energy building” is a metaphor, not a measurable mechanism.
state ratio = current realized range÷matched trailing median range
The denominator matters. Comparing a quiet overnight hour with the all-day distribution can classify the clock rather than the state. Match the weekday, exact timezone-aware window, bar length, event status, and contract-roll condition. Use only observations available before the candidate time when calculating a rolling percentile or median.
6B’s standard outright tick is 0.0001, worth $6.25 per contract. A range in ticks maps directly to order distance and dollar exposure; a log return is easier to compare across long histories with different price levels. Preserve both and state which one drives the label.
Past-only state
Define Compression Without Peeking at the Break
Compression must be completely knowable at the decision timestamp. A symmetric centered window, a future-confirmed swing, or a box drawn around the bars that preceded a known breakout all leak future information.
| Definition family | Frozen rule | Useful property | Limitation |
|---|---|---|---|
| High-low span | Maximum high minus minimum low over the last n fixed bars | Simple and transparent | One extreme can dominate |
| True-range summary | Median or mean true range over the last n bars | Includes gaps across bar boundaries | Smooths the path and depends on lookback |
| Realized variance | Sum of squared fixed-interval log returns | Uses the intrawindow path | High-frequency noise and bad ticks matter |
| Range percentile | Current measure below a training-sample clock-matched percentile | Adapts scale to the historical distribution | Threshold and lookback can be overfit |
| Multi-scale agreement | Two predeclared measures must both be below their thresholds | Can reject a one-measure artifact | More choices create more search degrees of freedom |
Store the continuous value even when the live rule uses a binary threshold. If the result appears only below the 14.7th percentile and vanishes at the 10th and 20th, the threshold may be fitting noise.
Three separate outcomes
Define Expansion on Size, Direction, and Cost Separately
A large forward range is not the same as a profitable directional break. It can be one clean move, a breakout and reversal, or two-sided churn with poor fills.
Movement
Did the distribution of range change?
Measure forward realized range, realized variance, tail quantiles, and time until a frozen range threshold is reached. Compare the full distribution, not only the average.
Direction
Was movement one-sided?
Measure signed return, close location, path efficiency, breakout-side follow-through, and reversal frequency. Direction must be declared independently of compression.
Execution
Could an order capture it?
Measure spread, displayed depth, trade-through distance, slippage, missed passive fills, and latency. A wider range can arrive with worse execution.
Economics
Did the net rule beat a baseline?
Specify entry, invalidation, exit, sizing, commission, fees, spread, slippage, and queue assumptions. Gross range is not net expectancy.
Predeclare several forward horizons because a state can affect the next 15 minutes but not the next four hours. Treat every horizon as part of the multiple-testing family.
Event sample
Construct One Observation per Eligible State
Repeated low-range bars inside one quiet episode are dependent. Counting each bar as a fresh signal can inflate the sample and reward long-lasting compression.
Episode-based primary sample
Enter an episode when the frozen compression rule first becomes true. Keep it active until an exit threshold is met. Record one anchor timestamp per episode, impose a declared cooldown, and retain duration as a variable. A secondary bar-level analysis can be reported with dependence-aware uncertainty.
- Unit
- Compression episode
- Anchor
- First knowable timestamp
- Cooldown
- Predeclared
- Uncertainty
- Block by day or episode
Clean data
Audit gaps, duplicates, crossed quotes, outliers, and contract identity.
Fit baseline
Use training dates only to estimate clock-matched distributions.
Label episodes
Apply the frozen entry, exit, overlap, and cooldown rules.
Score forward
Measure movement, direction, cost, and failure on untouched dates.
Rival explanations
Control the Clock, News, and Contract
A low-range state often reflects a known information schedule or a thin market. The later expansion may be caused by a release, reopening, or roll transition rather than the compression itself.
Match in an IANA timezone and preserve the daylight-saving regime. Do not pool unlike local hours.
Tag ONS, Bank of England, BLS, BEA, and Federal Reserve times from the contemporaneous official calendar.
Store minutes before and after each release. A pre-news lull is a distinct state, not a generic compression result.
Use dated securities and an ex-ante roll policy. Report nearby and next-contract results around migration.
Condition on spread, depth, quote-update rate, and outages. Zero trades can mean missing data.
Compare within longer-run states so a low intraday percentile in a crisis is not equated with ordinary calm.
Stress the result
A Finding Should Survive Reasonable Definitions
Robustness is not rerunning parameters until one works. Declare the grid before opening the holdout and publish all cells.
| Stress test | What changes | Failure signal |
|---|---|---|
| Sampling | One-, five-, and fifteen-minute inputs with noise-aware construction | Effect exists only at the noisiest frequency |
| Threshold neighbors | Adjacent percentiles and durations | Sign or magnitude flips at small changes |
| Outcome horizon | Several frozen forward windows | Only a post-selected endpoint looks favorable |
| Event exclusion | All dates, non-event dates, and named event families | Generic claim is entirely an event effect |
| Contract construction | Dated contracts, two ex-ante roll rules, no stitch bars | Continuous-series artifact drives the result |
| Cost scenarios | Observed and stressed spread/slippage, missed fills | Net result fails under ordinary friction |
| Chronology | Development, validation, final holdout, rolling re-estimation | Performance decays outside the fit period |
Report effect sizes and uncertainty intervals, not just a p-value. If testing many definitions, horizons, sessions, and trade rules, use a multiple-testing procedure or present the study as exploratory. Keep the final holdout sealed until the analysis code and exclusions are frozen.
Evidence hierarchy
What the Evidence Can and Cannot Support
The strongest permissible conclusion depends on which layer has actually been measured.
A named window’s realized range was low relative to a frozen matched distribution.
In a disclosed sample, a declared forward outcome differed from its matched baseline with uncertainty reported.
A fully specified, costed rule remained stable on untouched data and across reasonable variants.
Current data quality, liquidity, margin, and risk limits match the conditions under which the rule was validated.
Layer 1 is a measurement definition. Layers 2 through 4 are not claimed. No original 6B dataset, event count, expansion frequency, directional edge, backtest or live performance result was produced. The 18-tick, 42-tick and 0.43 values are a hypothetical calculation, not a market observation.
Sources, method and editorial disclosure
- CME Group British Pound product overview for current standard-contract size, tick, quotation, and trading-hour context.
- Andersen, Bollerslev, Diebold, and Labys, Modeling and Forecasting Realized Volatility for realized-volatility construction from intraday returns.
- Ait-Sahalia and Yu, High Frequency Market Microstructure Noise Estimates and Liquidity Measures for the need to distinguish high-frequency price noise from the latent signal.
- Office for National Statistics release calendar and Bank of England monetary-policy schedule for contemporaneous U.K. event labels.
- U.S. Bureau of Labor Statistics release calendar, U.S. Bureau of Economic Analysis release schedule, and Federal Reserve FOMC calendar for U.S. event controls.
Sources and time-sensitive facts were reviewed August 13, 2026. This is original, unsponsored editorial analysis.