Educational worksheet · setupsmarkethub.online · Updated 23 October 2026

Prop Correlation Research: Join Dates Before Calculating a Relationship

A correlation calculation pairs observations. If two return series use different trading dates, pairing rows by position can compare unrelated periods. Establish the date join and missing-data policy before using a relationship in evaluation research.

Explore this site’s existing research resource

Define what one paired row means

Record the market, return interval, currency and endpoint convention for each series. Join the same dated intervals rather than simply placing the first row beside the first row. Different session closes can still leave a timing mismatch even when the date labels match.

Keep an unmatched date visible. Inserting a zero or carrying a prior value creates a model assumption; it does not recover a missing return. The existing date-alignment resource on this site remains the companion for that audit.

Inspect a fictional three-date intersection

Series A supplies returns on Monday, Tuesday and Wednesday. Series B supplies Monday, Wednesday and Thursday. The observed intersection is Monday and Wednesday: two paired rows. Pairing the three row positions would incorrectly match Tuesday with Wednesday and Wednesday with Thursday.

Two observed pairs do not provide strong evidence of a stable market relationship. A calculated coefficient, if one is reported, needs its sample size, exact periods and assumptions beside it. It does not establish a future hedge, joint loss bound or account permission.

Fictional date-intersection audit
DateSeries ASeries B / treatment
MondayObservedObserved:paired
TuesdayObservedMissing:unmatched
WednesdayObservedObserved:paired
ThursdayMissingObserved:unmatched

Keep the research and account questions distinct

A market statistic cannot supply actual fills, costs or evaluation headroom. Review the current HashHedge product and method conditions independently. This article does not propose opposing or coordinated accounts to evade a provider’s loss conditions.

The optional sponsored link leads to programme information after the audit method. No live series is downloaded, no market relationship is estimated here and no pass probability is asserted. The useful result is an explicit paired dataset and an honest list of unmatched observations.

Sources and rule dates