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Finance & Capital

Quarter-over-Quarter (QoQ)

Also known as: QoQ, quarter-over-quarter, QoQ change

Quarter-over-quarter (QoQ) is the change in a metric from one fiscal quarter to the immediately prior quarter; in U.S. bank reporting the four quarters end March, June, September, and December, and QoQ deltas are expressed in percentage points (pp) for ratios or percent (%) for dollar levels.

Quarter-over-quarter (QoQ) is the change in a metric from one fiscal quarter to the immediately prior quarter. In U.S. bank and credit union reporting, the four quarters end March 31, June 30, September 30, and December 31, aligning with the FDIC and NCUA call-report cadence. QoQ is the unit of analysis for trend detection in NPL Explorer's distress-card framework — a single quarter's snapshot is a point, two consecutive quarters form a vector.

How is QoQ Calculated?

The convention depends on whether the underlying metric is a ratio or a dollar level:

Metric TypeQoQ ConventionExample
Ratio (e.g., Texas Ratio, Tier 1 leverage, NWR)Subtract; express in percentage points (pp)18.4% − 15.1% = +3.3pp
Dollar level (e.g., total assets, OREO balance, ACL)Divide; express in percent (%)($85M − $68M) / $68M = +25%

Mixing the two conventions — for example, reporting a Texas Ratio QoQ change as a percentage rather than percentage points — is a common authoring mistake that obscures the magnitude of the change. A Texas Ratio rising from 15% to 18% is a +3pp move, not a +20% move. Both descriptions are arithmetically true but readers consume them differently; the percentage-points convention is the only one that travels cleanly across institutions and metrics.

Quarter Definitions

All federally insured banks and credit unions report on the calendar-quarter cycle. There is no off-cycle fiscal-quarter reporting in regulator data — every FDIC and NCUA panel publishes for Mar/Jun/Sep/Dec exclusively.

QoQ should not be confused with year-over-year (YoY), which compares the current quarter to the same quarter one year prior. YoY smooths seasonal patterns; QoQ captures the most-recent trajectory and is the more sensitive trend indicator for distress detection.

QoQ in Cohort Context

A single institution's QoQ change in isolation is harder to interpret than the same QoQ change set against the peer cohort median QoQ for the same metric. A 3pp jump in Texas Ratio at a community bank when the cohort median jumped 2.5pp is sector-typical noise; the same 3pp jump when the cohort median was flat is institution-specific deterioration worth investigating. NPL Explorer surfaces both the raw QoQ delta and the cohort-relative QoQ delta for the metrics it tracks.

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