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Model methodsSystemic riskactive

Absorption ratio and AR shift

The share of bank-return variance captured by the leading correlation-matrix eigenvalues, plus a short-minus-long moving-average shift in that share.

Registry slug:
absorption-ratio
Visible surface:
/systemic

Data and implementation

Vintage

2,951 absorption-ratio observations from 2020-04-03 and 1,130 AR-shift observations from 2021-12-31, both through 2026-07-06, measured 2026-08-30

Data tables

  • data/parquet/systemic_series.parquet

Engine

  • engine/finweave_engine/layers/systemic/absorption.py

Producer

scripts/build_systemic.py

Outputs

  • data/parquet/systemic_series.parquet

Source: Yahoo Finance equity returns via the argus collector, internal-use input

Method

The engine computes a rolling correlation matrix for the fresh 27-bank panel, orders its eigenvalues, and divides the sum of the top 20% by total variance. The producer publishes this absorption ratio over both 63-day and 252-day windows.

AR shift is a separate series. It subtracts the 252-day moving average of the 252-day absorption ratio from its 21-day moving average, so it measures a change in coupling rather than the variance share itself.

Methodology evidence

Path and linesEvidence
engine/finweave_engine/layers/systemic/absorption.py:13-56Constructs the PCA variance share from the top 20% of correlation-matrix eigenvalues.
engine/finweave_engine/layers/systemic/absorption.py:77-98Constructs AR shift as the short-window average minus the long-window average.
docs/systemic_methodology.md:196-218Distinguishes the two rolling PCA windows from the separate AR-shift series and records their spans.
docs/systemic_methodology.md:269-338Records crisis anchors and independent recomputation validation for the systemic output.

Equations

Absorption ratioAR = sum(top eigenvalues) / sum(all eigenvalues)
AR shiftAR shift = short-window AR average minus long-window AR average

Validation

  • The parquet contains 2,951 absorption-ratio observations from 2020-04-03 and 1,130 AR-shift observations from 2021-12-31, both ending 2026-07-06.
  • The documented independent recomputation of the 63-day absorption ratio on 2023-03-17 matches the stored value at six decimal places (absolute difference 2.22e-16), and the COVID-period level is reported against the full-sample distribution.

Limitations

  • The absorption ratio is a system-level co-movement statistic, not an institution-level loss, failure probability, or causal measure of fragility.
  • The 63-day and 252-day absorption ratios are separate rolling constructions. Their rows are combined under one measure name and are distinguished by window_days.
  • AR shift is available later because it requires 21-day and 252-day moving averages of the already rolling 252-day absorption series.
  • The underlying Yahoo-derived equity-return input carries an internal-use, display-aggregates-only licence posture and is not a redistributable raw dataset.

References

  • Kritzman, Li, Page, and Rigobon (2011), Principal Components as a Measure of Systemic Risk, Journal of Portfolio Management 37(4): 112-126.

Metadata endpoint

PathMethodReturnsExample
/api/methods/[slug]GETRegistry metadata, implementation paths, measured vintage, methodology evidence, validation, and limitations. No model observations or parquet contents./api/methods/absorption-ratio
Last verified 2026-08-30