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Record W3016526541 · doi:10.21511/bbs.15(2).2020.03

Asset portfolio maturity changes during the financial crisis: evidence from U.S. banks

2020· article· en· W3016526541 on OpenAlexaboutno aff
Thomas W. Secrest

Bibliographic record

VenueBanks and Bank Systems · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsMaturity (psychological)PortfolioAsset (computer security)Financial crisisBusinessProxy (statistics)Quarter (Canadian coin)Monetary economicsFinancial systemEconomicsFinanceMathematicsGeographyStatistics

Abstract

fetched live from OpenAlex

This paper determines if the maturity structure of commercial banks’ asset portfolios changed as a result of the financial crisis of the late 2000s and whether any changes in the portfolios may be homogeneous across bank size. A proxy for the maturity of rate-sensitive assets is constructed, and it is found that significant changes did begin to occur during the third quarter of 2008. The maturity structure of assets of relatively small banks gradually began to increase before leveling off six years later. The maturity of larger bank asset portfolios had been falling and continued to decrease for three more years, until reversing during the 3rd quarter of 2011. Large banks also have significantly shorter-term portfolios compared to their smaller counterparts, which tend to be very similar regardless of their small size. The composition of banks’ asset portfolios is also examined with some notable differences among banks of different size.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.222
Teacher spread0.189 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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