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Record W2112198014 · doi:10.7202/1106753ar

Bank Capital, Securitization and Credit Risk: An Empirical Evidence

2023· article· en· W2112198014 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAssurances et gestion des risques · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsStatistics CanadaHEC Montréal
Fundersnot available
KeywordsSecuritizationBusinessCapital adequacy ratioCredit riskCapital requirementEconomic capitalFinancial systemCredit enhancementCapital (architecture)EconomicsFinanceProfit (economics)Credit reference

Abstract

fetched live from OpenAlex

This paper is one of the first attempts to conduct an empirical investigation of the relationship between bank capital, securitization and bank risk-taking in a context of the rapid growth in off-balance-sheet activities. The data come from the Canadian financial sector. Evidence from the 1988-1998 period indicates that: (a) securitization has a negative statistical link with both current Tier 1 and Total risk-based capital ratios, and (b) there exists a positive statistical link between securitization and bank risk-taking. Profit-risk measure is more sensitive than loss-risk measure to the variation in securitization activity. These results seem to agree, during the studied period, with models indicating that banks might be induced to shift to more risky assets under the current capital requirements for credit risk because the regulatory capital levels are considered too high.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.126
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.077
GPT teacher head0.307
Teacher spread0.231 · 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