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Record W3136715134 · doi:10.1093/jjfinec/nbaa029

Regulatory Capital and Incentives for Risk Model Choice under Basel 3*

2020· article· en· W3136715134 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.

Bibliographic record

VenueJournal of Financial Econometrics · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsWestern University
Fundersnot available
KeywordsCapital requirementBasel IIIBasel IIRisk-adjusted return on capitalRisk-weighted assetCapital adequacy ratioPortfolioEconomicsIncentiveCapital (architecture)Basel IBank regulationEconomic capitalMarket liquidityBusinessActuarial scienceFinancial economicsFinanceFinancial capitalMicroeconomicsCapital formation

Abstract

fetched live from OpenAlex

Abstract In response to the Subprime mortgage crisis, the Basel Committee on Banking Supervision (BCBS) has spent the previous decade overhauling the regulatory framework that governs how banks calculate minimum capital requirements. In 2019, the BCBS finalized the Basel 3 regulatory regime, which changes the regulatory measure of market risk and adds new complex calculations based on liquidity and risk factors. This article is motivated by these changes and seeks to answer the question of how regulation affects banks’ choice of risk-management models, whether it incentivizes them to use correctly specified models, and if it results in more stable capital requirements. Our results show that, although the models that minimize regulatory capital for a representative bank portfolio also result in the most stable requirements, these models are generally rejected as being correctly specified and tend to produce inferior forecasts of the regulatory risk measures.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.261
Threshold uncertainty score0.900

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.039
GPT teacher head0.228
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