MétaCan
Menu
Back to cohort
Record W3122079329 · doi:10.1093/rfs/hhz082

Ambiguity, Volatility, and Credit Risk

2019· article· en· W3122079329 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

VenueReview of Financial Studies · 2019
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsMcGill University
Fundersnot available
KeywordsAmbiguityVolatility (finance)Credit riskCredit default swapBusinessCredit default swap indexSign (mathematics)EconomicsActuarial scienceEconometricsFinancial economicsComputer scienceCredit valuation adjustmentMathematics

Abstract

fetched live from OpenAlex

Abstract We explore the implications of ambiguity for the pricing of credit default swaps (CDSs). A model of heterogeneous investors with independent preferences for ambiguity and risk shows that, because CDS contracts are assets in zero net supply, the net credit risk exposure of the marginal investor determines the sign of the impact of ambiguity on CDS spreads. We find that ambiguity has an economically significant negative impact on CDS spreads, on average, suggesting that the marginal investor is a net buyer of credit protection. A 1-standard-deviation increase in ambiguity is estimated to decrease CDS spreads by approximately 6%. (JEL C65, D81, D83, G13, G22) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

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)0.002
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: Review · Consensus signal: Review
Teacher disagreement score0.219
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.037
GPT teacher head0.276
Teacher spread0.239 · 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