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Record W3122747833 · doi:10.3386/w24506

Sovereign Credit Risk and Exchange Rates: Evidence from CDS Quanto Spreads

2018· article· en· W3122747833 on OpenAlexaff
Patrick Augustin, Mikhail Chernov, Dongho Song

Bibliographic record

VenueNational Bureau of Economic Research · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsMcGill University
Fundersnot available
KeywordsDevaluationSovereign defaultForeign exchange riskMonetary economicsRisk premiumEconomicsCurrencyCredit riskExchange rateArbitrageBondBusinessSovereigntyFinancial economicsFinanceSovereign debt

Abstract

fetched live from OpenAlex

Sovereign CDS quanto spreads-the difference between CDS premiums denominated in U.S. dollars and a foreign currency-tell us how financial markets view the interaction between a country's likelihood of default and associated currency devaluations (the Twin Ds).A noarbitrage model applied to the term structure of quanto spreads can isolate the interaction between the Twin Ds and gauge the associated risk premiums.We study countries in the Eurozone because their quanto spreads pertain to the same exchange rate and monetary policy, allowing us to link crosssectional variation in their term structures to cross-country differences in fiscal policies.The ratio of the risk-adjusted to the true default intensities is 2, on average.Conditional on the occurrence of default, the true and risk-adjusted 1-week probabilities of devaluation are 5% and 77%, respectively.The risk premium for the euro devaluation in case of default exceeds the regular currency premium by up to 0.3% per week.

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)0.003
metaresearch head score (Gemma)0.042
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 score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.366
GPT teacher head0.459
Teacher spread0.092 · 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
Published2018
Admission routes1
Has abstractyes

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