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AN ADMISSIBLE TERM STRUCTURE MODEL OF SOVEREIGN YIELD SPREADS WITH MACRO FACTORS: THE CASE OF BRAZILIAN GLOBAL BONDS

2009· article· en· W2104101048 on OpenAlexaff
Zhuoshi Liu, Peter Spencer

Bibliographic record

VenueManchester School · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsBarrie Urology Group
Fundersnot available
KeywordsEconomicsBondVolatility (finance)MacroYield (engineering)Monetary economicsSovereigntyCredit riskAffine term structure modelTerm (time)Yield curveSovereign defaultEconometricsFinancial economicsFinanceSovereign debt

Abstract

fetched live from OpenAlex

We study the term structure of Brazilian sovereign bond yield spreads and their links with the domestic economy using a macro‐finance framework. Our model allows Brazilian macroeconomic variables as well as a latent country risk factor to affect sovereign spreads. We find that although the Brazilian sovereign yield spreads are dominated by the risk factor during the high default risk periods of 1999 and 2002, the effects of macro variables are significant during the rest of the estimation period. In addition, the volatility level of the macroeconomic system is driven by the country risk factor.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.242
Teacher spread0.216 · 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 designSimulation or modeling
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
Published2009
Admission routes1
Has abstractyes

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