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Record W4321374074 · doi:10.5750/jpm.v16i3.1957

Health risk, stimulus packages, and subordinated bank yields: evidence from the COVID-19 outbreak.

2023· article· en· W4321374074 on OpenAlexaboutno aff
Evangelos Vasileiou

Bibliographic record

VenueThe Journal of Prediction Markets · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCOVID-19 Pandemic Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)Stimulus (psychology)BondGovernment bondPandemicStock (firearms)German governmentEmpirical evidenceGermanOutbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Monetary economicsBusiness2019-20 coronavirus outbreakEconomicsActuarial scienceFinancial economicsEconometricsFinancePsychologyMedicineVirologyGeography

Abstract

fetched live from OpenAlex

This note presents the impact of pandemic on bank subordinated bonds. Using weekly data for the period 10/1/2020-12/3/2021 of 14 US, UK, Spanish, Italian, German, and Canadian banks this note provides empirical evidence that the health risk due to the COVID-19 increases the bank yields, and the stimulus packages achieved the main objective which was to reduce the risk of the bond markets and the yields. The impact of pandemic could be measured by the searches of COVID-19 related terms on Google trends. Moreover, the empirical section shows that subordinated bond yields are influenced negatively by the performance of the stock price and positively by the government yields.

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 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)0.011
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.068
GPT teacher head0.299
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations3
Published2023
Admission routes1
Has abstractyes

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