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Record W3187034467 · doi:10.1093/cmlj/kmab015

Make-wholes in sovereign bonds

2021· article· en· W3187034467 on OpenAlexaboutno aff
Ugo Panizza, Mitu Gulati

Bibliographic record

VenueCapital Markets Law Journal · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
Fundersnot available
KeywordsTreasuryBondMaturity (psychological)Forward rateEconomicsCorporate bondFinancial economicsInterest rateFixed incomeMonetary economicsBasis pointValue (mathematics)Actuarial scienceBusinessFinanceMathematicsStatisticsPolitical science

Abstract

fetched live from OpenAlex

Multiple researchers have observed a dramatic shift in US corporate bonds starting roughly in the mid-1990s and extending to the current period: from fixed premium call options to flexible rate call options.1 This flexible rate call provision was known initially as the ‘doomsday call’ and is now referred to as ‘make-whole’ call. It originated in the Canadian corporate bond market in the mid-1980s and migrated to the USA in the mid-1990s.2 Today, it is ubiquitous in the corporate bond market. A fixed premium call typically specified a percentage premium over the principal amount as a function of the remaining time on the bond (eg 110 per cent, if called five years prior to maturity year or 108 per cent if redeemed four years prior and so on).3 A ‘make-whole’ call, instead, measures the amount to be paid as a discounted value of future amounts, with the discount rate being a small spread over the prevailing risk-free rate (eg the discount rate might be the US Treasury rate plus 50 basis points).4

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)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0060.008
Open science0.0010.003
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0200.002

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 head0.015
GPT teacher head0.213
Teacher spread0.199 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2021
Admission routes1
Has abstractyes

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