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Record W4319709962 · doi:10.58886/jfi.v10i1.2322

Transmission of Shocks to LIBOR Risk Spreads and Nominal Risk-Free Rates

2012· article· en· W4319709962 on OpenAlexaboutno aff
Albert E. DePrince, Pamela D. Morris

Bibliographic record

VenueJournal of Finance Issues · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMonetary Policy and Economic Impact
Canadian institutionsnot available
Fundersnot available
KeywordsLiborVector autoregressionEconomicsShock (circulatory)Monetary economicsEconometricsInterest rate

Abstract

fetched live from OpenAlex

In this study, effects of shocks to international money market conditions, as measured by the three-month London Interbank Offer Rates (LIBOR) for five financially integrated economies (United States, the euro zone countries, Great Britain, Japan, and Canada) are examined. The sample period runs from January 4, 1999, through December 31, 2010. A fiveequation vector autoregressive (VAR) model is developed using daily risk spreads between each country’s LIBOR and its nominal risk-free rate. Also, effects of the risk spreads on the respective nominal risk-free rates are identified in a separate VAR system. Based on the risk-spread VAR, effects of exogenous shocks are examined. Single-country impulse tests show that the feedthrough effects on the other countries are surprisingly limited for these integrated countries. Only when a shock is applied concurrently to all five risk spreads can effects on the magnitude noted in 2008 and 2009 be replicated, suggesting that all LIBOR rates were affected by a contemporaneous shock. Finally, a proportion of the shock to the risk-spread feed has an inverse effect on each country’s nominal risk-free rate, reflecting the effect of the flow of funds from risky assets to safe assets in a time of increased risk and vice versa.

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)0.001
metaresearch head score (Gemma)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.040
GPT teacher head0.260
Teacher spread0.220 · 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.

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".

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Citations0
Published2012
Admission routes1
Has abstractyes

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