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Record W4412313754

Structured Retail Products and Return Predictability

2012· article· en· W4412313754 on OpenAlexfundno aff
Henrik Nørholm

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicForecasting Techniques and Applications
Canadian institutionsnot available
FundersHEC Montréal
KeywordsPredictabilityBusinessEconometricsEconomicsMathematicsStatistics
DOInot available

Abstract

fetched live from OpenAlex

This paper studies the cost structure and pricing efficiency of principal protected notes (PPNs) from the Danish retail market.Our data set consists of detailed information on almost 400 Danish issues of PPNs during the period from 1998 to 2009.Comparing actual offer prices with theoretical fair values we find that on average PPNs are overpriced by about 6%.Only half of the overpricing can be explained by the costs disclosed by sellers at the time of issuance.At the individual instrument level we find time to maturity and indicators of product complexity to be important determinants of costs and of the degree of overpricing, but other factors such as arranger and issuer size play a part as well.The degree of overpricing of PPNs has declined over time, but the unexplained cost component -hidden costs -has not.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.174
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.166
GPT teacher head0.379
Teacher spread0.213 · 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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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