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Record W4246354662 · doi:10.1007/978-3-7908-2660-9_8

Summary

2004· book-chapter· en· W4246354662 on OpenAlexaff
Erik Lüders

Bibliographic record

VenueZEW economic studies · 2004
Typebook-chapter
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsGeometric Brownian motionEconomicsEconometricsMathematical economicsBrownian motionAsset (computer security)Capital asset pricing modelStochastic discount factorFinancial economicsMathematicsComputer scienceDiffusion processEconomyStatistics

Abstract

fetched live from OpenAlex

The purpose of this study is to provide an economic foundation for asset price processes and to derive economically motivated time-series models as alternatives to the empirically motivated time-series models The analysis is based on the fact that asset prices are completely determined by the information process and the pricing kernel The information process may be interpreted as characterizing a representative investor’s expectations while the pricing kernel equals the standardised marginal utility function of the representative investor in such an economy For example, the geometric Brownian motion as a model for the behaviour of asset prices implies that the pricing kernel has constant elasticity and that the information process is also governed by a geometric Brownian motion These relationships were explained in Chaps 2 and 3 In Chap 4 the literature was reviewed in the light of these relationships.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.417
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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)0.0030.009

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 head0.064
GPT teacher head0.234
Teacher spread0.169 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2004
Admission routes1
Has abstractyes

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