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Record W2166900235 · doi:10.1017/s1053837213000205

ECONOPHYSICS: A NEW CHALLENGE FOR FINANCIAL ECONOMICS?

2013· article· en· W2166900235 on OpenAlexaff
Franck Jovanovic, Chrıstophe Schınckus

Bibliographic record

VenueJournal of the History of Economic Thought · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicComplex Systems and Time Series Analysis
Canadian institutionsSocial Sciences and Humanities Research CouncilUniversité TÉLUQ
Fundersnot available
KeywordsEconophysicsMainstreamMainstream economicsEconomicsField (mathematics)Neoclassical economicsFinancial econometricsFinanceFinancial economicsPositive economicsFinancial marketApplied economicsPolitical scienceMathematicsLawIndirect finance

Abstract

fetched live from OpenAlex

Financial economics was born in the 1960s. It took less than two decades for the new discipline’s main theoretical results to become established, creating what is considered to be mainstream financial economics. Less than thirty years later, a new field of research called “econophysics” was created. This field aims to reinvent modern financial theory and, indirectly, financial economics. This article proposes to study, by an historical analysis, to what extent econophysics today could constitute one of the major theoretical challenges to financial economics. It shows how these two fields have historical similarities, and analyzes how these similarities call the future evolution of financial theory into question.

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)0.004
metaresearch head score (Gemma)0.009
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: Review · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0030.018
Scholarly communication0.0100.024
Open science0.0010.003
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0070.002

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 head0.034
GPT teacher head0.193
Teacher spread0.158 · 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
GenreReview

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

Citations29
Published2013
Admission routes1
Has abstractyes

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