MétaCan
Menu
Back to cohort
Record W2563542046 · doi:10.1287/mnsc.2017.2836

The Bull of Wall Street: Experimental Analysis of Testosterone and Asset Trading

2017· article· en· W2563542046 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueManagement Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsTestosterone (patch)Affect (linguistics)Asset (computer security)Monetary economicsEconomicsValue (mathematics)Financial economicsBusinessEndocrinologyPsychologyBiologyComputer scienceCommunicationStatisticsMathematics

Abstract

fetched live from OpenAlex

Growing evidence shows that biological factors affect individual financial decisions that could be reflected in financial markets. Testosterone, a chemical messenger especially influential in male physiology, has been shown to affect economic decision making and is taken as a performance enhancer among some financial professionals. This is the first experimental study to test how testosterone causally affects trading and prices. We exogenously elevated testosterone in male traders and tested testosterone’s effect both on their trading behavior in experimental asset markets and on the size and duration of asset price bubbles. Using both aggregated and individual trading data, we find that testosterone administration generated larger and longer-lasting bubbles by causing high bids and the slow incorporation of the asset’s fundamental value. The e-companion is available at https://doi.org/10.1287/mnsc.2017.2836 . This paper was accepted by Uri Gneezy, behavioral economics.

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.

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 categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.050
GPT teacher head0.364
Teacher spread0.314 · 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