MétaCan
Menu
Cohort builder

4,299,418 works, Canadian by any of four routes.

Every filter state is a URL; the URL is the query; the query is citable via /q/⟨hash⟩. The page, the API and the export parse the same parameters.

The current cohort, streamed from the database: every work column, the machine labels, the provisional scores, and the per-row validation status. Exports are capped at 100,000 rows. Mints a permanent /q/ link for this exact query. The same filters always produce the same link, whoever asks.

Search term
Author
Year range
→
Sort
Language
Type
Field
Venue
Topic
Financial Markets and Investment Strategies
Retraction
Abstract
Evidence source
Study design
Label agreement
Label status

Direct Codex and Gemma labels are unvalidated and sparse. Distilled predictions cover the full frame and are also unvalidated. Choose the evidence source explicitly; absence of a direct label is never a negative label.

affaffiliation
fundfunder
venuejournal
aboutaboutness

The four routes compose: require the funder route and exclude affiliation to get the funder-only stratum no affiliation-based frame ever sees.

3,747 results · 1 filter active ·
Results by year
20002025
Publication date
Categories
Machine labels · sparse coverage
Evidence
Language
Type
Citations
An unlabeled work is unknown, not a negative. Label coverage is reported on every query.
3,747 works in the cohort · of 4,299,418page 34 of 75

Labels cover 0 of 3,747 works in this cohort. The rest are unlabeled, which is not a negative label: the label table is sparse today and grows as labeling rounds land.

Distilled predictions cover 3,747 of 3,747 works in this cohort. Predictions are machine_predicted_unvalidated. The Gemma side is a direct model label for every work (title-only); the Codex side is a distilled, calibrated classifier. Candidate is the union; consensus is the intersection.

affno abstractunlabeled
Hedge funds trading strategies and leverage
Wenli Huang, Wenqiong Liu, Lei Lu, Congming Mu
2023· article· en· Journal of Economic Dynamics and Control· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Can Anomalies Survive Insider Disagreements?
Deniz Anginer, Gerard Hoberg, H. Nejat Seyhun
2015· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Downside Variance Risk Premium
Bruno Feunou, Mohammad R. Jahan‐Parvar, Cédric Okou
2015· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
venueno affunlabeled
VPIN and the China’s Circuit-Breaker
Yameng Zheng
2017· article· en· International Journal of Economics and Finance· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
aboutno affunlabeled
The Dynamic Informativeness of Scheduled News
Julio A. Crego, Jasmin Gider
2023· article· en· Management Science· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Why Do Predicted Stock Issuers Earn Low Returns?
Charles M.C. Lee, Kezhi Li
2022· article· en· The Review of Asset Pricing Studies· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
venueno affunlabeled
Aggregate News Sentiment and Stock Market Returns in India
S. Lakshmana Chari, Purva Hegde Desai, Nilesh Borde, Babu George
2023· article· en· Journal of risk and financial management· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Time Variation in Cash Flows and Discount Rates
Tolga Cenesizoglu, Denada Ibrushi
2022· article· en· Journal of Financial Econometrics· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
What is Quantum Finance and Economics?
David Orrell, Emmanuel Haven, Raymond J. Hawkins
2024· article· en· Quantum Economics and Finance· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
THE GLOBAL MACRO HEDGE FUND CEMETERY
Masoud Asgharian, Fernando Diz, Greg N. Gregoriou, Fabrice Douglas Rouah
2004· article· en· Journal of Derivatives Accounting· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affunlabeled
Too Big to Fail or Too Deceitful to be Caught?
Olivier Mesly, Hareesh Mavoori, François‐Éric Racicot
2021· article· en· Journal of Economic Issues· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
fundno affunlabeled
Event-day Options
Jonathan H. Wright
2020· preprint· en· National Bureau of Economic Research· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations
affno abstractunlabeled
Institutional Trading and Anomalies
Paul Calluzzo, Fabio Moneta, Selim Topaloglu
2015· article· en· SSRN Electronic Journal· Economics, Econometrics and Finance
machine prediction:candidate · noneconsensus · none
4
citations

How this was built: Screen · Findings · About