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Record W2117022793 · doi:10.5539/ijef.v1n2p3

Turn-of-the-month and Intramonth Anomalies and U.S. Macroeconomic News Announcements on the Thinly Traded Finnish Stock Market

2009· article· en· W2117022793 on OpenAlexvenueno aff
Jussi Nikkinen, Petri Sahlström, Karri Takko, Janne Äijö

Bibliographic record

VenueInternational Journal of Economics and Finance · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Risk and Volatility Modeling
Canadian institutionsnot available
Fundersnot available
KeywordsStock (firearms)Stock marketEconomicsMonetary economicsBusinessFinancial economicsGeography

Abstract

fetched live from OpenAlex

Evidence from the U.S. stock market as well as from major European stock markets has lately suggested that the turn-of-the-month (hereafter TOM) and intramonth anomalies occur because of major U.S. macroeconomic news announcements that are released around the TOM. World-wide markets are becoming more integrated and therefore in this study we hypothesize that major U.S. macroeconomic news announcements are also the cause for the TOM and intramonth effects on the thinly traded Finnish market. This study uses Finnish data to first identify significant TOM and intramonth effects and second to investigate whether these anomalies arise because of the clustered major U.S. macroeconomic news announcements. Both so-called calendar anomalies are evident, but after controlling for the effect of the major U.S. news releases the anomalies disappear, resulting in further evidence for the significance of the clustered U.S. macroeconomic news announcements. The results of this study are in line with earlier findings and claim that the TOM and intramonth anomalies are driven by the clustered release of major U.S. macroeconomic news announcements.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.483
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.022
GPT teacher head0.219
Teacher spread0.197 · 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 designTheoretical or conceptual
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

Citations15
Published2009
Admission routes1
Has abstractyes

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