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Record W7034443696

Tariffs and stock returns : the effect of U.S. tariffs and Canadian, Chinese and European retaliatory tariffs in 2018

2019· dissertation· en· W7034443696 on OpenAlexaboutno aff

Bibliographic record

VenueSkemman · 2019
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicPaleontology and Evolutionary Biology
Canadian institutionsnot available
Fundersnot available
KeywordsStock marketStock (firearms)ChinaTrade warEvent studyChinese market
DOInot available

Abstract

fetched live from OpenAlex

In this study, the effect of the ongoing trade war, which started in 2018 between the United States on the one hand and the European Union, China and Canada on the other, on stock returns of publicly traded companies, is analysed. The major events of the trade war in 2018 are included in the study. The study was formalised into two hypotheses. Firstly, that the announcement of tariffs in one market would lead to average abnormal returns, either positive or negative, for companies in that market. Secondly, that the announcement of tariffs in one market would lead to average abnormal returns, either positive or negative, for companies in a foreign market targeted by the tariffs. The results of the study show a statistically significant evidence supporting the hypotheses. The study also shows that stock market reactions cannot only be expected in the markets directly involved in the events but also in other markets. In the study, there are examples of market behaviour both consistent and inconsistent with the efficient market hypothesis, and examples of where a backwards drift in returns follows a market overreaction. 
\nKeywords: Corporate finance, Fama and French three-factor model, abnormal returns, tariffs, trade war.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.746
Threshold uncertainty score0.834

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.005
GPT teacher head0.201
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 designObservational
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

Citations0
Published2019
Admission routes1
Has abstractyes

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