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Record W3124903334

The Impact Of The Persian Gulf Crisis On National Equity Markets

2005· article· en· W3124903334 on OpenAlexaboutno aff
A. G. Malliaris, Jorge L. Urrutia

Bibliographic record

VenueWorld Scientific Book Chapters · 2005
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)Diversification (marketing strategy)Stock marketEconomicsStock (firearms)Monetary economicsEvent studyPersianFinancial economicsBusinessGeographyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

This paper uses the mean-adjusted returns and the market and risk-adjusted returns event-study methodologies to analyze the response of national equity markets to the Persian Gulf Crisis. Daily cumulative abnormal returns are computed for 16 national stock markets and three portfolios of national markets. The main empirical findings are: (1) the Persian Gulf Crisis had a negative effect on equity prices; (2) the Oil Crisis had a greater negative effect on the European, Asian, and Australian markets than on the American and Canadian markets; (3) the initiation of the Gulf War had a much lesser impact in the equity market prices than the invasion of Kuwait; (4) the national markets reacted to both events, the invasion of Kuwait and the start of the Gulf War with lags of two to three days. The negative abnormal returns following the invasion of Kuwait seem to reflect investors' fear of a long armed conflict in the Middle East. On the other hand, the positive abnormal returns following the initiation of the War suggest that investors expected a quick end to the Gulf War. Our results confirm the important role played by oil prices in the world economies and the limitations of international diversification. The efficiency of equity markets is also reflected in the fact that several national markets responded to the Persian Gulf Crisis according to the country's dependence on oil imports.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.693
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.271
Teacher spread0.237 · 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.

Study designNot applicable
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
Published2005
Admission routes1
Has abstractyes

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