Financial Markets and Terrorism: The Perspective of the Two Sides of the Conflict
Bibliographic record
Abstract
This paper uses a unique data set and advanced econometric methods to examine the effect of terrorism on financial markets of both sides of the barricade in the Israeli-Palestinian conflict. The main finding are: (1) Real economies on both sides suffered significantly during the intifada period; (2) On the avarege share prices on the Israeli side declined significantly due to terror attack by 0.43% where the decline on the other side (probably due to fear of retaliation) was much less and insignificant; (3) There is a bi-directional causality effects of returns in the two markets and both markets are affected by the US market; (4) The more fatal the terror attack is, the greater is the negative effect in the two markets. In the more severe terror attack event (i.e. more people were killed and injured or if it was suicide attack), share prices in the Israeli market declined significantly by 0.63% compared to a decline of 0.16% in less severe attacks. The same pattern, but less significant is revealed on the Palestinian side. In the more severe terror attack, share prices declined significantly by 0.21% compared with 0.07% in less severe attacks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".