A Study on the Relationship between Economic Policy Uncertainty and Stock Volatility
Bibliographic record
Abstract
As an important part of economic operation, financial market has been playing an indispensable role, whether positive or strong negative impediment. If the financial market runs steadily, it will undoubtedly benefit the good operation of the economy, but the transition fluctuation of the financial market will easily lead to major difficulties in economic development. Therefore, the government has been committed to adopt different policy measures to regulate the healthy development of the economy and even the financial market, but the frequent introduction of policies will inevitably lead to policy uncertainty, which itself will lead to financial market volatility to a certain extent. Taking stock market as the representative of financial market, this paper studies the correlation between China’s economic policy uncertainty and China’s stock market. Using monthly data from 1995 to 2019, so as to trigger in-depth thinking，this paper mainly uses VAR model to explore whether there is a structural mutation in the relationship between the two, and to find out the reasons behind the mutation.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".