Have Sentiments Influenced Malaysia’s Stock Market Volatility During the 2008 Crisis?
Bibliographic record
Abstract
This paper examined the effects of both macro-economic and investor sentiment on the volatility of the Malaysian stock market, during the 2008 global financial crisis.However, as the measurement for investor sentiment is unavailable, we constructed an investor sentiment composite index from a number of proxies, namely; the stock market turnover, number of Initial public offerings (IPO) and its initial returns, advance decline ratio, and consumer sentiment index by employing a strict process of Factor analysis with Principal component analysis' extraction.By employing Autoregressive Distributive Lags (ARDL) model, we observed the failure of macroeconomic fundamentals to significantly predict the Malaysian stock market's volatility during the crisis period while investor sentiment was a significant factor that influenced the market.These findings support the notion that investors tend to behave irrationally during crisis periods and these may assist practitioners in formulating specific investment strategies during crucial periods in order to gain abnormal returns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".