Subjective/ Behavioural Factors Influence the PSI 20 and IBEX 35
Bibliographic record
Abstract
This study assesses the impact of investor sentiment on the volatility of the PSI 20 and IBEX 35 from time series data from January 1988 to May 2019. The impact of investor sentiment on market and portfolio selection has aroused great interest in the literature, however the results obtained are not consensual, considering the different methodologies used to build sentiment indices, as well as the various levels of institutional development in the market.Asymmetric volatility behaviours according to good or bad news were evaluated using the TGARCH model. The results indicate that there is an asymmetric effect of good versus bad news on the volatility of IBEX 35. It was also noted that for Portugal and Spain investor sentiment presents statistical significance with a negative sign, suggesting that market volatility is more sensitive to negative shocks in the conditional variance. In Portugal, contrary to Spain, sentiment has no relevance on return. The study reveals that investor sentiment is a key factor in selecting investment in the market. The relationship that this establishes with volatility, can help to implement policies that allow to minimize future shocks’ impact on return. The study reveals for the first time that investor sentiment is a key factor in selecting investment in the market for Portugal.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".