Dopad finanční krize na kolektivní investování v České republice
Bibliographic record
Abstract
In this thesis we examined the implications of the financial crisis from the September 2008 for investments into mutual funds in the Czech Republic. We compared this implication for worldwide, European and Czech mutual funds market. Using the linear regression (ordinary least squares) with dummy variables we proved that crisis had implication not just for the whole level of invested financial resources but for the structure of mutual funds market as well. We showed that the crisis occurred at the world and European markets between 3rd quarter of 2007 and 1st quarter of 2009 meanwhile between 3rd quarter of 2008 and 2nd quarter of 2009 at the Czech mutual funds market. We tested these hypotheses as well: 1) influence of stock share index on the price of equity funds, 2) influence of the short interest rate on the price of money market funds, 3) influence of the long term interest rate on the price of bond funds under the conditions of the Czech mutual funds market.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".