Trends in Quantitative Asset Management in Europe
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study of the use of financial modeling at European asset management firms is based on interviews at asset management firms in the Benelux countries, France, Germany, Italy, the Scandinavian countries, Switzerland, and the United Kingdom. Since the fall of the market from its peak in March 2000, there have been six major changes: 1) we have seen a sharp increase in the use of modeling and quantitative techniques; 2) the performance of models has improved, and market participants now have a better understanding of models and their limits; 3) there is a growing use of multiple models and of methods to handle them; 4) there is increased use of value-based models and of factors that measure market sentiment; 5) risk management has assumed a greater role, as the handling of extreme events has gained importance; and 6) uncertainty as to the macrotrends in financial markets remains high.
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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 | 0.002 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it