The Role of Derivative Instruments in 2008Global Financial Crisis
Bibliographic record
Abstract
Global economy faced so-called the greatest crises that is mentioned after 1929 Great Depression, and that showed its first signals in housing market imbalances in the second quarter of the 2007 and increased seriousness due to bankruptcy of 158 year-old finance giant Lehman Brothers, the fifth largest investment bank. Interest rate policy post 2000 period, distortions in mortgage market, deficiencies in risk assessment and transparency, increasing risk in securitizations and increasing number of derivatives market make the financial environment riskier. These changes can be mentioned as the causes of the financial crises. In this uncontrolled expansion period houses prices implausibly raised owed to speculations and price bubbles are happened. Increasing number of derivatives contributes bubble economies and these malfunctions inevitably transmitted to real side of economy. This paper aims at uncovering the role of financial derivatives in Global Financial Crisis, its effects on real economy and trying to find out the ways of overcoming the crisis
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".