Bibliographic record
Abstract
Bitcoin (BTC) represents an emerging asset class, offering investors an alternative avenue for diversification across various units of exchange. The recent global banking crisis of 9 March 2023 has provided an opportunity to reflect on how Bitcoin’s perception as a speculative asset may be evolving. This paper analyzes the volatility behavior of BTC in comparison to gold and the traditional financial market using GARCH models. Additionally, we have developed and incorporated a bank index within our volatility analysis framework, aiming to isolate the impact of financial crises while minimizing idiosyncratic risk. The aim of this work is to understand Bitcoin’s perception among investors and, more importantly, to determine whether BTC can be considered a new asset class. Our findings show that in terms of volatility and price, BTC and gold have responded in very similar ways. Counterintuitively, the financial market seems not to have experienced high volatility and significant price swings in response to the March 9th crisis. This suggests a consumer tendency to seek refuge in both Bitcoin and gold.
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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 | 0.006 |
| 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 | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".