Does the Design of Stablecoins Impact Their Volatility?
Bibliographic record
Abstract
In this paper, we shall compare the average volatility that characterises the main stablecoin design types with a view to answering the question of whether all stablecoin designs accomplish the goal of minimising their price fluctuations to the same degree. Our research is motivated by the lack of rigorous studies comparing volatility of different stablecoin types stressed in the literature as well as the practical importance of such a comparison from the investors’ viewpoint. We opted for a standard volatility measure, i.e., standard deviation of return rates, corrected it for autocorrelation, and detected differences between distributions of the measure in three stablecoin groups using various non-parametric tests, i.e., the Kruskal–Wallis test, the bootstrap F-test, post-hoc tests and non-parametric contrasts. We proved that stablecoins do not deliver equally on the promise to provide stable market value with tokenised funds being leaders. Tokenised funds design involves complete coverage of the stablecoin supply in units of the currency of reference as well as great dependence on the trusted third-party acting as a trustee for the collateral. Our study reveals that existing complex stablecoins designs hardly compete with this simple design in terms of volatility.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 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 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".