# Does the Design of Stablecoins Impact Their Volatility?

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## Abstract

**:**

## 1. Introduction

## 2. Materials and Methods

## 3. Results

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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1 | As of 22 October 2020 according to coinmarketcap.com. |

2 | A fascinating look into the various ways stablecoin designers interpret the idea of stability can be found in The state of stablecoins report by Samman and Masanto (2019). |

**Figure 1.**ACF estimates. Source: authors’ own calculations based on data sourced from coinmarketcap.com.

**Figure 2.**ACF estimates. Source: authors’ own calculations based on data sourced from coinmarketcap.com.

**Table 1.**A ranking of 20 stablecoins included in the study according to the SD of daily returns (in percentage points).

Name | Peg | Volatility (in p.p.) | Type |
---|---|---|---|

Paxos | USD | 0.457619 | tokenised funds |

USD Coin | USD | 0.552184 | tokenised funds |

StableUSD (Stably) | USD | 0.640032 | tokenised funds |

TrueUSD | USD | 0.770574 | tokenised funds |

Gemini Dollar | USD | 1.194509 | tokenised funds |

Dai | USD | 1.48214 | collateralised (on-chain) |

Stasis Euro | EUR | 1.510869 | tokenised funds |

Tether | USD | 2.165575 | tokenised funds |

Terra | SDR | 3.956304 | algorithmic |

Aurora | USD | 6.762596 | collateralised (on-chain) |

PHI | USD | 7.334355 | collateralised (on-chain) |

BitShares | USD | 7.444987 | collateralised (on-chain) |

NuBits | USD | 8.58101 | algorithmic |

Moneytoken (IMT) | USD | 9.119281 | collateralised (on-chain) |

Steem | USD | 10.03096 | algorithmic |

BridgeCoin (SweetBridge) | USD | 10.41627 | collateralised (off-chain) |

MinexCoin | USD | 10.49871 | collateralised (on-chain) |

Alchemint | USD | 11.82065 | collateralised (on-chain) |

White Standard | USD | 15.04977 | tokenised funds |

bitUSD | USD | 16.01225 | collateralised (on-chain) |

Null Hypothesis | Normality of Residuals | Homogeneity of Variances | |||
---|---|---|---|---|---|

Test | Shapiro–Wilk Normality Test | Kolmogorov–Smirnov Test | Bartlett Test | Fligner–Killeen Test | Levene Test |

Value of the test statistic | 0.8619 | 0.45004 | 0.64207 | 2.2536 | 0.0965 |

df | - | - | 2 | 2 | 2 |

p-value | 0.008491 | 0.000324 | 0.7254 | 0.3241 | 0.9085 |

Test | Kruskal–Wallis Test | Bootstrap F-Test |
---|---|---|

Value of the test statistic | 7.4258 (df = 2) | 4.4291 |

p-value | 0.02441 (chi-square) | 0.0239 |

Test | Tested Groups | Value of the Test Statistic | p-Value |
---|---|---|---|

Pairwise Wilcoxon–Mann–Whitney U test with Holm correction | collateralised—algorithmic | - | 0.600 |

tokenised funds—algorithmic | - | 0.170 | |

tokenised funds—collateralised | - | 0.033 | |

Dunn test (p-values adjusted with Benjamini–Hochberg method) | collateralised—algorithmic | −0.3662335 | 0.714 |

tokenised funds—algorithmic | 1.5500663 | 0.182 | |

tokenised funds—collateralised | 2.6621153 | 0.023 |

Contrasts * | Estimator | Confidence Interval | Test Statistic | p-Value |
---|---|---|---|---|

[0.5, 0.5, −1] | 0.368 | (0.003, 0.733) | 3.131 | 0.048 |

[1, −1, 0] | −0.082 | (−0.484, 0.321) | −0.630 | 0.813 |

[1, 0, −1] | 0.327 | (−0.084, 0.737) | 2.470 | 0.110 |

[0, 1, −1] | 0.409 | (−0.013, 0.831) | 3.006 | 0.056 |

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Jarno, K.; Kołodziejczyk, H. Does the Design of Stablecoins Impact Their Volatility? *J. Risk Financial Manag.* **2021**, *14*, 42.
https://doi.org/10.3390/jrfm14020042

**AMA Style**

Jarno K, Kołodziejczyk H. Does the Design of Stablecoins Impact Their Volatility? *Journal of Risk and Financial Management*. 2021; 14(2):42.
https://doi.org/10.3390/jrfm14020042

**Chicago/Turabian Style**

Jarno, Klaudia, and Hanna Kołodziejczyk. 2021. "Does the Design of Stablecoins Impact Their Volatility?" *Journal of Risk and Financial Management* 14, no. 2: 42.
https://doi.org/10.3390/jrfm14020042