# Lead Behaviour in Bitcoin Markets

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## Abstract

**:**

## 1. Introduction

## 2. Proposal

## 3. Data

## 4. Empirical Findings

## 5. Conclusions

## Author Contributions

## Funding

## Acknowledgments

## Conflicts of Interest

## References

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1. | The BTC transactions are reported in Satoshi values, the smallest fraction of a BTC, where 1 BTC = 100,000,000 Satoshi. |

**Figure 1.**Daily volume transactions (expressed in logarithms) of the 10 groups displayed as boxplots, where the left boxplot represents the first group and the right one the ten groups of the respective continent. The scatter plot displays the accumulated log transaction size of the 10 groups. The time period goes from 25 February 2012 until 17 July 2017 in all 6 continents.

**Table 1.**Descriptive statistics of the accumulated log transactions of the 6 regions Africa (Af), Asia (As), Europe (Eu), North America (N_A), Oceania (Oc), South America (S_A). Eu and N_A show a related behavior in terms of the descriptive statistics, as so do As and Oc. Also Af and S_A behave related.

Af | As | Eu | N_A | Oc | S_A | |
---|---|---|---|---|---|---|

mean | 142.25 | 193.77 | 232.18 | 230.45 | 186.60 | 155.80 |

sd | 72.84 | 19.81 | 11.59 | 9.18 | 24.55 | 62.39 |

skewness | −1.30 | −4.81 | −0.86 | −1.61 | −4.59 | −1.91 |

kurtosis | 2.98 | 44.71 | 5.27 | 10.50 | 34.79 | 5.12 |

min | 0.00 | 0.00 | 162.72 | 154.25 | 0.00 | 0.00 |

max | 222.76 | 240.14 | 257.76 | 254.96 | 235.36 | 228.09 |

**Table 2.**Comparison between the root mean square errors obtained with our full VAR model and with a model composed by the solely autoregressive component.

Group | RMSE_Full | RMSE_AR | Group | RMSE_Full | RMSE_AR |
---|---|---|---|---|---|

Africa1 | 0.1945 | 0.2052 | N_A1 | 0.2495 | 0.2500 |

Africa2 | 0.1298 | 0.1315 | N_A2 | 0.4590 | 0.4613 |

Africa3 | 0.1600 | 0.1584 | N_A3 | 0.5523 | 0.5596 |

Africa4 | 0.1521 | 0.1538 | N_A4 | 0.3241 | 0.3631 |

Africa5 | 0.1492 | 0.1460 | N_A5 | 0.8437 | 0.8530 |

Africa6 | 0.1609 | 0.1538 | N_A6 | 1.2396 | 1.2653 |

Africa7 | 0.1385 | 0.1419 | N_A7 | 0.9865 | 0.9951 |

Africa8 | 0.1382 | 0.1371 | N_A8 | 0.8721 | 0.9041 |

Africa9 | 0.1276 | 0.1250 | N_A9 | 0.6895 | 0.6962 |

Africa10 | 0.0960 | 0.0979 | N_A10 | 1.2575 | 1.2698 |

Asia1 | 0.2258 | 0.2286 | Oceania1 | 0.3182 | 0.3209 |

Asia2 | 0.2340 | 0.2264 | Oceania2 | 0.2447 | 0.2477 |

Asia3 | 0.3148 | 0.3173 | Oceania3 | 0.3717 | 0.3655 |

Asia4 | 0.3479 | 0.3432 | Oceania4 | 0.4795 | 0.4914 |

Asia5 | 0.4328 | 0.4501 | Oceania5 | 0.4909 | 0.5057 |

Asia6 | 0.5425 | 0.5493 | Oceania6 | 0.5837 | 0.5782 |

Asia7 | 0.6143 | 0.6064 | Oceania7 | 0.5857 | 0.5965 |

Asia8 | 0.6403 | 0.6455 | Oceania8 | 0.8265 | 0.8353 |

Asia9 | 0.5294 | 0.6863 | Oceania9 | 0.3350 | 0.3255 |

Asia10 | 0.5565 | 0.5623 | Oceania10 | 0.2659 | 0.2733 |

Europe1 | 0.0558 | 0.0572 | S_A1 | 0.2577 | 0.2663 |

Europe2 | 0.1414 | 0.1433 | S_A2 | 0.2162 | 0.2183 |

Europe3 | 0.1779 | 0.1894 | S_A3 | 0.2315 | 0.2326 |

Europe4 | 0.1405 | 0.1423 | S_A4 | 0.2307 | 0.2302 |

Europe5 | 0.1822 | 0.1839 | S_A5 | 0.2196 | 0.2231 |

Europe6 | 0.2241 | 0.2257 | S_A6 | 0.2227 | 0.2234 |

Europe7 | 0.2852 | 0.2880 | S_A7 | 0.2152 | 0.2145 |

Europe8 | 0.3673 | 0.3688 | S_A8 | 0.2052 | 0.2061 |

Europe9 | 0.4021 | 0.4028 | S_A9 | 0.1970 | 0.1960 |

Europe10 | 0.3460 | 0.3481 | S_A10 | 0.1749 | 0.1757 |

Lambda 0.001 | Lambda 0.01 | |||
---|---|---|---|---|

Positive | Negative | Positive | Negative | |

Within Europe | 17 | 14 | 17 | 13 |

Within North America | 21 | 13 | 19 | 13 |

Between Europe and North America | 48 | 53 | 45 | 48 |

$\mathit{\lambda}=0.001$ | $\mathit{\lambda}=0.01$ | $\mathit{\lambda}=0.25$ | $\mathit{\lambda}=0.5$ | |
---|---|---|---|---|

Average degree | 1.189206937 | 1.157479 | 0.855028 | 0.663931 |

Average betweenness | 270.5666667 | 288.5667 | 269 | 39.3 |

Average closeness | 0.000448235 | 0.000428 | 0 | 0 |

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Chen, Y.; Giudici, P.; Hadji Misheva, B.; Trimborn, S.
Lead Behaviour in Bitcoin Markets. *Risks* **2020**, *8*, 4.
https://doi.org/10.3390/risks8010004

**AMA Style**

Chen Y, Giudici P, Hadji Misheva B, Trimborn S.
Lead Behaviour in Bitcoin Markets. *Risks*. 2020; 8(1):4.
https://doi.org/10.3390/risks8010004

**Chicago/Turabian Style**

Chen, Ying, Paolo Giudici, Branka Hadji Misheva, and Simon Trimborn.
2020. "Lead Behaviour in Bitcoin Markets" *Risks* 8, no. 1: 4.
https://doi.org/10.3390/risks8010004