Contagion in Bitcoin Networks

Coquidé, Célestin; Lages, José; Shepelyansky, Dima L.

doi:10.1007/978-3-030-36691-9_18

Cited by 8 publications

(6 citation statements)

References 23 publications

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“…The WTN crisis contagion model is described by the Algorithm 1. This contagion model has already been used to analyze the crisis contagion in the bitcoin transaction network (Coquidé et al 2019c).…”

Section: Contagion Modelmentioning

confidence: 99%

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Crisis contagion in the world trade network

2020

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We present a model of worldwide crisis contagion based on the Google matrix analysis of the world trade network obtained from the UN Comtrade database. The fraction of bankrupted countries exhibits an on-off phase transition governed by a bankruptcy threshold κ related to the trade balance of the countries. For κ>κc, the contagion is circumscribed to less than 10% of the countries, whereas, for κ<κc, the crisis is global with about 90% of the countries going to bankruptcy. We measure the total cost of the crisis during the contagion process. In addition to providing contagion scenarios, our model allows to probe the structural trading dependencies between countries. For different networks extracted from the world trade exchanges of the last two decades, the global crisis comes from the Western world. In particular, the source of the global crisis is systematically the Old Continent and The Americas (mainly US and Mexico). Besides the economy of Australia, those of Asian countries, such as China, India, Indonesia, Malaysia and Thailand, are the last to fall during the contagion. Also, the four BRIC are among the most robust countries to the world trade crisis.

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Section: Contagion Modelmentioning

confidence: 99%

“…The detailed UN Comtrade database, collected for about 50 years, allows to perform a thorough modeling of the crisis contagion in the WTN. In the following, we use the contagion model inspired by the analysis of the crisis in the Bitcoin transactions network presented in Ermann et al (2018); Coquidé et al (2019c).…”

Section: Introductionmentioning

confidence: 99%

Crisis contagion in the world trade network

2020

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“…The WTN crisis contagion model is described by the Algorithm 1. This contagion model has already been used to analyze the crisis contagion in the bitcoin transaction network [13].…”

Section: Contagion Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Crisis contagion in the world trade network

Coquidé,

Lages,

Shepelyansky

2020

Preprint

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We present a model of worldwide crisis contagion based on the Google matrix analysis of the world trade network obtained from the UN Comtrade database. The fraction of bankrupted countries exhibits an on-off phase transition governed by a bankruptcy threshold κ related to the trade balance of the countries. For κ > κ c , the contagion is circumscribed to less than 10% of the countries, whereas, for κ < κ c , the crisis is global with about 90% of the countries going to bankruptcy. We measure the total cost of the crisis during the contagion process. In addition to providing contagion scenarios, our model allows to probe the structural trading dependencies between countries. For different networks extracted from the world trade exchanges of the last two decades, the global crisis comes from the Western world. In particular, the source of the global crisis is systematically the Old Continent and The Americas (mainly US and Mexico). Besides the economy of Australia, those of Asian countries, such as China, India, Indonesia, Malaysia and Thailand, are the last to fall during the contagion. Also, the four BRIC are among the most robust countries to the world trade crisis.

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“…Coquidé et al [ 21 ] applied the reduced Google matrix (REGOMAX) algorithm on the United Nations COMTRADE database in order to analyze the multiproduct world trade in the years 2004–2016. They also applied REGOMAX [ 22 ] to the bitcoin network, where the nodes are the users and transactions are the edges. From PageRank and CheiRank probabilities, analogous to trade import and export, they specified the dimensionless trade balance of each user and modeled the contagion propagation on the network.…”

Section: Introductionmentioning

confidence: 99%

Competitive Conditions in Global Value Chain Networks: An Assessment Using Entropy and Network Analysis

Angelidis

Ioannidis

Makris

et al. 2020

Entropy

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We investigated competitive conditions in global value chains (GVCs) for a period of fifteen years (2000–2014), focusing on sector structure, countries’ dominance and diversification. For this purpose, we used data from the World Input–Output Database (WIOD) and examined GVCs as weighted directed networks, where countries are the nodes and value added flows are the edges. We compared the in-and out-weighted degree centralization of the sectoral GVC networks in order to detect the most centralized, on the import or export side, respectively (oligopsonies and oligopolies). Moreover, we examined the in- and out-weighted degree centrality and the in- and out-weight entropy in order to determine whether dominant countries are also diversified. The empirical results reveal that diversification (entropy) and dominance (degree) are not correlated. Dominant countries (rich) become more dominant (richer). Diversification is not conditioned by competitiveness.

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Contagion in Bitcoin Networks

Cited by 8 publications

References 23 publications

Crisis contagion in the world trade network

Crisis contagion in the world trade network

Crisis contagion in the world trade network

Competitive Conditions in Global Value Chain Networks: An Assessment Using Entropy and Network Analysis

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