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Anatomy of a Stablecoin's failure: the Terra-Luna case: Herding analysis

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Table of Links

Abstract and 1. Introduction

2. Data and quantitative nature of the events

2.1. Hourly data analysis

2.2. Transaction data analysis

2.3. Anchor protocol

3. Methodology

3.1. Network analysis: Triangulated Maximally Filtered Graph (TMFG)

3.2. Herding analysis

4. Results

4.1. Correlations and network analysis

4.2. Herding analysis: CSAD approach

5. Robustness analysis

6. Implications and future research

6.1. Relevance for stakeholders

6.2. Future lines of research

7. Conclusion, Acknowledgements, and References

Supplementary Material

3.2. Herding analysis

In this study, we also use the approach proposed by Chang et al. (2000) to study the possible emergence of herd behaviour during Terra collapse. This method is based on the notion of herding towards market consensus in which “herds are characterised by individuals who suppress their own beliefs and base their investment decisions solely on the collective actions of the market, even when they disagree with its predictions” (Christie and Huang, 1995). More specifically, Chang et al. (2000) analysed the existence of herding in a system of N assets through the cross-sectional absolute deviation of returns (CSAD) as a measure of return dispersion,



Authors:

(1) Antonio Briola, Department of Computer Science, University College London, Gower Street, WC1E 6EA - London, United Kingdom and UCL Centre for Blockchain Technologies, London, United Kingdom;

(2) David Vidal-Tomas (Corresponding author), Department of Computer Science, University College London, Gower Street, WC1E 6EA - London, United Kingdom, Department of Economics, Universitat Jaume I, Campus del Riu Sec, 12071 - Castellon, Spain and UCL Centre for Blockchain Technologies, London, United Kingdom ([email protected]);

(3) Yuanrong Wang, Department of Computer Science, University College London, Gower Street, WC1E 6EA - London, United Kingdom and UCL Centre for Blockchain Technologies, London, United Kingdom;

(4) Tomaso Aste, Department of Computer Science, University College London, Gower Street, WC1E 6EA - London, United Kingdom, Systemic Risk Centre, London School of Economics, London, United Kingdom, and UCL Centre for Blockchain Technologies, London, United Kingdom.


This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license.

[12] Following the corresponding literature (e.g. Chang et al., 2000; Chiang and Zheng, 2010), in Eq.(3) and Eq.(4), we used Newey-West standard errors (Newey and West, 1994).

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