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

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

2.2. Transaction data analysis

o provide a complete overview of Terra project’s collapse, we analyse public trades (i.e. transaction data) for BTC, LUNA and UST. Compared to hourly prices, which are retrieved from CryptoCompare database (CryptoCompare, 2022), this new dataset is directly sourced from Kraken digital currency exchange using CCXT (Ccxt, 2022) Python package. Figure 2 reports hourly imbalances: positive values denote a selling pressure, while negative ones denote a buying pressure.[8] We observe interesting features that could be related to some of the events introduced in Section 1. First, on 05 May 2022 (a), we identify a strong, positive imbalance for BTC, with a value comparable to those detected during the main collapse of LUNA and UST (i.e. from 09 to 11 May 2022 (c-d)). We do not observe comparable high positive imbalance values for LUNA and UST on the same date. Therefore, even though we cannot confirm that short selling positions were opened against BTC as described by different social media sources (Hall, 2022; Ashmore, 2022; Locke, 2022), we remark the presence of a considerable selling pressure on this cryptoasset. In other words, if short selling positions were truly opened against BTC, 05 May 2022 should be the most plausible day in which this happened.[9] Second, focusing on the UST behaviour, we underline the existence of a remarkable selling pressure since 09 May 2022 (i.e. after the second UST de-pegging). This finding is particularly relevant, since the selling pressure after the first UST de-pegging (b) was remarkably lower than the second one, which could be in line with social media news when contending that attackers caused panic by selling whale-size UST holdings (Hall, 2022; Ashmore, 2022; Locke, 2022). This strategy would be similar to the one used to bring down Iron Finance, given that attackers waited to the second de-pegging, taking advantage of the uncertainty that already dominated the market (Finematics, 2021). Last but not least, it is relevant to emphasise that we cannot confirm the existence of a coordinated attack executed by related market agents. Indeed, the potential short selling against BTC and the Terra attack could have occurred at the same time by chance, in the context of a global economic uncertainty. In the case of Iron Finance collapse, no coordinated attack using a third cryptoasset was detected (Finematics, 2021).

[8] In order to compute the imbalance, we firstly distinguish between public trades on the buy and sell side. We then multiply the volume of each transaction and the price at which it is executed, obtaining the transaction’s costs. We aggregate resulting transactions’ costs by hour. We finally subtract buy hourly transactions costs from sell hourly transactions costs.