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

arXiv: https://arxiv.org/abs/2207.13914 · HTML: https://mlsanity.com/paper/2207.13914/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Jul 2022.

## Built on by (most cited first, 9 of 9)

- [Deep Limit Order Book Forecasting](https://mlsanity.com/paper/2403.09267/) (2024)
- [Homological Neural Networks: A Sparse Architecture for Multivariate Complexity](https://mlsanity.com/paper/2306.15337/) (2023)
- [Homological Convolutional Neural Networks](https://mlsanity.com/paper/2308.13816/) (2023)
- [Topological Feature Selection](https://mlsanity.com/paper/2302.09543/) (2023)
- [DeXposure: A Dataset and Benchmarks for Inter-protocol Credit Exposure in Decentralized Financial Networks](https://mlsanity.com/paper/2511.22314/) (2025)
- [Can Blockchains Reliably Train Machine Learning Models?](https://mlsanity.com/paper/2307.07066/) (2023)
- [Information Filtering Networks: Theoretical Foundations, Generative Methodologies, and Real-World Applications](https://mlsanity.com/paper/2505.03812/) (2025)
- [Leveraging Large Language Models to Bridge Cross-Domain Transparency in Stablecoins](https://mlsanity.com/paper/2512.02418/) (2025)
- [Are Whitepaper Claims Reflected in Market Structure? A Contamination-Aware Pipeline and a Power-Limited Null](https://mlsanity.com/paper/2601.20336/) (2026)

## Abstract (arXiv)

We quantitatively describe the main events that led to the Terra project's failure in May 2022. We first review, in a systematic way, news from heterogeneous social media sources; we discuss the fragility of the Terra project and its vicious dependence on the Anchor protocol. We hence identify the crash's trigger events, analysing hourly and transaction data for Bitcoin, Luna, and TerraUSD. Finally, using state-of-the-art techniques from network science, we study the evolution of dependency structures for 61 highly capitalised cryptocurrencies during the down-market and we also highlight the absence of herding behaviour analysing cross-sectional absolute deviation of returns.