Causal estimation of FTX collapse on cryptocurrency: a counterfactual prediction analysis

Khalid Khan (), Adnan Khurshid () and Javier Cifuentes-Faura ()
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Khalid Khan: Hengxing University
Adnan Khurshid: Zhejiang Normal University
Javier Cifuentes-Faura: University of Murcia

Financial Innovation, 2025, vol. 11, issue 1, 1-17

Abstract: Abstract This study uses the Bayesian structural model to assess the causal effect of the futures exchange (FTX) insolvency on cryptocurrencies from October 2022 to December 14, 2022. Findings show that FTX insolvency negatively impacts cryptocurrencies. Moreover, the results indicate rapid divergence from counterfactual predictions, and the actual cryptocurrencies are consistently lower than would have been expected in the absence of the FTX collapse. Cryptocurrency is reacting strongly to the uncertainty caused by insolvency. In relative terms, the collapse of FTX has been highly detrimental to Solana and Ethereum. Furthermore, the outcomes show that cryptocurrencies would not have been negatively affected if the intervention had not occurred. FTX collapsed owing to a mismatch between the assets and liabilities. The industry is still mostly unregulated, and regulators must act quickly, highlighting the need for outstanding innovation and decentralized and trustless technology adoption.

Keywords: Cryptocurrency; FTX collapse; Causal inference; Counterfactual predicting; Bayesian structural model (search for similar items in EconPapers)
JEL-codes: E44 E66 G18 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1186/s40854-024-00690-8

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