A crypto-stock weekend effect: Predicting Monday stock returns using weekend cryptocurrency returns

Mathis Mourey (), Mohamad Shahrour and Florentina Şoiman ()
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Mathis Mourey: The Hague University of Applied Sciences, CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes
Mohamad Shahrour: HBKU - Hamad Bin Khalifa University [Doha, Qatar]
Florentina Şoiman: CERAG - Centre d'études et de recherches appliquées à la gestion - UGA - Université Grenoble Alpes

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Abstract: This study examines the predictive power of weekend cryptocurrency performance on Monday stock returns. Using a Bayesian framework and Kalman filter, we analyze 20 of the largest cryptocurrencies, covering about 85% of market capitalization. Our results show a strong asymmetry: negative weekend returns significantly predict Monday equity declines, while positive returns have no effect. This pattern remains robust across benchmarks, including the Nasdaq, Russell 2000, S&P sector indices, and the S&P Crypto Index. The transmission mechanism strengthens markedly after the May 2022 LUNA collapse, signaling a structural break in crypto-equity dynamics. Our findings highlight the growing role of cryptocurrencies as transmitters of systemic risk and carry implications for forecasting, portfolio management, and financial stability monitoring.

Keywords: Weekend effect; Information; Bayesian; Cryptocurrency; Stock indices (search for similar items in EconPapers)
Date: 2025-10-17
Note: View the original document on HAL open archive server: https://hal.science/hal-05415054v1
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Published in Finance Research Letters, 2025, 86, pp.108661. ⟨10.1016/j.frl.2025.108661⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05415054

DOI: 10.1016/j.frl.2025.108661

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