Prediction is central in finance. A growing line of research uses cross-asset signals to forecast market movements. A recent example showed that Bitcoin can serve as a strong leading indicator in a machine learning-based trading system.
Along similar lines, Reference [1] examines whether cryptocurrency overnight returns, defined as price changes during U.S. equity market closures, can predict the VIX. For this study, the authors use five-minute data of Bitcoin and Ethereum from 2018 to 2025, motivated by the idea that crypto markets are highly sensitive to sentiment, and that overnight returns capture this information. They pointed out,
This study examines the informational content of cryptocurrency returns through a novel temporal decomposition framework that aligns cryptocurrency trading activity with U.S. equity market hours. Our analysis shows that the overnight returns of both Bitcoin and Ethereum capture a distinct dimension of investor sentiment, which significantly improves the predictability of equity market volatility…
We then explore the predictive power of cryptocurrency overnight returns for VIX dynamics. In-sample analysis reveals a significantly negative relationship between cryptocurrency overnight returns and subsequent trading-hour VIX changes, indicating that positive overnight sentiment predicts a reduction in equity market uncertainty during the following trading session. Out-of-sample analysis demonstrates that models incorporating cryptocurrency overnight returns consistently outperform baseline models, with results remaining robust across subperiods and extending to other U.S. implied volatility indices. The economic significance of these findings is further validated through long-short trading strategies in VIX derivatives, where overnight-return-augmented models generate superior performance across different risk-aversion levels.
In short, the results show that crypto overnight returns have a negative predictive relationship with the VIX, with strong in-sample and out-of-sample performance. A trading strategy based on this signal is found to be profitable, and the results hold across different periods, including COVID and non-COVID regimes, and extend to other volatility indices.
Once again, the study reinforces the role of cryptocurrencies as leading indicators for broader market dynamics.
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References
[1] Gu, M., Lin, J., & Liu, S. (2026), Beyond Conventional Sentiment Indicators: Cryptocurrency’s Hidden Potential in VIX Forecasting, Economic Modelling.
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