Macro-Financial Spillovers between Stock Markets & Cryptocurrencies
This paper investigates the macro-financial spillovers between major U.S. technology equities and leading cryptocurrencies by applying a Quantile Vector Autoregression (QVAR) framework. Using daily data from November 2017 to October 2023, we examine the dynamic connectedness across asset classes at...
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| Autores principales: | , , , , |
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| Formato: | Article ou chapitre numérique |
| Lenguaje: | Français |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | Accès Université d'Orléans et IFPM Accès Université d'Orléans et IFPM |
| Sumario: | This paper investigates the macro-financial spillovers between major U.S. technology equities and leading cryptocurrencies by applying a Quantile Vector Autoregression (QVAR) framework. Using daily data from November 2017 to October 2023, we examine the dynamic connectedness across asset classes at various points of the return distribution, with particular emphasis on the tails, where systemic risk typically amplifies. Our findings reveal that while average connectedness is substantial, the intensity of spillovers is markedly asymmetric and concentrated in extreme quantiles, indicative of heightened interdependence during periods of financial stress or exuberance. Cryptocurrencies, act as net transmitters of volatility to certain tech equities under adverse market conditions, despite exhibiting limited spillover in normal times. These results highlight the evolving macroeconomic relevance of digital assets and the necessity of integrating quantile-based measures into macroprudential surveillance frameworks, suggesting that stress-testing models and financial stability frameworks, must be accompanied by these tail interconnectedness models, aiming at regularly assessing the cross-market tail dependencies. Finally, the paper provides significant insights for central banks, policy-makers, and institutional investors, with reference to the design of complex macro-financial monitoring, risk management techniques, and asset allocations. JEL Classification: C32, C58, D53, E44, E60, G10 |
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