Conditional Integration of AI Equities with Traditional and Alternative Assets: Evidence from Wavelet Coherence and Time-Varying Connectedness

This study examines whether the equities of leading artificial intelligence (AI) firms were integrated with Bitcoin, gold, West Texas Intermediate (WTI) crude oil and clean energy from January 2018 to July 2026. Using an equally weighted index of NVIDIA, Apple, Alphabet and Microsoft, we combine wavelet coherence, time-varying parameter vector autoregressive (TVP-VAR) connectedness and time-varying Granger causality, complemented by windowed scalogram difference and variance decomposition analyses. Dependence is time-varying and horizon-dependent: significant co-movements concentrate around the COVID-19 crash, the 2022 inflation and monetary tightening shock, and the AI-driven boom. Average total connectedness was low (20.23%) but exceeded 50% in March 2020. Clean energy and the AI index are net transmitters of shocks, whereas Bitcoin, gold and oil are net receivers; however, much of the transmitting role of AI equities reflects their exposure to the broad equity market. Lagged predictability is episodic, and AI equities are almost never predicted by the other assets. The results are robust to ex ante AI exchange-traded funds, alternative model specifications, weekly data and Brent oil. AI equities therefore appear only conditionally integrated with other asset classes, and diversification benefits observed in calm periods should not be assumed to persist during stress episodes.

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Publication Details

Journal
Journal of risk and financial management
Published
2026-11-09
DOI
https://doi.org/10.3390/jrfm19110907
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
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article

Conditional Integration of AI Equities with Traditional and Alternative Assets: Evidence from Wavelet Coherence and Time-Varying Connectedness

Heni Boubaker, Nadia Farjallah
Journal of risk and financial management
Market Dynamics and Volatility
article

Conditional Integration of AI Equities with Traditional and Alternative Assets: Evidence from Wavelet Coherence and Time-Varying Connectedness

Heni Boubaker, Nadia Farjallah
article en

Abstract

This study examines whether the equities of leading artificial intelligence (AI) firms were integrated with Bitcoin, gold, West Texas Intermediate (WTI) crude oil and clean energy from January 2018 to July 2026. Using an equally weighted index of NVIDIA, Apple, Alphabet and Microsoft, we combine wavelet coherence, time-varying parameter vector autoregressive (TVP-VAR) connectedness and time-varying Granger causality, complemented by windowed scalogram difference and variance decomposition analyses. Dependence is time-varying and horizon-dependent: significant co-movements concentrate around the COVID-19 crash, the 2022 inflation and monetary tightening shock, and the AI-driven boom. Average total connectedness was low (20.23%) but exceeded 50% in March 2020. Clean energy and the AI index are net transmitters of shocks, whereas Bitcoin, gold and oil are net receivers; however, much of the transmitting role of AI equities reflects their exposure to the broad equity market. Lagged predictability is episodic, and AI equities are almost never predicted by the other assets. The results are robust to ex ante AI exchange-traded funds, alternative model specifications, weekly data and Brent oil. AI equities therefore appear only conditionally integrated with other asset classes, and diversification benefits observed in calm periods should not be assumed to persist during stress episodes.

Journal of risk and financial managementVol. 19(11)
University of Sousse (TN)
Market Dynamics and Volatility
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