Dynamic Volatility Spillovers Between Global Volatility Indices and the Magnificent Seven: What Drives System-Wide Volatility Connectedness?

Abstract

This study examines the dynamic connectedness between the daily volatility series of global volatility indices (VIX, OVX, and GVZ) and those of the Magnificent Seven companies using data from 22 May 2012 to 25 June 2026. The analysis employs the time-varying parameter vector autoregressive (TVP-VAR) connectedness framework to decompose volatility transmission into within-group and cross-group spillovers. Unlike conventional connectedness analyses that focus primarily on aggregate connectedness measures, this decomposition identifies the dominant source of system-wide volatility connectedness. The results reveal a moderate but highly dynamic transmission structure that intensifies during periods of heightened market stress, particularly during the COVID-19 pandemic. The decomposition further reveals that, although the system incorporates equity-, oil-, and gold-market uncertainty through the VIX, OVX, and GVZ, cross-group spillovers between the global volatility indices and the Magnificent Seven remain comparatively limited. Instead, system-wide connectedness is driven primarily by within-group interactions among the Magnificent Seven. Apple, Meta, and Amazon emerge as net volatility transmitters, whereas Microsoft, Alphabet, and NVIDIA act as net receivers. Pairwise spillovers strengthen during major stress episodes, particularly in the VIX–Apple, VIX–Meta, and Amazon–Meta relationships. The main connectedness patterns remain robust across alternative forecast horizons, lag specifications, rolling-window lengths, and the Diebold –Yilmaz connectedness framework. Overall, the findings highlight the dominant role of within-group spillovers in shaping system-wide connectedness and provide practical insights for portfolio diversification, risk management, and hedging.