Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/339741 
Year of Publication: 
2026
Citation: 
[Journal:] Financial Internet Quarterly [ISSN:] 2719-3454 [Volume:] 22 [Issue:] 1 [Year:] 2026 [Pages:] 46-66
Publisher: 
University of Information Technology and Management, Rzeszów
Abstract: 
This study investigates the volatility spillover dynamics between the VIX fear index and the Magnificent Seven technology stocks - namely Microsoft, Apple, Nvidia, Amazon, Alphabet, Meta Platforms, and Tesla - over the period of June 2012 to March 2024. To achieve this objective, the variance causality test is employed to detect potential volatility transmissions among the series. Preliminary diagnostic tests confirm the validity of the GARCH (1,1) specification for all individual return series. The results from the variance causality analysis indicate significant volatility spillovers from the VIX to the conditional variances of Microsoft, Alphabet, Meta Platforms, Nvidia, and Amazon stocks. Building on these findings, impulse-response functions and variance decomposition analyses are conducted based on the conditional variance series estimated through the GARCH (1,1) model. The impulse-response analysis reveals that a positive shock in the VIX generates a temporary increase in the conditional volatility of Apple, Alphabet, Nvidia, and Tesla stocks, which gradually diminishes over time. Conversely, a VIX shock induces a negative volatility response in Meta Platforms, Microsoft, and Amazon stocks, although these effects also fade and converge to zero in the long run. Variance decomposition results further show that, in the short term, the volatility of each technology stock is predominantly driven by its own internal dynamics. However, as the forecast horizon extends, the influence of the VIX index becomes increasingly pronounced, underscoring its role as a significant external volatility driver. These findings imply that investors' perceptions of heightened risk - captured by the VIX index - are effectively transmitted to technology stock markets. Accordingly, the incorporation of the VIX index into volatility forecasting models can enhance prediction accuracy. From a practical standpoint, the study underscores the importance of monitoring the fear index when developing portfolio allocation and risk management strategies-oriented equities.
Subjects: 
Volatility
Volatility Spillover
Technology Stock
JEL: 
G11
G15
G17
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.