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Can Banking Intermediates Crowd Out Their High‐Tech Promising Successors? A Financial Stress Perspective

Nikolaos A. Kyriazis et al.

International Journal of Finance & Economics2026https://doi.org/10.1002/ijfe.70183article
AJG 3ABDC B
Weight
0.50

What the paper says

This study examines the evolving relationship between large U.S. Financial institutions and Big Tech firms amid rising financial stress driven by global crises, including the COVID‐19 pandemic, the Russia‐Ukraine war, and inflationary shocks. Using weekly data from January 2013 to December 2024, the study employs the Quantile‐VAR (Q‐VAR) framework and the Financial Stress Index (FSI) to evaluate net pairwise and extended joint connectedness across various market regimes. Findings reveal that most Big Tech stocks affect financial stress but this reverses in bull markets. Bank stocks’ causal footprint on financial stress is obvious in all conditions and Morgan Stanley concentrates and leads systemic causality in bull markets. Overall, Big Tech stocks display weaker connection with the FSI but play a major role in bear markets, the Covid‐19 and the Russia‐Ukraine war crises. The results suggest that technology firms are poised to play an increasingly dominant role in financial intermediation, potentially merging with or replacing traditional banks, especially during future crises, offering critical insights for investors, regulators, and policymakers.

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https://doi.org/https://doi.org/10.1002/ijfe.70183

Or copy a formatted citation

@article{nikolaos2026,
  title        = {{Can Banking Intermediates Crowd Out Their High‐Tech Promising Successors? A Financial Stress Perspective}},
  author       = {Nikolaos A. Kyriazis et al.},
  journal      = {International Journal of Finance & Economics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1002/ijfe.70183},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.