Financial Institution Multiscale Systemic Risk Spillover Network: A Wavelet Packet-MCQRNN Method

Siyu Ren and Xu Zhang

Complexity, 2026, vol. 2026, 1-13

Abstract: This paper proposes a novel network topology method that combines wavelet packet decomposition with a monotonic composite quantile regression neural network (MCQRNN). Using market data from 82 listed financial institutions spanning 2015–2025 and incorporating macroeconomic variables into the modeling framework, it aims to accurately identify the nonlinear features of multiscale systemic risk spillovers under different market conditions. The results reveal that the systemic risk spillover network of financial institutions exhibits clear multiscale frequency domain characteristics. In the risk spillover network, the banking sector consistently acts as a risk transmitter across all frequency bands, while other financial sectors serve as primary risk absorbers.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:2352898

DOI: 10.1155/cplx/2352898

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