Risk spillovers between the financial market and macroeconomic sectors under mixed-frequency information: A frequency domain perspective
Year: 2025
Type: article
Abstract: We construct the Mixed-Frequency Vector Autoregression of Frequency Domain Decomposition model, labeled as MF-VAR-FDD, to investigates the risk spillovers between financial market and the macroeconomic sectors. The MF-VAR-FDD innovatively introduces the spectral density function into the Mixed-Frequency Vector Autoregression (MF-VAR) model, providing a spectral representation of the generalized variance decomposition of the MF-VAR model. It decomposes time domain risk spillovers into high-frequency and low-frequency components, constructs the Mixed-Frequency Frequency Domain Spillover (MFFDS) index, and characterizes risk spillovers between finance and macroeconomic sectors at different frequencies from a frequency domain perspective. The research findings are as follows: First, during major crises, frequency domain risk spillover significantly intensifies, exhibiting notable time-varying characteristics. Moreover, risk spillover is mainly dominated by low-frequency spillover, while high-frequency spillover is more sensitive to crisis events, enabling more agile monitoring of market disturbances and aiding in risk prevention. Second, finance consistently represents a net risk exporter to all macroeconomic sectors, emphasizing that financial risk should remain a key focus for national regulatory authorities. Our conclusions provide additional information for the formulation of macroprudential policies.
Authors: Mengting Li, Xiaofu Ma, Junsheng Jia, Chen Zhu
Institution: Nanjing University of Finance and Economics
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,930
Funders: National Natural Science Foundation of China, National Office for Philosophy and Social Sciences, Major Basic Research Project of the Natural Science Foundation of the Jiangsu Higher Education Institutions, Natural Science Research of Jiangsu Higher Education Institutions of China, National Social Science Fund of China
Awards: G2168977003, G3026968021, G4503582433
OpenAlex ID: W4407947241
