Detecting Giver and Receiver Spillover Groups in Large Vector Autoregressions

45 Pages Posted: 21 Jan 2022 Last revised: 2 Aug 2022

Date Written: December 13, 2021

Abstract

I propose an algorithm that partitions the series of a large vector autoregression (VAR) into groups based on the spillover structure. The novelty of the procedure is that it is capable of simultaneously detecting both the giver and receiver group structures. I study the properties of the algorithm when the data are generated by a class of network-based VAR models and show that it consistently detects the groups within this class. The methodology is applied to study the spillover group structure in a panel of volatility measures for the constituents of the S&P 100.

Keywords: Vector Autoregressions, Random Graphs, Community Detection, Spectral Clustering

JEL Classification: C3, C32, C55

Suggested Citation

Gudmundsson, Gudmundur, Detecting Giver and Receiver Spillover Groups in Large Vector Autoregressions (December 13, 2021). Available at SSRN: https://ssrn.com/abstract=3983635 or http://dx.doi.org/10.2139/ssrn.3983635

Gudmundur Gudmundsson (Contact Author)

Aarhus BSS ( email )

Fuglesangs Allé 4
Aarhus V, 8210
Denmark

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