Stock co-jump networks

Yi Ding, Yingying Li, Guoli Liu and Xinghua Zheng

Journal of Econometrics, 2024, vol. 239, issue 2

Abstract: We propose a Degree-Corrected Block Model with Dependent Multivariate Poisson edges (DCBM-DMP) to study stock co-jump dependence. To estimate the community structure, we extend the SCORE algorithm in Jin (2015) and develop a Spectral Clustering On Ratios-of-Eigenvectors for networks with Dependent Multivariate Poisson edges (SCORE-DMP) algorithm. We prove that SCORE-DMP enjoys strong consistency in community detection. Empirically, using high-frequency data of S&P 500 constituents, we construct two co-jump networks according to whether the market jumps and find that they exhibit different community features than GICS. We further show that the co-jump networks help in stock return prediction.

Keywords: Network; Community detection; Jumps; Co-jumps; Stock dependence; High-frequency data (search for similar items in EconPapers)
JEL-codes: C14 C38 C58 G17 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:239:y:2024:i:2:s030440762300057x

DOI: 10.1016/j.jeconom.2023.01.026

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