RSFAS Seminar Series – Yingying Li

seminar events banner

A seminar by Yingying Li from Hong Kong University of Technology

Title: Stock co-jump networks

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.

For further information, please contact RSFAS Seminars.

All information collected by the University is governed by the ANU Privacy Policy.

Event Details

Start Date
End Date
Allan Barton Forum