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Creators/Authors contains: "Song, Rui"

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  1. ; ; (, Journal of the American Statistical Association)
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  2. ; ; ; (, Journal of Econometrics)
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  3. ; ; ; ; (, Journal of the American Statistical Association)
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  4. ; ; ; (, NIPS '23: Proceedings of the 37th International Conference on Neural Information Processing Systems)
    Accepted Manuscript Full Text Available
  5. ; ; ; ; ; (, Journal of the American Statistical Association)
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  7. ; ; ; ; ; ; ; ; ; ; et al (, IEEE)
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  8. ; ; (, Proceedings of Machine Learning Research)
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  9. ; ; ; (, Journal of the American Statistical Association)
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  10. ; ; (, Journal of Physics Communications)
    Abstract The problem of analyzing interconnectedness is one of today’s premier challenges in understanding systemic risk. Connections can both stabilize networks and provide pathways for contagion. The central problem in such networks is establishing global behavior from local interactions. Jiang-Lim-Yao-Ye (Jianget al2011Mathematical Programming 1271203–244) recently introduced the use of theHodge decomposition(see Lim 2020SIAM Review62685–715 for a review), a fundamental tool from algebraic geometry, to construct global rankings from local interactions (see Barbarossaet al2018(2018 IEEE Data Science Workshop (DSW), IEEE)pp 51–5; Haruna and Fujiki 2016Frontiers in Neural Circuits1077; Jiaet al2019(Proc. of the XXV ACM SIGKDD International Conf. on Knowledge Discovery & Data Mining, pp 761–71 for other applications). We apply this to a study of financial networks, starting from the Eisenberg-Noe (Eisenberg and Noe 2001Management Science47236–249) setup of liabilities and endowments, and construct a network of defaults. We then use Jiang-Lim-Yao-Ye to construct a global ranking from the defaults, which yields one way of quantifying ‘systemic importance’. 
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