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dc.contributor.authorGe, S.
dc.date.accessioned2021-01-05T10:28:09Z
dc.date.available2021-01-05T10:28:09Z
dc.date.issued2020-11-26
dc.identifier.otherCWPE20115
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/315716
dc.description.abstractThis paper uses extensive text data to construct firms' links via which local shocks transmit. Using the novel text-based linkages, I estimate a heterogeneous spatial-temporal model which accommodates the contemporaneous and dynamic spillover effects at the same time. I document a considerable degree of local risk spillovers in the market plus sector hierarchical factor model residuals of S&P 500 stocks. The method is found to outperform various previously studied methods in terms of out-of-sample fit. Network analysis of the spatial-temporal model identifies the major systemic risk contributors and receivers, which are of particular interest to microprudential policies. From a macroprudential perspective, a rolling-window analysis reveals that the strength of local risk spillovers increases during periods of crisis, when, on the other hand, the market factor loses its importance.
dc.publisherFaculty of Economics, University of Cambridge
dc.relation.ispartofseriesCambridge Working Papers in Economics
dc.rightsAll Rights Reserved
dc.rights.urihttps://www.rioxx.net/licenses/all-rights-reserved/
dc.subjectExcess co-movement
dc.subjectweak and strong cross-sectional dependence
dc.subjectlocal risk spillovers
dc.subjectnetworks
dc.subjecttextual analysis
dc.subjectbig data
dc.subjectsystemic risk
dc.subjectheterogeneous spatial auto-regressive model (HSAR)
dc.titleText-Based Linkages and Local Risk Spillovers in the Equity Market
dc.typeWorking Paper
dc.identifier.doi10.17863/CAM.62830


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