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DTSTART;TZID=Europe/Helsinki:20230119T103000
DTEND;TZID=Europe/Helsinki:20230119T113000
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SUMMARY:Julia SCHAUMBURG   (Vrije Universiteit Amsterdam) "Joint modelling and estimation of global and local cross-sectional dependence in large panels"
DESCRIPTION:The Financial Econometrics Seminar: \nTime: 10:30 pm\nDate: 19th of January 2023\nRoom 3001 \nJulia SCHAUMBURG (Vrije Universiteit Amsterdam) “Joint modelling and estimation of global and local cross-sectional dependence in large panels” \nAbstract :We propose a new unified approach to identifying and estimating spatio-temporal dependence structures in large panels. The model accommodates global cross-sectional dependence due to global dynamic factors as well as local cross-sectional dependence\, which may arise from local network structures. Model selection\, filtering of the dynamic factors\, and estimation are carried out iteratively using a new algorithm that combines the Expectation-Maximization algorithm with proximal minimization\, allowing us to efficiently maximize an l1- and l2-penalized state space likelihood function. A Monte Carlo simulation study illustrates the good performance of the algorithm in terms of determining the presence and magnitude of common factors and local spillover effects. In an empirical application\, we investigate monthly US interest rate data on 12 maturities over almost 35 years. We find that besides a changing number of global dynamic factors\, there is evidence for heterogeneous local spillover effects among neighboring maturities. Taking this heterogeneity into account substantially improves out-of-sample forecasting performance. \nJoint work : Quint Wiersma (VU) and Siem Jan Koopman (VU) \nOrganizers:\n\nJean-Michel ZAKOIAN  (CREST) \nSponsors:\nCREST \n
URL:https://crest.science/event/julia-schaumburg-vrije-universiteit-amsterdam-joint-modelling-and-estimation-of-global-and-local-cross-sectional-dependence-in-large-panels/
CATEGORIES:Finance-Insurance,Financial Econometrics
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