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X-WR-CALDESC:Events for CREST
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TZID:Europe/Helsinki
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TZOFFSETFROM:+0200
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DTSTART:20250330T010000
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DTSTART;TZID=Europe/Helsinki:20251106T100000
DTEND;TZID=Europe/Helsinki:20251106T230000
DTSTAMP:20260711T104128
CREATED:20250930T060319Z
LAST-MODIFIED:20251022T090910Z
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SUMMARY:Jordi LLORENS-TERRAZAS (University of SURREY)  "Monitoring Joint Tail Risks: An Application to Growth and Inflation"
DESCRIPTION:Finance-Insurance\nTime: 10.00 am\nDate:06th of November 2025\nRoom 3001 \nJordi LLORENS-TERRAZAS (University of SURREY) “Monitoring Joint Tail Risks: An Application to Growth and Inflation” \nAbstract :This paper develops the concept of Growth and Inflation at Risk frontier (GIaR). This is a bivariate generalisation of the concepts of Growth-at-Risk (GaR) and Inflation-at-Risk (IaR). We propose a novel approach to identify and estimate GIaR and provide uniformly valid upper and lower confidence bands. We first apply our procedure to predict the conditional probability of stagflation. Second\, we compute worst-case scenarios for a policy maker who is concerned about the joint tail risk of low growth and high inflation. We study the effect that a tightening of financial conditions has on the joint tail risks. \n  \nOrganizers:  Zakoian Jean-Michel \n  \n
URL:https://crest.science/event/jordi-llorens-terrazas-university-of-surrey-monitoring-joint-tail-risks-an-application-to-growth-and-inflation/
CATEGORIES:Finance-Insurance,Seminars
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DTSTART;TZID=Europe/Helsinki:20251106T110000
DTEND;TZID=Europe/Helsinki:20251106T120000
DTSTAMP:20260711T104128
CREATED:20250711T064840Z
LAST-MODIFIED:20251003T070857Z
UID:18222-1762426800-1762430400@crest.science
SUMMARY:Jérémy LEYMARIE (Clermont School of Business)  "Multivariate Inference for Dynamic Systemic Risk Measures"
DESCRIPTION:Finance-Insurance\nTime: 11.00 am\nDate:06th of November 2025\nRoom 3001 \nJérémy LEYMARIE (Clermont School of Business) “Multivariate Inference for Dynamic Systemic Risk Measures” \nAbstract : This paper introduces a system perspective on inference for standard dynamic systemic risk measures. In particular\, we provide a multivariate GARCH-type framework to analytically quantify confidence and prediction intervals of marginal expected shortfall (MES) and delta conditional value-at-risk (∆CoVaR) type measures in a multivariate system setting. We establish the asymptotic properties for estimators of both types of measures and show how the estimation uncertainty in the multivariate case can be decomposed into dynamic univariate marginal and potentially time-varying dependence components. Our finite sample study shows good performance of our methodology for estimation and prediction risk in cases with constant and dynamic dependence. In an empirical application\, we provide new results for the analysis of systemic risk contributions of 50 large US financial institutions in a recent period from the financial crisis to the COVID crisis (2010-2020). Our findings highlight the critical role of comprehensive multivariate forecast intervals in systemic risk assessment\, particularly with regard to the interpretation of systemic risk rankings. \n  \nOrganizers:  Christian FRANCQ \n  \n
URL:https://crest.science/event/jeremy-leymarie-clermont-school-of-business-t-b-a/
CATEGORIES:Finance-Insurance,Seminars
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