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X-WR-CALDESC:Events for CREST
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TZID:Europe/Helsinki
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TZOFFSETFROM:+0200
TZOFFSETTO:+0300
TZNAME:EEST
DTSTART:20260329T010000
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DTSTART:20261025T010000
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DTSTART;TZID=Europe/Helsinki:20260219T100000
DTEND;TZID=Europe/Helsinki:20260219T230000
DTSTAMP:20260710T211629
CREATED:20251208T104829Z
LAST-MODIFIED:20260203T135026Z
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SUMMARY:Danial Ali AKBARI (University of Oslo)"HAACE -- Heterogeneous Agent Analytic Climate Economy"
DESCRIPTION:Quantitative Sustainable Economics and Finance \nTime: 10.00 am\nDate: 19th of February 2026\nRoom 3001 \nDanial Ali AKBARI (University of Oslo)”HAACE — Heterogeneous Agent Analytic Climate Economy” \nAbstract : We develop an analytic\, continuous-time climate-economy model with heterogeneity in both household wealth and climate-damage exposure. We cast the social planner problem using distributional Pareto and Negishi-style welfare weights\, making the heterogeneous economy tractable and allowing us to map integrated assessment primitives directly to policy objects\, most notably the social cost of carbon (SCC). We formalize distributional damages to consumption — damages whose incidence is correlated with wealth — and analyze how the joint distribution of wealth and damages to consumption capacity reshapes the SCC \nOrganizers:   Peter Tankov\, Gauthier Vermandel\, and Olivier David Zerbib \nSponsors:\nCREST-CMAP \n
URL:https://crest.science/event/danial-ali-akbari-university-of-oslot-b-a/
CATEGORIES:Finance-Insurance,Quantitative Sustainable Economics and Finance,Seminars
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DTSTART;TZID=Europe/Helsinki:20260219T110000
DTEND;TZID=Europe/Helsinki:20260219T120000
DTSTAMP:20260710T211629
CREATED:20251208T110700Z
LAST-MODIFIED:20260120T151808Z
UID:18631-1771498800-1771502400@crest.science
SUMMARY:Alexander ARANJDELOVIC (Vienna University of Economics and Business) "Solving Stochastic Climate-economy Models: a Deep Least-squares Monte Carlo Approach"
DESCRIPTION:Quantitative Sustainable Economics and Finance \nTime: 10.00 am\nDate: 19th of February 2026\nRoom 3001 \nAlexander ARANJDELOVIC (Vienna University of Economics and Business) “Solving Stochastic Climate-economy Models: a Deep Least-squares Monte Carlo Approach” \nAbstract : Stochastic versions of recursive integrated climate-economy assessment models are essential for studying and quantifying policy decisions under uncertainty. However\, as the number of state variables  and stochastic shocks increases\, solving these models via deterministic grid-based dynamic programming (e.g.\, value-function iteration / projection on a discretized grid over continuous state variables\, typically coupled with discretized shocks) becomes computationally infeasible\, and simulation-based methods are needed. The least-squares Monte Carlo (LSMC) method has become popular for solving optimal stochastic control problems in quantitative finance. In this paper\, we extend the application of the LSMC method to stochastic climate-economy models. We exemplify this approach using a stochastic version of the DICE model with five key uncertainty sources highlighted in the literature. To address the complexity and high dimensionality of these models\, we incorporate deep neural network approximations in place of standard regression techniques within the LSMC framework. Our results demonstrate that the deep LSMC method can be used to efficiently derive optimal policies for climate-economy models in the presence of uncertainty. \nOrganizers:  Peter Tankov\, Gauthier Vermandel\, and Olivier David Zerbib \nSponsors:\nCREST-CMAP \n
URL:https://crest.science/event/abraham-lioui-edhec-t-b-a/
CATEGORIES:Finance-Insurance,Quantitative Sustainable Economics and Finance,Seminars
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