{"61471":{"#nid":"61471","#data":{"type":"event","title":"Robust Risk Management","body":[{"value":"\u003Cp\u003E\u003Cstrong\u003ETITLE: \u003C\/strong\u003ERobust Risk Management\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003ESPEAKER: \u003C\/strong\u003EApostolos Fertis\u003C\/p\u003E\u003Cp\u003E\u003Cstrong\u003EABSTRACT:\u003C\/strong\u003E\u003C\/p\u003E\u003Cp\u003ECoherent risks can be expressed as the worst-case expectation when the \nprobability distribution varies in some uncertainty set, according to \nthe representation theorem. Very often, randomness can be divided in two \nstages, and there is additional information about the possible first \nstage scenarios. Traditional coherent risks, such as the CVaR, fail to \nmake use of this information. In this talk, we introduce a new class of \nrisk measures, called robust risk measures, which combine the \nuncertainty set of a traditional risk measure with the additional \ninformation about the first stage scenarios. We state and prove a \nrepresentation theorem for the robust risk measures, which facilitates \ntheir computation. We define and show how to compute the Robust CVaR, \nthe robust risk constructed based on CVaR. We compare the optimal-Robust \nCVaR and optimal-CVaR portfolios under diverse scenarios constructed \nusing real New York Stock Exchange (NYSE) and NASDAQ data from 2005 to \n2010.\n\u003Cbr \/\u003E\u003Cbr \/\u003E\nBio:\u003Cbr \/\u003EApostolos Fertis completed his PhD at the Electrical Engineering and \nComputer Science Department of the Massachusetts Institute of Technology \nin 2009.\u0026nbsp; Currently he is a researcher at the Institute for Operations \nResearch (IFOR) in Zurich.\n\u003Cbr \/\u003EIn\u0026nbsp; PhD thesis,\u0026nbsp; under the supervision of Professor Dimitris Bertsimas, \nhe investigated the application of the robust optimization concept in \nconfronting the uncertainty in the samples used to produce statistical \nestimates. In January 2010, he initiated the \u0022Robust Risk Management\u0022 \nresearch project at theIFOR. The project aspires to introduce a new idea \nin uncertainty management by combining traditional risk management \ntechniques with robust optimization.\u003C\/p\u003E","summary":null,"format":"limited_html"}],"field_subtitle":"","field_summary":"","field_summary_sentence":[{"value":"Robust Risk Management"}],"uid":"27187","created_gmt":"2010-10-06 11:07:44","changed_gmt":"2016-10-08 01:52:31","author":"Anita Race","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2010-11-09T10:00:00-05:00","event_time_end":"2010-11-09T11:00:00-05:00","event_time_end_last":"2010-11-09T11:00:00-05:00","gmt_time_start":"2010-11-09 15:00:00","gmt_time_end":"2010-11-09 16:00:00","gmt_time_end_last":"2010-11-09 16:00:00","rrule":null,"timezone":"America\/New_York"},"extras":[],"groups":[{"id":"1242","name":"School of Industrial and Systems Engineering (ISYE)"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}