{"id":11630,"date":"2016-04-19T20:18:25","date_gmt":"2016-04-19T20:18:25","guid":{"rendered":"https:\/\/stage.kse.ua\/news\/2016-04-19-scenario-based-financial-value-at-risk-optimization-academic-seminar-2\/"},"modified":"2016-04-19T20:18:25","modified_gmt":"2016-04-19T20:18:25","slug":"2016-04-19-scenario-based-financial-value-at-risk-optimization-academic-seminar-2","status":"publish","type":"news","link":"https:\/\/kse.ua\/en\/news\/2016-04-19-scenario-based-financial-value-at-risk-optimization-academic-seminar-2\/","title":{"rendered":"Academic seminar “Scenario-Based Financial Value-at-Risk Optimization” on April 21"},"content":{"rendered":"

<\/p>\n

KSE welcomes to academic seminar “Scenario-Based Financial Value-at-Risk Optimization”<\/div>\n
<\/div>\n
Coauthors<\/u>: Helmut Mausser, Lead Mathematician, IBM Risk Analytics \u00a0and Oleksandr Romanko, Senior Research Analyst, Risk Analytics – Business Analytics, IBM Canada<\/div>\n
<\/div>\n
Abstract<\/b>:<\/div>\n
<\/div>\n
Simulation and optimization are tools and techniques to model, evaluate, hedge and optimally re-balance portfolios of financial instruments. The main challenge of practical financial models is minimizing risk in the presence of uncertainty. The primary goal of simulation is to model uncertainty in asset values over time. Optimization techniques help to minimize risk and maximize performance of financial portfolios.<\/div>\n
<\/div>\n
In financial risk management Value-at-Risk (VaR) is a popular tail-based risk measure which forms the basis for regulatory capital according to Basel II and III Accords. The problem is that VaR is a quantile of the loss distribution, which is a chance-constrained problem. Since the loss distribution is typically unknown or computationally impractical, VaR optimization usually uses a finite sample approximation to the distribution by means of scenarios, so that an estimate of the VaR over a sample scenario set is optimized. This requires mixed-integer optimization, which makes the problem difficult. To improve solution time, different heuristic techniques can be used during optimization. We develop and test heuristic algorithms for scenario-based VaR optimization. Due to high computational complexity of VaR optimization, we utilize Conditional Value-at-Risk (CVaR) – based proxies for VaR objectives and constraints. Our heuristic algorithm allows obtaining robust results with low computational complexity.<\/div>\n
<\/div>\n
About the presenter:<\/i><\/div>\n
Oleksandr Romanko, Ph.D.<\/i><\/div>\n
Senior Research Analyst, Risk Analytics – Business Analytics, IBM Canada<\/i><\/div>\n
Adjunct Professor, University of Toronto<\/i><\/div>\n
\u00a0<\/i><\/div>\n
Short Bio:<\/i><\/div>\n
Oleksandr Romanko is a Senior Research Analyst, Risk Analytics – Business Analytics at IBM Canada (Quantitative Research Group). He holds Ph.D. degree in computer science from McMaster University. Research interests of Dr. Romanko include financial and risk modeling, portfolio optimization, business analytics, data science, operations research, multiobjective and parametric optimization, and computational algorithms. He has published a number of research papers and won several awards from IBM, Canadian Operational Research Society, Mitacs, and Institute for Operations Research and the Management Sciences.<\/i><\/div>\n
\u00a0<\/i><\/div>\n
To participate please register:<\/div>\n
<\/div>\n

REGISTER!<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

KSE welcomes to academic seminar “Scenario-Based Financial Value-at-Risk Optimization” Coauthors: Helmut Mausser, Lead Mathematician, IBM Risk Analytics and Oleksandr Romanko, Senior Research Analyst, Risk Analytics – Business Analytics, IBM Canada Abstract: Simulation and optimization are tools and techniques to model, evaluate, hedge and optimally re-balance portfolios of financial instruments. The main challenge of practical financial\u2026<\/p>\n","protected":false},"featured_media":0,"template":"","categories":[],"tags":[],"department":[],"news_type":[15],"project":[],"region":[],"unit":[38],"class_list":["post-11630","news","type-news","status-publish","hentry","news_type-news","unit-kse"],"acf":{"primary_unit":null,"news_intro":"","header_cta_mode":"event","header_event_cta_text":"\u0414\u043e \u043f\u043e\u0434\u0456\u0457","header_event_cta_url":"","header_research_cta_text":"\u0427\u0438\u0442\u0430\u0442\u0438 \u0432\u0441\u0435 \u0434\u043e\u0441\u043b\u0456\u0434\u0436\u0435\u043d\u043d\u044f","header_research_pdf":null,"author_person":"","author_name":"","related_news":null,"related_events":[],"related_people":[],"related_links":null,"external_link":"","external_link_label":"","is_featured":false,"is_featured_archive":false,"quote_text":"","quote_author":"","quote_author_role":"","program_title":"\u0424\u043e\u0440\u043c\u0430\u0442 \u043f\u0440\u043e\u0433\u0440\u0430\u043c\u0438","program_items":null,"reference_title":"\u0414\u043e\u0432\u0456\u0434\u043a\u0430","reference_content":"","source_system":"migration","source_id":"16777","content_owner":"kse","last_reviewed":null,"visibility":"public","platform_id":"","platform_version":"","platform_managed":false},"yoast_head":"\nAcademic seminar "Scenario-Based Financial Value-at-Risk Optimization" on April 21 - KSE<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/kse.ua\/en\/news\/2016-04-19-scenario-based-financial-value-at-risk-optimization-academic-seminar-2\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Academic seminar "Scenario-Based Financial Value-at-Risk Optimization" on April 21\" \/>\n<meta property=\"og:description\" content=\"KSE welcomes to academic seminar "Scenario-Based Financial Value-at-Risk Optimization" Coauthors: Helmut Mausser, Lead Mathematician, IBM Risk Analytics and Oleksandr Romanko, Senior Research Analyst, Risk Analytics - Business Analytics, IBM Canada Abstract: Simulation and optimization are tools and techniques to model, evaluate, hedge and optimally re-balance portfolios of financial instruments. 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