Agenda: Difference between revisions
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===Friday, July 20 Morning=== | ===Friday, July 20 Morning=== | ||
''8:30am-9am: Registration & Continental Breakfast'' | ''8:30am-9am: Registration & Continental Breakfast'' | ||
Fast paced tutorials (20 minutes + 10 minutes Q&A) on computational topics | ''Fast paced tutorials (20 minutes + 10 minutes Q&A) on computational topics'' | ||
* Michael Wellman, University of Michigan (Thursday) - Strategic Reasoning and Agent-Based Modeling | * ''Michael Wellman, University of Michigan (Thursday) - Strategic Reasoning and Agent-Based Modeling'' | ||
Financial scenarios are characterized by complex interactions among forward-looking | Financial scenarios are characterized by complex interactions among forward-looking | ||
self-interested agents. I discuss an emerging methodology for strategic reasoning that | self-interested agents. I discuss an emerging methodology for strategic reasoning that | ||
Line 60: | Line 60: | ||
understanding the implications of high-frequency trading in various market mechanisms. | understanding the implications of high-frequency trading in various market mechanisms. | ||
* Phil Bernstein, Microsoft Research - Metamodels | * ''Phil Bernstein, Microsoft Research - Metamodels'' | ||
- What's at stake in choosing a metamodel in a modeling environment? | - What's at stake in choosing a metamodel in a modeling environment? | ||
- How do you deal with models expressed in heterogeneous metamodels? | - How do you deal with models expressed in heterogeneous metamodels? | ||
* Mike Bennett, EDM Council and David Newman, Wells Fargo - Conceptual Modeling and | * ''Mike Bennett, EDM Council and David Newman, Wells Fargo - Conceptual Modeling and | ||
Ontologies and Semantic Web Technologies | Ontologies and Semantic Web Technologies'' | ||
[http://www.rhsmith.umd.edu/doit/docs/NewmanBennettPres.pdf LEI Semantic Solutions for Financial Industry Systemic Risk Management] | [http://www.rhsmith.umd.edu/doit/docs/NewmanBennettPres.pdf LEI Semantic Solutions for Financial Industry Systemic Risk Management] | ||
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- Relationship to enhanced institutional and macroprudential risk management. | - Relationship to enhanced institutional and macroprudential risk management. | ||
* Lucian Popa, IBM Almaden - Information Extraction and Modeling | * ''Lucian Popa, IBM Almaden - Information Extraction and Modeling'' | ||
Midas is a research infrastructure to extract, clean, link, and integrate entities from public | Midas is a research infrastructure to extract, clean, link, and integrate entities from public |
Revision as of 06:29, 14 July 2012
Thursday, July 19 Morning
8:30 am - 9 am: Registration & Continental Breakfast
9 am - 9:30 am: Welcome and Vision for the Workshop
9:30 - 11 am: The Anatomy of a Financial Quandary In-depth interviews a la Terry Gross of a panel of financial experts from academia, industry and regulatory agencies. * Mark Flood and Nancy Wallace .. interviewed by Louiqa Raschid * Joe Langsam and Pete Kyle .. interviewed by H.V. Jagadish
11 am to 12 noon: The Dating Game * What I would Like to LEARN * What I can TEACH * Who am I? Exchange at least one LEARN and one TEACH card with a colleague and find a partner for introductions.
Thursday, July 19 Afternoon
12 - 1 pm: Lunch
1 - 2 pm Introductions
2 - 2:20 pm Michael Wellman Presentation (see Friday Agenda)
2:20 - 3:15 pm: Roundup of Challenges
Thursday, July 19 Afternoon
3:15 - 3:30 pm: Afternoon Break and Choose Your Challenge
3:30 to 5 pm: Breakout Session A Date with a Regulator to Resolve a Research Challenge
Thursday, July 19 Evening
Group Dinner
Zaytina Restaurant
701 9th Street NW, Washington DC 20001 http://www.zaytinya.com/ 6pm Meet outside the Marriott or the Waterview at 5:45 p.m. to share a taxi.
Friday, July 20 Morning
8:30am-9am: Registration & Continental Breakfast
Fast paced tutorials (20 minutes + 10 minutes Q&A) on computational topics
- Michael Wellman, University of Michigan (Thursday) - Strategic Reasoning and Agent-Based Modeling
Financial scenarios are characterized by complex interactions among forward-looking self-interested agents. I discuss an emerging methodology for strategic reasoning that bridges the gap between computational modeling and economic analysis by combining fine-grained simulation with game-theoretic solution concepts. These methods have shed light on several scenarios in automated trading, and may be suitable for understanding the implications of high-frequency trading in various market mechanisms.
- Phil Bernstein, Microsoft Research - Metamodels
- What's at stake in choosing a metamodel in a modeling environment? - How do you deal with models expressed in heterogeneous metamodels?
- Mike Bennett, EDM Council and David Newman, Wells Fargo - Conceptual Modeling and
Ontologies and Semantic Web Technologies LEI Semantic Solutions for Financial Industry Systemic Risk Management
- The value and role of a conceptual model in systems development. - The role in ontology development. - Faceted representation using an example of an interest rate swap - Comprehensive view of the transaction terms, rights and obligations, contract terms, etc. - An overview of the value of using operational ontologies based upon the Financial Industry Business Ontology (vs. conventional technologies). - Data standardization, instrument classification, identifying impact of contractual provisions and identifying legal entity linkage and exposures. - Relationship to enhanced institutional and macroprudential risk management.
- Lucian Popa, IBM Almaden - Information Extraction and Modeling
Midas is a research infrastructure to extract, clean, link, and integrate entities from public unstructured data sources. A major focus area is in the financial domain and is based on the regulatory filings that publicly traded companies periodically submit to the US Securities and Exchange Commission (SEC). By extracting and analyzing data spread over millions of documents, we built an entity-centric repository for the network of major financial institutions, where the main entities are financial companies, their loans and securities, their key executives and directors, as well as relationships with other companies. We show how the resulting entities can be visualized and further analyzed. We show extensions of these methods to social media data collections.
- H.V. Jagadish - Data modeling and analysis.
- Leora Morgenstern and Benjamin Grosof - Reasoning.
- Ben Schneiderman and William Ribarsky - Visual analytics
Friday, July 20 Morning
Fireside chat: Life of a Finance Faculty in this Brave New World of Data Chester Spatt and Russ Wermers interviewed by H V Jagadish.
Friday, July 20 Afternoon
12-1pm: Lunch
2:30-3pm: Break
More breakout sessions
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