Agenda: Difference between revisions

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  The Dating Game  
  The Dating Game  
  * What I would Like to Know
  * What I would Like to LEARN
  * What I Can Tell Others
  * What I Can TEACH Others


===Thursday, July 19 Afternoon===
===Thursday, July 19 Afternoon===

Revision as of 04:23, 12 July 2012

Thursday, July 19 Morning

In-depth interviews a la Terry Gross with panels of experts, both academic 
finance researchers and federal regulators.
* Mark Flood and OFR researchers .. interviewed by Louiqa Raschid
* Joe Langsam and Andrei Kirilenko interviewed by H.V. Jagadish
* Nancy Wallace and Pete Kyle interviewed by Louiqa Raschid

Thursday, July 19 Afternoon

The Dating Game 
* What I would Like to LEARN
* What I Can TEACH Others

Thursday, July 19 Afternoon

A Date with a Regulator to Resolve a Research Challenge

Friday, July 20 Morning

Fast paced tutorials (20 minutes each) 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

More breakout sessions
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