Minsim Meeting Agendas and Recaps
Revision as of 02:48, 1 December 2008 by Dhayes
Meeting Agendas/Tasks for Next Meeting
09/29/08 For next week:
- Look up information on Aspen project/failure(?) (starting point: Aspen)
- Look at Chris's software and start trying to see if real-life economic problems are reproduced in the simulation
- Tariffs, international trade
- Specialization of labor, Adam Smith
- Maximizing revenue of entrepreneurs vs total country revenue
- Inflation, Stagflation, Phillips curve
- Compare the stability of a central banking system with that of the gold standard
- Evaluate the "bailout"
- Post summaries of articles up on the wiki
- Sign up for the wiki
- Edit the section "Papers on economic Agent-Based simulation"
- Look at the household model and formulate ways to improve Chris's model
- Went over code
- Why don't prices stabilize on its own?
- Broad objectives?
- Figure out where supply/demand is in the code
- use this to see if the simulation satisfies the properties of supply/demand
- Play with parameters- More stability with more workers, etc? (keep in mind that this slows down the program)
- Brainstorm things we can look at in the future
- Interest rates?
- Meet separately Wednesday (4:30, Friend library) to look over code
- Start looking into old intro micro/macro books
Meeting Recap 10/13/08 - Tasks
- Baseline economy
- External Influence
- SEC Regulation
- Government Regulation
- Factors going into external influence
- Central banks
- Gold standard
- Technical vs. Fundamental analysis
- Trend following
- Machine learning
- Partial/full information for agent?
- Emotional agents?
- Agents don’t have to be fully rational
- How good should the machine learning be to reflect the world?
- International Trade
Meeting Recap 10/20/08 - Tasks
- eric- lifecycles of individual
- tony- info flow, communication, mkt for information
- stephanie- financial intruments? taxes, 401ks?
- Current banking system, politician's plans- will it work? Moratorium on mortgages. Free market vs. regulation of government
- Controversy b/w deregulation and regulation, party platforms
- CVS setup
- Sheri wants to look at Trend following, arbitrageurs
- Tony wants to look at media- flow of information in economy where default state is that they only know local information
- To simulate: make a theory, get mathematical results, then simulate to verify/revoke results
- Market failure - used to justify infusion of capital, govt regulation (build model for credit default swaps - miscalculation of risk- because of lack of government regulation?)
- IIASA: publications that conduct interdisciplinary studies on economy and other global forces: IIASA
Meeting Updates 11/10/08
- Eric's professor recommends that he understand the original model in the simulation and go through literature to understand savings and lifetimes.
- Tony - wants to start fundamentally on convergent prices and how information flows with pricing mechanisms.
- Zero-intelligence Agents- Economic science association conference
- JEBO- paper by Mizuta, giving agents access to order book with offers to buy and sell-- enormously stabilizing
- Tony's advisor wants him to first do analytics, then do simulation
- Stephanie- is going to look into interbank lending and the credit crunch, then if possible, look into CDS contracts
- Prof Steiglitz has a technical description of credit crunch by a WWS professor affililated with the Econ dept
- Tony should look into auctions
- Stephanie will write up API documentation on the banking code.
- Framework interface is set up to define arbitrageurs like hedge fund. The entrepreneurs are arbitrage firms.
- Presentation by Prof. Vichnevetsky: "World" Modeling and Simulation
- Bib-tech: allows you to sort citations
- Paper summaries: To migrate to the main website at minsim.cs.princeton.edu. Will create a bibliographic list, with links to popups with sumaries.
- Should be assessable to everyone
- Getting started page
- Step by step instructions
- Eclipse cheat-sheet
- Applications to COS444 and other classes
- Tony: locality problems to be looked into
- Machine learning responses to bidding strategies
- Ausubel + Cramton paper