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Title: Professor

Short Description: J. Doyne Farmer is a professor at the Santa Fe Institute. His main interests are complex systems, with applications to financial markets and techological innovation.

Institution: Santa Fe Institute

Special Academic Interests: , ,

Dept Homepage: link

Is this Member on the AGENDA team?: No

Joined: July 6th, 2011

Activity

J Doyne Farmer wrote a new blog post titled New: Wright Meets Markowitz: How Standard Portfolio Theory Changes When Assets Are Technologies Following Experience Curves

This paper considers how to optimally allocate investments in a portfolio of competing technologies. We introduce a simple model representing the underlying trade-off — between investing enough effort in any one project to spur rapid progress, and diversifying effort over many projects simultaneously to hedge against failure. We use stochastic experience curves to model the idea that investing more in a technology reduces its unit costs, and we use a mean-variance objective function to understand the effects of risk aversion. In contrast to portfolio theory for standard financial assets, the...
(162 days ago)

J Doyne Farmer wrote a new blog post titled New: Best Reply Structure and Equilibrium Convergence in Generic Games

Game theory often assumes rational players that play equilibrium strategies. But when the players have to learn their strategies by playing the game repeatedly, how often do the strategies converge? We analyze generic two player games using a standard learning algorithm, and also study replicator dynamics, which is closely related. We show that the frequency with which strategies converge to a fixed point can be understood by analyzing the best reply structure of the payoff matrix. A Boolean transformation of the payoff matrix, replacing all best replies by one and all other entries by zero,...
(184 days ago)

J Doyne Farmer wrote a new blog post titled REVISION: A Taxonomy of Learning Dynamics in 2 × 2 Games

Learning would be a convincing method to achieve coordination on an equilibrium. But does learning converge, and to what? We answer this question in generic 2-player, 2-strategy games, using Experience-Weighted Attraction (EWA), which encompasses many extensively studied learning algorithms. We exhaustively characterize the parameter space of EWA learning, for any payoff matrix, and we understand the generic properties that imply convergent or non-convergent behaviour in 2 × 2 games. Irrational choice and lack of incentives imply convergence to a mixed strategy in the centre of the strategy...
(246 days ago)

About me:

J. Doyne Farmer is a professor at the Santa Fe Institute. He has broad interests in complex systems, and has done research in dynamical systems theory, time series analysis and theoretical biology. At present his main interest is in developing quantitative theories for social evolution, in particular for financial markets (which provide an accurate record of decision making in a complex environment) and the evolution of technologies (whose performance through time provides a quantitative record of one component of progress).

He was a founder of Prediction Company, a quantitative trading firm that was sold to the United Bank of Switzerland, and was their chief scientist from 1991 - 1999. During the eighties he worked at Los Alamos National Laboratory, where he was an Oppenheimer Fellow, founding the Complex Systems Group in the theoretical division. He began his career as part of the U.C. Santa Cruz Dynamical Systems Collective, a group of physics graduate students who did early research in what later came to be called "chaos theory". In his spare time during graduate school he led a group that designed and built the first wearable digital computers (which were used to beat the game of roulette). For popular press see The Newtonian Casino by Thomas Bass, Chaos by Jim Gleick, Complexity by Mitch Waldrup, and The Predictors by Thomas Bass.