An investigation of crash avoidance in a complex system

Authored by D Lamper

Date Published: 2002-12-15

DOI: 10.1016/s0378-4371(02)01381-x

Sponsors: No sponsors listed

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

Complex systems can exhibit unexpected large changes, e.g. a crash in a financial market. We examine the large endogenous changes arising within a non-trivial generalization of the minority game: the grand canonical minority game. Using a Markov-Chain description, we study the many possible paths the system may take. This `many-worlds' view not only allows us to predict the start and end of a crash in this system, but also to investigate how such a crash may be avoided. We find that the system can be `immunized' against large changes: by inducing small changes today, much larger changes in the future can be prevented. (C) 2002 Elsevier Science B.V. All rights reserved.

Tags

Agent-based models econophysics Complex adaptive systems