Problems of identification and inference for 'non-standard' models in complex systems with special reference to finance and teletraffic [ 2003-01-01 - 2006-12-31 ]

Research Grant

Researchers: Prof Chris Heyde (Chief Investigator) ,  The Australian National University (Managed by)

Brief description Problems of identification and inference for 'non-standard' models in complex systems with special reference to finance and teletraffic. The project is concerned with 'non-standard' models needed to deal with complex systems, such as those exhibiting scaling and fractal properties. There is a focus on methods for dealing with heavy tailed distributions and long range dependent observations, for which most standard statistical methods break down, and on applications in finance and telecommunications. An important part of the project concerns model validation for Heyde's fractal activity time geometric Brownian motion model, a candidate minimal description risky asset model to replace the geometric Brownian motion paradigm.

Funding Amount $215,000

Funding Scheme Discovery Projects

View this grant in the ARC Data Portal