Bifurcation Routes to Volatility Clustering

A simple asset pricing model with two types of adaptively learning traders,fundamentalists and technical analysts, is studied. Fractions of these tradertypes, which are both boundedly rational, change over time according toevolutionary learning, with technical analysts conditioning their forecastingrule upon deviations from a benchmark fundamental. Volatility clustering arisesendogenously in this model. Two mechanisms are proposed as an explanation. Thefirst is coexistence of a stable steady state and a stable limit cycle, whicharise as a consequence of a so-called Chenciner bifurcation of the system. Thesecond is intermittency and associated bifurcation routes to strange attractors.Both phenomena are persistent and occur generically in nonlinearmulti-agent evolutionary systems.