
handle: 10419/86068
A simple asset pricing model with two types of adaptively learning traders, fundamentalists and technical analysts, is studied. Fractions of these trader types, which are both boundedly rational, change over time according to evolutionary learning, with technical analysts conditioning their forecasting rule upon deviations from a benchmark fundamental. Volatility clustering arises endogenously in this model. Two mechanisms are proposed as an explanation. The first is coexistence of a stable steady state and a stable limit cycle, which arise as a consequence of a so-called Chenciner bifurcation of the system. The second is intermittency and associated bifurcation routes to strange attractors. Both phenomena are persistent and occur generically in nonlinear multi-agent evolutionary systems. (author's abstract)
Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"
JEL E32, G12, D84, ddc:330, CAPM, Beschränkte Rationalität, Working Papers SFB \Adaptive Information Systems and Modelling in Economics and Management Science\, Clusteranalyse, Volatilität, Lernprozess, Theorie, multi-agent systems / bounded rationality / evolutionary learning / bifurcation and chaos / coexisting attractors
JEL E32, G12, D84, ddc:330, CAPM, Beschränkte Rationalität, Working Papers SFB \Adaptive Information Systems and Modelling in Economics and Management Science\, Clusteranalyse, Volatilität, Lernprozess, Theorie, multi-agent systems / bounded rationality / evolutionary learning / bifurcation and chaos / coexisting attractors
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
