An evolutionary CAPM under heterogeneous beliefs

Abstract

We would like to thank Cars Hommes for a stimulating discussion in the early stages of this project. We are grateful to valuable comments from two anonymous referees. Dieci gratefully acknowledges a Visiting Professor Appointment at the Quantitative Finance Research Centre, UTS Business School, during which this work was finalised. Dieci also acknowledges support from MIUR under project PRIN 2009 "Local interactions and global dynamics in economics and finance: models and tools" and from EU COST within Action IS1104 "The EU in the new complex geography of economic systems: models, tools and policy evaluation". Financial support for Chiarella and He from the Australian Research Council (ARC) under Discovery Grant (DP110104487) is gratefully acknowledged.

Managing rational routes to randomness

“…In another influential paper, Brock and Hommes (1998) detect rational routes to randomness in an asset-pricing model in which market participants have the choice between technical and fundamental predictors. Quite similar asset pricing dynamics is obtained in the models by Diks and van der Weide (2003) and Brock et al (2005) in which speculators select between a large number of technical and fundamental predictors; in the models by Hommes et al (2005) and Diks and van der Weide (2005) in which heterogeneous speculators asynchronously update their beliefs; in the model by Anuvrief and Panchenko (2009) in which different market designs ranging from market clearing setups to market maker scenarios are explored; and in the model by Chiarella et al (2013) in which heterogeneous speculators can invest in multiple risky assets. Moreover, de Grauwe and Grimaldi (2006) discover complex endogenous dynamics in a foreign exchange market model with heterogeneous speculators.…”

Time-varying economic dominance in financial markets: A bistable dynamics approach

“…This is different from the observations in Chiarella et al (2013) that one asset is stable and the other can be unstable in a coupled system. Intuitively, the multi-assets are coupled via the variance-covariance matrices in Chiarella et al (2013), which is in the higher order terms and hence cannot affect the local stability. However, the current model couples the two assets together even in its linearization skeleton.…”

Research on price Stackelberg game model with probabilistic selling based on complex system theory

“…Ma and Li [23] constructed a dynamic Bertrand-Stackelberg pricing model to analyze the influence of uncertain demand on the profit and complexity. Chiarella et al [24] incorporated the adaptive behavior of agents with heterogeneous beliefs and establishes an evolutionary capital asset pricing model (ECAPM) within the mean-variance framework. Ma and Pu [25] studied the Cournot-Bertrand duopoly model, analyzed the stability of the fixed points, and recognized the chaotic behavior of the system.…”