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This paper incorporates information uncertainty and social interaction among investors into a random utility framework and develops a dynamic equilibrium model of asset pricing and investor choice. We show that strong social interaction can lead to endogenous switching between two persistent regimes for the mean choice fraction of investor population, which can simultaneously generate volatility clustering and time-series momentum in asset returns. By using StockTwits post volume as a proxy for social interaction, we provide empirical evidence for the model predictions for various equity indices. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jebo.2005.08.005 Byline: Carl Chiarella (a), Roberto Dieci (b), Xue-Zhong He (a) Keywords: Heterogeneous beliefs; Asset pricing; Portfolio choice; Bifurcation analysis; Co-movements in stock prices Abstract: This paper develops a dynamic model of a financial market where heterogeneous agents invest among multiple risky assets and a risk-free asset, under a market maker scenario. Particular attention is paid to the case of two risky assets and two agent types, fundamentalists and trend chasers, whose beliefs on both first and second moments of the conditional distribution of returns are based on past observations. Conditions for the stability of the 'fundamental' equilibrium are established and the effect of the correlation between the risky assets is examined. It turns out that investors' anticipated correlation and dynamic portfolio diversification do not always have a stabilizing role, but rather may act as a source of complexity in the financial market. Author Affiliation: (a) School of Finance and Economics, University of Technology, Sydney, Australia (b) Dipartimento di Matematica per le Scienze Economiche e Sociali, Universita degli Studi di Bologna, Italy Article History: Received 30 October 2004; Revised 11 July 2005; Accepted 31 August 2005

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jebo.2004.07.019 Byline: Carl Chiarella (a), Xue-Zhong He (a), Hing Hung (a), Peiyuan Zhu (b) Keywords: Cobweb model; Heterogeneity; Bounded rationality; Geometric decay learning dynamics; Bifurcations Abstract: This paper considers the traditional cobweb model with heterogenous risk averse producers whose supply functions involve their estimates of the conditional mean and variance of the future price. The producers seek to learn these quantities by applying geometric decay processes (GDP) to past prices. The heterogeneity manifests itself in the lag lengths and memory parameters applied to past prices as well as in risk aversion coefficients. We find that each dimension of heterogeneity changes/enriches the cobweb dynamics with respect to the case of homogeneous producers. Author Affiliation: (a) School of Finance and Economics, University of Technology, Sydney, P.O. Box 123, Broadway, NSW 2007, Australia (b) Department of Electrical and Information Engineering, The University of Sydney, NSW 2006, Australia Article History: Received 20 October 2003; Accepted 21 July 2004

Instead of heuristical heterogeneity assumption in the current heterogeneous agent models (HAMs), we derive the trading heterogeneity by introducing information uncertainty about the fundamental value to a HAM. Conditional on their private information about the fundamental value, agents choose different trading strategies when optimizing their expected utilities. This provides a micro-foundation to heterogeneity and switching behavior of agents. We show that the HAM with trading heterogeneity originating from the incomplete information performs equally well, if not better than existing HAMs, in generating bubbles, crashes, and mean-reverting prices. The simulated time series matches with the S&P 500 in terms of power law distribution in returns, volatility clustering and long memory in volatility. [ABSTRACT FROM AUTHOR]

This paper verifies the endogenous mechanism and economic intuition on volatility clustering using the coexistence of two locally stable attractors proposed by Gaunersdorfer et al. (2008) . By considering a simple asset pricing model with two types of boundedly rational traders, fundamentalists and trend followers, and noise traders, we provide theoretical conditions on the coexistence of a locally stable steady state and a locally stable invariant circle of the underlying nonlinear deterministic financial market model and show numerically that the interaction of the coexistence of the deterministic dynamics and noise processes can endogenously generate volatility clustering and long range dependence in volatility observed in financial markets. Economically, volatility clustering occurs when neither the fundamental nor trend following traders dominate the market and when traders switch more often between the two strategies. [ABSTRACT FROM AUTHOR]

This paper empirically assesses heterogeneous expectations in asset pricing. We use a maximum likelihood approach on S&P500 data to estimate a structural model. Our empirical results are consistent with a market populated with fundamentalists and chartists. In addition, agents switch between these groups conditional on their previous performance. The results imply that the model can explain the inflation and deflation of bubbles. Finally, the model is shown to be in the deterministically stable region, but produces stochastic bubbles of similar length and magnitude as empirically observed. [ABSTRACT FROM AUTHOR]

Abstract: Financial markets are typically characterized by high (low) price level and low (high) volatility during boom (bust) periods, suggesting that price and volatility tend to move together with different market conditions/states. By proposing a simple heterogeneous agent model of fundamentalists and chartists with Markov chain regime-dependent expectations and applying the S&P 500 data from January 2000 to June 2010, we show that the estimation of the model matches well with the boom and bust periods in the US stock market. In addition, we find evidence of time-varying behavioural heterogeneity within-group and that the model exhibits good forecasting accuracy. [Copyright &y& Elsevier]

Abstract: Within a continuous-time framework, this paper proposes a stochastic heterogeneous agent model (HAM) of financial markets with time delays to unify various moving average rules used in discrete-time HAMs. The time delay represents a memory length of a moving average rule in discrete-time HAMs. Intuitive conditions for the stability of the fundamental price of the deterministic model in terms of agents’ behavior parameters and memory length are obtained. It is found that an increase in memory length not only can destabilize the market price, resulting in oscillatory market price characterized by a Hopf bifurcation, but also can stabilize an otherwise unstable market price, leading to stability switching as the memory length increases. Numerical simulations show that the stochastic model is able to characterize long deviations of the market price from its fundamental price and excess volatility and generate most of the stylized facts observed in financial markets. [ABSTRACT FROM AUTHOR]