A common phenomenon of financial markets is the frequent occurrence of simultaneous extreme returns. In times of market turmoil, assets display stronger comovements than usual, resulting in extreme (usually negative) returns happening jointly. This phenomenon seriously affects portfolio risk and diminishes the benefits of diversification. Here, extremal dependence of bivariate stock returns is studied using a simple nonparametric estimation of the tail dependence coefficient. An agent-based behavioral model is presented to account for this phenomenon. Joint extremes are generated by heterogeneous fundamentalist traders whose perceptions of the effect of a common news factor on asset values become aligned during market stress. Simulation results reproduce the features observed in the return data.

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