This paper demonstrates that a simultaneous-move herd behavior model generates a fat-tailed distribution of traders' aggregate actions. Each trader infers other traders' private information on the value of assets by observing their actions and decides whether to buy the asset or not. We show that the number of buying actions in a Bayesian Nash equilibrium is characterized as a sum of a binomial process. Under a broad class of distributions for the private information, the distribution of the aggregate actions exhibits a power-law with an exponential truncation. The model prediction is matched with an empirical distribution of stock returns. This model nests the benchmark herd behavior model and the recent models of critical phenomena in the network of traders. In the latter context, we provide an economic reason why the herding behavior in a general setting exhibits criticality
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