We perform an experimental study to assess the effect of complexity on asset trading. We find that higher complexity leads to increased price volatility, lower liquidity, and decreased trade efficiency especially when repeated bargaining takes place. However, the channel through which complexity acts is not simply due to the added noise induced by estimation error. Rather, complexity alters the bidding strategies used by traders, making them less inclined to trade, even when we control for estimation error across treatments. As such, it appears that adverse selection plays an important role in explaining the trading abnormalities caused by complexity.

We describe how episodic illiquidity arises from a breakdown in cooperation between market participants. We first solve a one‐period trading game in continuous‐time, using an asset pricing equation that accounts for the price impact of trading. Then, in a multi‐period framework, we describe an equilibrium in which traders cooperate most of the time through repeated interaction, providing apparent liquidity to one another. Cooperation breaks down when the stakes are high, leading to predatory trading and episodic illiquidity. Equilibrium strategies that involve cooperation across markets lead to less frequent episodic illiquidity, but cause contagion when cooperation breaks down.