Zero-intelligence versus human agents: An experimental analysis of the efficiency of Double Auctions and Over-the-Counter markets of varying sizes

We study two well-known electronic markets: an over-the-counter (OTC) market, in which each trader looks for the best counterpart through bilateral negotiations, and a double auction (DA) market, in which traders post their quotes publicly. We focus on the DA–OTC efficiency gap and show how it varies with different market sizes (10, 20, 40, and 80 traders). We compare experimental results from a sample of 6400 undergraduate students in Economics and Management with zero-intelligence agent-based simulations. Simulation results show that the traded quantity increases with market size under both DA and OTC. Experimental results confirm the same tendency under DA, while the share of periods in which the traded quantity is lower than the efficient one increases with market size under OTC, ultimately leading to a DA–OTC efficiency gap increasing with the market size. We rationalize these results by putting forward a simple model of OTC market as a repeated bargaining procedure under incomplete information on buyers' valuations and sellers' costs. We show that efficiency decreases slightly with size due to two counteracting effects: acceptance rates in earlier interactions decrease with size, and earlier offers increase, but not always enough to compensate for the decrease in acceptance rates.