In this paper we conduct two experiments within an agent-based double auction market. These two experiments allow us to see the effect of learning and smartness on price dynamics and allocative efficiency. Our results are largely consistent with the stylized facts observed in experimental economics with human subjects. From the amelioration of price deviation and allocative efficiency, the effect of learning is vividly seen. However, smartness does not enhance market performance. In fact, the experiment with smarter agents (agents without a quote limit) results in a less stable price dynamics and lower allocative efficiency.

Many systems of different nature exhibit scale free behaviors. Economic systems with power law distribution in the wealth is one of the examples. To better understand the working behind the complexity, we undertook an empirical study measuring the interactions between market participants. A Web server was setup to administer the exchange of futures contracts whose liquidation prices were coupled to event outcomes. After free registration, participants started trading to compete for the money prizes upon maturity of the futures contracts at the end of the experiment. The evolving 'cash' flow network was reconstructed from the transactions between players. We show that the network topology is hierarchical, disassortative and scale-free with a power law exponent of 1.02±0.09 in the degree distribution. The small-world property emerged early in the experiment while the number of participants was still small. We also show power law distributions of the net incomes and inter-transaction time intervals. Big winners and losers are associated with high degree, high betweenness centrality, low clustering coefficient and low degree-correlation. We identify communities in the network as groups of the like-minded. The distribution of the community sizes is shown to be power-law distributed with an exponent of 1.19±0.16.

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A 24-hour exchange market was created on the Web to trade political futures contracts using fictitious money. In this online market, a political futures contract is a futures contract which matures on the election day with a liquidation price determined by the percentage of votes a candidate receives on the election day. Continuous double auctions were implemented as the system for order storage and price discovery. We drew market participants in the form of tournaments in which top traders won cash awards. Such a market was run, with about 400 registered traders, during the U.S. presidential election in November 2004 and Taiwan parliamentary election in December 2004. The experiments recorded transaction price, highest bid, lowest ask, and trading volume of each contract as a function of time. Despite the relatively small scale of the exchange, in terms of the number of participants and duration of the tournament, we report evidence for asymptotic power-law behaviors of the distributions of price returns, trading volumes, inter-transaction time intervals, and accumulated wealth that were found universal in real financial markets.