Experience Does Not Eliminate Bubbles: Experimental Evidence

We study the role of investor experience in the formation of asset price bubbles. We conduct a call market experiment in which participants trade assets with each other and a learning-to-forecast experiment in which participants only forecast future prices (while trade based on these forecasts is computerized). Each experiment comprises three treatments varying the information that participants receive about the fundamental value. Each experimental market is repeated three times. Throughout, we observe sizable bubbles that persist despite participant experience. Our findings in the call market experiment contrast with those in the literature. Our findings in the learning-to-forecast experiment are novel.

Experience Does not Eliminate Bubbles: Experimental Evidence

We study the role of experience in the formation of asset price bubbles. Therefore, we conduct two related experiments. One is a call market experiment in which participants trade assets with each other. The other is a learning-to-forecast experiment in which participants only forecast future prices, while the trade, which is based on these forecasts, is computerized. Each experiment comprises three treatments that vary the amount of information about the fundamental value that participants receive. Each market is repeated three times. In both experiments and in all treatments, we observe sizable bubbles. These bubbles do not disappear with experience. Our findings in the call market experiment stand in contrast to the literature. Our findings in the learning- to-forecast experiment are novel. Interestingly, the shape of the bubbles is different between the two experiments. We observe flat bubbles in the call market experiment and boom-and-bust cycles in the learning-to-forecast experiment.

COMMENTARY: A Market Structure That Fits the Needs of Portfolio Managers

Trading “these” securities for “those” (portfolio trades) can be expensive if done through our current continuous markets. This article compares a broker-implemented blind bid solution to this problem in a continuous market setting versus a combined value computerized call market that maximizes available liquidity to create balanced trades between such lists. The technology is known: combined value markets are in use today servicing markets in logistics contracts, emissions permits, spectrum licenses, and aerospace procurement. Should not financial concerns, such as custodial banks, be currently offering such services to their clients?

Call Market Experiments: Efficiency and Price Discovery through Multiple Calls and Emergent Newton Adjustments

We study multiple-unit, laboratory experimental call markets in which orders are cleared by a single price at a scheduled “call.” The markets are independent trading “days” with two calls each day preceded by a continuous and public order flow. Markets approach the competitive equilibrium over time. The price formation dynamics operate through the flow of bids and asks configured as the “jaws” of the order book with contract execution featuring elements of an underlying mathematical principle, the Newton-Raphson method for solving systems of equations. Both excess demand and its slope play a systematic role in call market price discovery. (JEL C92, D41, D44, G14)

Order Consolidation, Price Efficiency, and Extreme Liquidity Shocks

We show that the consolidation of orders is important for producing efficient prices, especially during times of high liquidity demand. The NYSE's centralized opening call market performs better than Nasdaq's decentralized opening process on typical trading days. The NYSE is much better than Nasdaq on witching days when index arbitrage activity subjects S&P 500 stocks to large, predictable, and mostly informationlessorder flow around quarterly futures contract expirations. Nasdaq opening price efficiency improves to NYSE levels once Nasdaq initiates a consolidated opening call in November 2004, but prices on the decentralized Nasdaq remain less efficient at other times of day.