Our market experiment investigates the extent to which traders learn from the price, differentiating between situations where orders are submitted before versus after the price has realized. When market participants have to submit their bids conditional on the price, they show a bias by reacting...

This experiment compares the price dynamics and bubble formation in an asset market with a price adjustment rule in three treatments where subjects (1) submit a price forecast only, (2) choose quantity to buy/sell and (3) perform both tasks. We find deviation of the market price from the...

This exercise offers an innovative learning mechanism to model economic agent's decision-making process using a deep reinforcement learning algorithm. In particular, this AI agent is born in an economic environment with no information on the underlying economic structure and its own preference....

We review the recent literature on the determinants and effects of housing market expectations. We begin by providing an overview of existing surveys that elicit housing market expectations, and discuss how those surveys may be expanded in the future. We then document a number of facts about...

We develop a model of firm learning in volatile markets with noisy signals and test its predictions using historical German data. Firms' forecasts improve with age. We exploit German Reunification as a natural experiment where firms in the East are treated with ignorance about the distribution...

We experimentally investigate how price expectations are formed in a large asset market where subjects' only task is to forecast the future price of a risky asset. The realized prices depend on these expectations. We observe small (6 participants) and large markets (about 100 participants). In...