We describe conditions on signal distributions that are necessary and sufficient for informational herding in a stylized model of sequential specialist security trading. Curiously, there can be persistent herding even with signals that satisfy the Monotone Likelihood Ratio Property. Price paths are strongly biased in the direction of the herd but prices are also very sensitive to movements agai...

To inform theory and to investigate the practical application of prediction markets in a setting where the distribution of information across agents is critical, we conducted markets designed to forecast post-IPO valuations before a particularly unique IPO: Google. Because prediction markets allow us to infer the distribution of information before the IPO, the combination of results from our ma...

In down-payment constrained housing consumption models, increases in house prices could trigger household mobility decisions in housing markets. This study empirically tests house price dynamics associated with the mobility of households in the public resale and private housing markets in Singapore. The results show that stochastic permanent breaks were found in the public housing resale prices...

We develop a model in which boundedly rational agents apply technical and fundamental analysis to identify trading signals in two different speculative markets. Whether an agent trades and, if so, in which market with which strategy depends on profit considerations. As it turns out, an ongoing evolutionary competition between the trading strategies causes complex price dynamics which closely re...

I formulate a stylized Glosten-Milgrom model of financial market trading in which people are allowed to time their trading decision. The focus of the analysis is to understand people’s timing behavior and how it affects bidand offer-prices and volume. Assuming heterogeneous quality of information, not all informed traders choose to trade immediately but some chose to delay, although they expect...

Permanent and widespread psychological biases affect both the subjective probability of future economic events and their retrospective interpretation. They may give rise to a systematic gap between (over-critical) judgments and (over-optimistic) expectations the “forecast” error. When things go bad, then, psychology suggests that people tend to become particularly optimistic, amplifying the for...

In recent “learning to forecast” experiments (Hommes et al. 2005), three different patterns in aggregate price behavior have been observed: slow monotonic convergence, permanent oscillations, and dampened fluctuations. We show that a simple model of individual learning can explain these different aggregate outcomes within the same experimental setting. The key idea is evolutionary selection amo...

This paper derives analytical results for determination of the window size that explores the trade-off between bias and forecast error variance to minimize the mean squared forecast error in the presence of breaks. We show analytically how to determine the estimation window optimally for the case with strictly exogenous regressors. Through Monte Carlo simulations the paper compares the performa...

We study a model in which individual agents use simple linear first order price forecasting rules, adapting them to the complex evolving market environment with a smart Genetic Algorithm optimization procedure. The novelties are: (1) a parsimonious experimental foundation of individual forecasting behaviour; (2) an explanation of individual and aggregate behavior in four different experimental ...