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...

We derive forecasts for Markov switching models that are optimal in the MSFE sense by means of weighting observations. We provide analytic expressions of the weights conditional on the Markov states and conditional on state probabilities. This allows us to study the e↵ect of uncertainty around states on forecasts. It emerges that, even in large samples, forecasting performance increases substan...

Recent evidence suggests that many economic time series are subject to structural breaks, yet little is known about the properties of alternative forecasting methods for such data. This paper proposes a new method for determining 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 in autoregre...

Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as GARCH models, are investigated, to determine if they are more appropriate for predicting future return volatility. Employing German DAX-index retu...

Prediction Markets in Theory and Practice Prediction Markets, sometimes referred to as “information markets,” “idea futures” or “event futures”, are markets where participants trade contracts whose payoffs are tied to a future event, thereby yielding prices that can be interpreted as market-aggregated forecasts. This article summarizes the recent literature on prediction markets, highlighting b...

This paper analyzes extreme co-movements between the Australian and Canadian commodity currencies, and the gold and oil markets respectively, within a multivariate extension of the Hawkes-POT model. The intensity of extreme events in the Australian dollar are influenced by extreme events in gold, while the size of extreme events in the Canadian dollar are driven by extreme events in crude oil. ...

This paper brings together two important but hitherto largely unrelated areas of the forecasting literature, density forecasting and forecast combination. It proposes a simple data-driven approach to direct combination of density forecasts using optimal weights. These optimal weights are those weights that minimise the ‘distance’, as measured by the Kullback-Leibler Information Criterion, betwe...

This paper investigates whether the degree of predictability can be explained by existing asset pricing models, and provides two theoretical upper bounds on the R-square of the regression of stock returns on predictors for given classes of models of interest. Empirically, we find that the predictive R-square is significantly larger than the upper bounds permitted by well known asset pricing mod...

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...