We introduce a forecasting method that closely matches the econometric properties required by the theory of exchange rate prediction. Our approach formally models (i) when (and if) predictor variables enter or leave a regression model, (ii) the degree of parameter instability, (iii) the...

We introduce a novel dynamic Bayesian model combination approach for predicting aggregate stock returns. Our method involves combining predictive densities in a data-adaptive fashion and simultaneously features (i) uncertainty about relevant predictor variables, (ii) parameter instability, (iii)...

This paper considers how an investor in the foreign exchange market can exploit predictive information by means of flexible Bayesian inference. Using a variety of different vector autoregressive models, the investor is able, each period, to revise past predictive mistakes and learn about...

We propose a framework for combining portfolio rules while mitigating the impact of estimation error. Our main goal is to integrate heterogeneous rules that previously proposed combination methods are unable to accommodate, enabling researchers and investors to leverage established and ongoing...

We propose a solution to the Closed-End Fund Puzzle in financial markets without a free lunch with vanishing risk. Our results are consistent with both the time-series and the cross-sectional aspect of the Closed-End Fund Puzzle. It turns out that a closed-end fund cannot be created if the fund...

We introduce a novel dynamic portfolio choice method, focusing on robust out-of-sample performance rather than on optimal in-sample performance. We therefore devise a strategy that rigorously tackles the problem of estimation error. The method involves defining a discrete set of single-period...

We address the question of how to construct optimal confidence bands with a predefined nominal coverage from a finite set of sample paths. We introduce a mixed-integer optimization algorithm to calculate globally optimal pathwise confidence bands. We illustrate the method with an example of...

We investigate whether predictive methods advanced in statistics and econometrics are capable of detecting the number and identities of relevant predictors for economic time series. Further, we study the relation between support recovery properties and point predictive accuracy. A novel feature...