We study the loss function of 15 European governments as implied by their budget balance forecasts. Results suggest that the shape of the loss function varies across countries. The loss function becomes more asymmetric as the forecast horizon increases and in advance of parliamentary election....

We report results on the ex ante predictability of monthly excess stock returns in Germany using real-time and revised macroeconomic data. Our real-time macroeconomic data cover the period 1994-2005. We report three results. 1) Real-time macroeconomic data did not contribute much to ex ante...

Based on the approach advanced by Elliott et al. (Rev. Ec. Studies. 72, 1197..1125, 2005), we analyzed whether the loss function of a sample of exchange rate forecasters is asymmetric in the forecast error. Using forecasts of the euro/dollar exchange rate, we found that the shape of the loss...

Using forecasts of the Brazilian real and the Mexican peso, we analyze the shape of the loss function of exchange-rate forecasters and the rationality of their forecasts. We find a substantial degree of cross-sectional heterogeneity with respect to the shape of the loss function. While some...

We use a Panel Smooth Transition Regression (STR) model to study nonlinearities in the expectationformation process in the US stock market. To this end, we use data from the Livingston survey to investigate how the importance of regressive and extrapolative expectations fluctuates over time as...

We use a boosting approach to study the time-varying out-of-sample informational content of various financial and macroeconomic variables for forecasting the volatility of gold-price fluctuations. We use an out-of-sample R2 statistic to evaluate forecasts as a function of the shape of a...

We use a machine-learning algorithm known as boosted regression trees (BRT) to implement an orthogonality test of the rationality of aggregate stock-market forecasts. The BRT algorithm endogenously selects the predictor variables used to proxy the information set of forecasters so as to maximize...

We use a quantile-boosting approach to compute out-of-sample forecasts of gold returns. The approach accounts for model uncertainty and model instability, and it allows forecasts to be computed under asymmetric loss functions. Different asymmetric loss functions represent different types of...

We report results on the ex ante predictability of monthly excess stock returns in Germany using real-time and revised macroeconomic data. Our real-time macroeconomic data cover the period 1994-2005. We report three results. 1) Real-time macroeconomic data did not contribute much to ex ante...