We derive forecast weights and uncertainty measures for assessing the role of individual series in a dynamic factor model (DFM) to forecast euro area GDP from monthly indicators. The use of the Kalman filter allows us to deal with publication lags when calculating the above measures. We find...

This paper considers Bayesian regression with normal and double-exponential priors as forecasting methods based on large panels of time series. We show that, empirically, these forecasts are highly correlated with principal component forecasts and that they perform equally well for a wide range...

This paper compares the predictive ability of the factor models of Stock and Watson (2002) and Forni, Hallin, Lippi, and Reichlin (2005) using a large panel of US macroeconomic variables. We propose a nesting procedure of comparison that clarifies and partially overturns the results of similar...

This paper develops a new methodology for simulating fixed-income return distributions. It is shown that a traditional factor risk model, when augmented with reference returns, is capable of generating visually consistent return distributions for a broad range of fixed income instruments such as...

We propose a theoretical framework for assessing whether a forecast model estimated over one period can provide good forecasts over a subsequent period. We formalize this idea by defining a forecast breakdown as a situation in which the out-of-sample performance of the model, judged by some loss...

Monetary policymakers in advanced transition economies such as Poland are increasingly interested in how inflation responds to changes in policy instruments and other economic forces. In this paper, measures of underlying CPI inflation based upon optimal trimming concepts are developed. The...

We propose probability and density forecast combination methods that are defined using the entropy regularized Wasserstein distance. First, we provide a theoretical characterization of the combined density forecast based on the regularized Wasserstein distance under the Gaus-sian assumption....

This paper studies the comparative predictive accuracy of forecasting methods using mixed-frequency data, as applied to nowcasting Philippine inflation, real GDP growth, and other related macroeconomic variables. It focuses on variations of mixed-frequency dynamic latent factor models (DFM for...

Prediction of future movement of stock prices has been a subject matter of many research work. There is a gamut of literature of technical analysis of stock prices where the objective is to identify patterns in stock price movements and derive profit from it. Improving the prediction accuracy...

This paper develops a means of visualising the vulnerability of complex systems of financial interactions resulting from the changing risk tolerance of investors. The investors' risk behavior contributes to the buildup of vulnerability in crisis and in calm periods. We show how both time-varying...