We develop a new series of Canadian monetary policy shocks and analyze their impact on inflation and real GDP from 1996-2020. Our shocks are constructed as the daily change in the Nelson-Siegel yield curve factors after a monetary policy announcement. Because these shocks include information...

In this paper a dynamic probit model for recession forecasing under pseudo-real time is set up using a large set of macroeconomic and financial monthly indicators for Germany. Using different initial sets of explanatory variables, alternative dynamic probit specifications are obtained through an...

An OLS and probit framework is used to examine the predictive power of yield spreads with respect to GDP growth and recessions in the Eurozone from the 1990s to the recent past. Credit default swap (CDS) data on sovereign bonds, which provide a direct measure of default risk, are employed as...

Geostatistical spatial models are widely used in many applied fields to forecast data observed on continuous three-dimensional surfaces. We propose to extend their use to finance and, in particular, to forecasting yield curves. We present the results of an empirical application where we apply...

Recent studies documented a sufficient forecasting performance of shadow-rate models in the low yields environment. Moreover, it has been shown that including the macro-variables into the shadow-rate models further improves the results. We build on these findings and evaluate for the U.S....

This paper proposes a forecasting model that combines a factor augmented VAR (FAVAR) methodology with the Nelson and Siegel (NS) parametrization of the yield curve to predict the Brazilian term structure of interest rates. Importantly, we extract the principal components for the FAVAR from a...