The paper presents forecasts of headline and core inflation in Estonia with factor models in a recursive pseudo out-of-sample framework. The factors are constructed with a principal component analysis and are then incorporated into vector autoregressive (VAR) forecasting models. The analyses...

The use of principal component techniques to estimate approximate factor models with large cross-sectional dimension is now well established. However, recent work by Inklaar, Jacobs and Romp (2003) and Boivin and Ng (2005) has cast some doubt on the importance of a large cross-sectional...

Using monthly data for Belgium, France, Germany, Italy and Spain for the period 2002-2019, we build a Hierarchical Euro Area Dynamic Nelson-Siegel model that allows for time varying exposures of national factors on the common components, and for stochastic volatility both at the regional and...

The paper uses functional auto-regression to predict the dynamics of interest rate curve. It estimates the auto-regressive operator by extending methods of the reduced-rank auto-regression to the functional data. Such an estimation technique is better suited for prediction purposes as opposed to...

The purpose of this paper is to show that an affine model which incorporates the condition of no arbitrage enables improvements in forecasting the term structure of interest rates in Mexico. The three factors of the yield curve (level, slope and curvature) used in the model are estimated by the...

The purpose of this paper is to show that an affine model which incorporates the condition of no arbitrage enables improvements in forecasting the term structure of interest rates in Mexico. The three factors of the yield curve (level, slope and curvature) used in the model are estimated by the...

Using different econometric models, Diebold and Li (J Econom 130:337-364, 2006) addressed the practical problem of forecasting the yield curve by predicting the factors level, slope and curvature in the Nelson-Siegel framework. This paper has two main aims: on the one hand, to investigate the...

Following (Almeida, Ardison, Kubudi, Simonsen, & Vicente, 2018) we implement a segmented three factor Nelson-Siegel model for the yield curve using daily observable bond prices and short term interbank rates for Colombia. The flexible estimation for each segment (short, medium, and long)...

VARs are a popular tool for forecasting and structural analysis, but ill-suited to handle occasionally binding constraints, like the effective lower bound on nominal interest rates. We extend the VAR framework by modeling interest rates as censored observations of a latent shadow-rate process,...

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...