Narrow search
Showing 1 - 10 of 65,881
Cover Image
Assessing the uncertainty in central banks' inflation outlooks
Knüppel, Malte; Schultefrankenfeld, Guido - 2019
Recent research has found that macroeconomic survey forecasts of uncertainty exhibit several deficiencies, such as horizon-dependent biases and lower accuracy than simple unconditional uncertainty forecasts. We examine the inflation uncertainty forecasts from the Bank of England, the Banco...
Persistent link: https://www.econbiz.de/10011962843
Cover Image
SVARs identification through bounds on the forecast error variance
Volpicella, Alessio - 2019
Sign-restricted Structural Vector Autoregressions (SVARs) are increasingly common. However, they usually result in a set of structural parameters that have very different implications in terms of impulse responses, elasticities, historical decomposition and forecast error variance decomposition...
Persistent link: https://www.econbiz.de/10012037315
Cover Image
Modeling and Forecasting a Firm's Financial Statements with a VAR-VECM Model
Doornik, Bernardus Ferdinandus Nazar Van; de Medeiros, … - 2009
This paper details efforts at developing and estimating a Vector Autoregressive (VAR) econometric model representative of the financial statements of a firm. Although the model can be generalized to represent the financial statements of any firm, this work was carried out as a case study, where...
Persistent link: https://www.econbiz.de/10014211147
Cover Image
Combined Density Nowcasting in an Uncertain Economic Environment
Aastveit, Knut Are - 2015
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10013023300
Cover Image
Forecast-Error-Based Estimation of Forecast Uncertainty When the Horizon is Increased
Knüppel, Malte - 2016
(2014) in order to relax the condition on the data structure required for the SUR estimator to be independent from unknown … quantities. It turns out that the SUR estimator of forecast uncertainty tends to deliver large e¢ ciency gains compared to the … OLS estimator (i.e. the sample mean of the squared forecast errors) in the case of increased forecast horizons. The SUR …
Persistent link: https://www.econbiz.de/10012988712
Cover Image
Combined Density Nowcasting in an Uncertain Economic Environment
Aastveit, Knut Are - 2014
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10013040417
Cover Image
Forecasting limit order book liquidity supply-demand curves with functional AutoRegressive dynamics
Chen, Ying; Chua, Wee Song; Härdle, Wolfgang - 2016
Limit order book contains comprehensive information of liquidity on bid and ask sides. We propose a Vector Functional AutoRegressive (VFAR) model to describe the dynamics of the limit order book and demand curves and utilize the tted model to predict the joint evolution of the liquidity demand...
Persistent link: https://www.econbiz.de/10011518802
Cover Image
Combined density nowcasting in an uncertain economic environment
Aastveit, Knut Are; Ravazzolo, Francesco; Dijk, Herman … - 2014
We introduce a Combined Density Nowcasting (CDN) approach to Dynamic Factor Models (DFM) that in a coherent way accounts for time-varying uncertainty of several model and data features in order to provide more accurate and complete density nowcasts. The combination weights are latent random...
Persistent link: https://www.econbiz.de/10010465155
Cover Image
Forecasting with Approximate Dynamic Factor Models : The Role of Non-Pervasive Shocks
Luciani, Matteo - 2011
In this paper we investigate whether accounting for non-pervasive shocks improves the forecast of a factor model. We compare four models on a large panel of US quarterly data: factor models, factor models estimated on selected variables, Bayesian shrinkage, and factor models together with...
Persistent link: https://www.econbiz.de/10013120664
Cover Image
Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction
Liao, Yin - 2012
Recent literature has focuses on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting...
Persistent link: https://www.econbiz.de/10013105658