Results 271 to 280 of about 627,025 (314)
Some of the next articles are maybe not open access.
Structural VAR models in the Frequency Domain
Journal of Econometrics, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guay, Alain, Pelgrin, Florian
openaire +1 more source
From VAR models to Structural VAR models
1997In this chapter we introduce the philosophy, the basic concepts and definitions of VAR analysis (sections 1.1 and 1.2). After that, in section 1.3 we discuss the problems of VAR estimation and in section 1.4 we describe the possible uses of VAR models. Then in section 1.5 we start dealing with Structural VAR analysis, pointing out the main features of ...
Gianni Amisano, Carlo Giannini
openaire +1 more source
SSRN Electronic Journal, 2005
This paper analyses several volatility models by examining their ability to forecast the Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by
Timotheos Angelidis +2 more
openaire +1 more source
This paper analyses several volatility models by examining their ability to forecast the Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by
Timotheos Angelidis +2 more
openaire +1 more source
2023
Credit value at risk (VaR) is used for measuring and analyzing credit risk of a portfolio. The basic methodology of the Credit VaR employs the credit migration approach spearheaded by RiskMetrics. It assumes that obligor's credit quality is determined by the obligor's asset value, which in turn is approximated by its standardized equity return.
openaire +1 more source
Credit value at risk (VaR) is used for measuring and analyzing credit risk of a portfolio. The basic methodology of the Credit VaR employs the credit migration approach spearheaded by RiskMetrics. It assumes that obligor's credit quality is determined by the obligor's asset value, which in turn is approximated by its standardized equity return.
openaire +1 more source
An Evaluation Framework for Alternative VaR Models
SSRN Electronic Journal, 2002In this paper we investigate the ability of different models to produce useful var-estimates for exchange rate positions. Our analysis shows that it is important to take into account parameter uncertainty, since this leads to uncertainty in the predicted var. We make this uncertainty in the var explicit by means of simulation.
Bams, Dennis +2 more
openaire +2 more sources
, 2014 We confirm that standard time-series models for US output growth, inflation, interest rates and stock market returns feature non-Gaussian error structure. We build a 4-variable VAR model where the orthogonolised shocks have a Student t-distribution with a time-varying variance.
Ching-Wai (Jeremy) Chiu +2 more
openaire +1 more source
Sparse Change-Point VAR models
SSRN Electronic Journal, 2019AbstractChange‐point (CP) VAR models face a dimensionality curse due to the proliferation of parameters that arises when new breaks are detected. We introduce the Sparse CP‐VAR model which determines which parameters truly vary when a break is detected.
Dufays, A, Li, Z, Rombouts, JVK, Song, Y
openaire +2 more sources
Markov-switching mixed-frequency VAR models
International Journal of Forecasting, 2015Abstract This paper introduces regime switching parameters to the Mixed-Frequency VAR model. We begin by discussing estimation and inference for Markov-switching Mixed-Frequency VAR (MSMF-VAR) models. Next, we assess the finite sample performance of the technique in Monte-Carlo experiments.
Foroni, Claudia +2 more
openaire +4 more sources
2016
The discussion of forecasting with VAR models proceeds in two steps. First, we assume that the parameters of the model are known. Although this assumption is unrealistic, it will nevertheless allow us to introduce and analyze important concepts and ideas.
openaire +1 more source
The discussion of forecasting with VAR models proceeds in two steps. First, we assume that the parameters of the model are known. Although this assumption is unrealistic, it will nevertheless allow us to introduce and analyze important concepts and ideas.
openaire +1 more source
A spectral decomposition for structural VAR models
Empirical Economics, 1996Based on structural VARs, this paper proposes a spectral decomposition which allows to infer the effects of changes in one variable on the other variables in the frequency domain. It is shown that there is a close relationship between this concept and conventional forecast error variance decomposition techniques for VARs.
openaire +2 more sources