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Enhancing Forecasting Accuracy of Financial Time Series by Hybrid VAR and Transfer Function Models [PDF]
The Egyptian Statistical JournalOur study suggests an approach that integrates vector autoregressive and transfer function models to enhance the modeling and forecasting of financial time series.
Mona Abdel Bary
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New evidence from NARDL model on CO2 emissions: Case of Morocco [PDF]
E3S Web of Conferences, 2021 The main objective of this study is to examine the effect of sickle energy consumption, renewable energy, and forest area on the emission of carbon dioxide (CO2) in Morocco.
Chikri Hassan +3 more
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Bias-Correction in Vector Autoregressive Models: A Simulation Study
Econometrics, 2014 We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models.
Tom Engsted, Thomas Q. Pedersen
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On Vector Autoregressive Modeling in Space and Time [PDF]
SSRN Electronic Journal, 2010 Despite the fact that it provides a potentially useful analytical tool, allowing for the joint modeling of dynamic interdependencies within a group of connected areas, until lately the VAR approach had received little attention in regional science and spatial economic analysis.
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Model uncertainty in Panel Vector Autoregressive models [PDF]
European Economic Review, 2014 We develop methods for Bayesian model averaging (BMA) or selection (BMS) in Panel Vector Autoregressions (PVARs). Our approach allows us to select between or average over all possible combinations of restricted PVARs where the restrictions involve interdependencies between and heterogeneities across cross-sectional units.
Koop, Gary, Korobilis, Dimitris
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The Vector Autoregressive Model [PDF]
, 1998 Abstract In Chapter 2 of SJ the basic facts about the vector autoregressive model with unrestricted parameters are given, and the asymptotics of the statistical theory is given in the stationary case. The p-dimensional process Xt considered throughout the book is generated by the autoregressive equations where X-k+i, ...
Peter Reinhard Hansen, Søren Johansen
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A sparsity-controlled vector autoregressive model [PDF]
Biostatistics, 2016 Vector autoregressive (VAR) models constitute a powerful and well studied tool to analyze multivariate time series. Since sparseness, crucial to identify and visualize joint dependencies and relevant causalities, is not expected to happen in the standard VAR model, several sparse variants have been introduced in the literature.
Carrizosa Priego, Emilio José +2 more
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Stationary Threshold Vector Autoregressive Models [PDF]
Journal of Risk and Financial Management, 2018 This paper examines the steady state properties of the Threshold Vector Autoregressive model. Assuming that the trigger variable is exogenous and the regime process follows a Bernoulli distribution, necessary and sufficient conditions for the existence of stationary distribution are derived.
Galyna Grynkiv, Lars Stentoft
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Predicting Benzene Concentration Using Machine Learning and Time Series Algorithms
Mathematics, 2020 Benzene is a pollutant which is very harmful to our health, so models are necessary to predict its concentration and relationship with other air pollutants.
Luis Alfonso Menéndez García +4 more
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Bayesian Nonparametric Vector Autoregressive Models [PDF]
SSRN Electronic Journal, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kalli, M, Griffin, JE
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