Evolving Economic Relationships: A TVP-VAR Analysis of Trade, World Uncertainty, and Stock Market Volatility in Europe

Understanding the intricate relationship between trade, uncertainty, and stock market volatility is fundamental to navigating economic fluctuations.This paper aims to examine the dynamic interdependencies between international trade, world uncertainty, and stock market volatility in 15 European countries using a Time-Varying Parameter Vector Autoregression (TVP-VAR) model.After extracting time-varying coefficients, we employ a Dynamic Factor Model (DFM) to identify common factors driving these dynamics.Our findings highlight significant patterns influenced by major economic events such as the European debt crisis, Brexit, and the COVID-19 pandemic and provide practical implications for better anticipation and response to economic shifts.This enhances economic stability and growth and fosters a more informed and enlightened approach to economic policy-making.

Authors

Publication Details

Journal
ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH
Published
2024-12-19
DOI
https://doi.org/10.24818/18423264/58.4.24.02
Citations
3
Primary Topic
Market Dynamics and Volatility
Type
article
Field-Weighted Citation Impact
3.39
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article

Evolving Economic Relationships: A TVP-VAR Analysis of Trade, World Uncertainty, and Stock Market Volatility in Europe

FILIP Radu Ion, Gheorghe Hurduzeu, LUPU Radu, Iulia Lupu
3 citations
ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH
Market Dynamics and Volatility
3.39
article

Evolving Economic Relationships: A TVP-VAR Analysis of Trade, World Uncertainty, and Stock Market Volatility in Europe

FILIP Radu Ion, Gheorghe Hurduzeu, LUPU Radu, Iulia Lupu
article en
3 citations

Abstract

Understanding the intricate relationship between trade, uncertainty, and stock market volatility is fundamental to navigating economic fluctuations.This paper aims to examine the dynamic interdependencies between international trade, world uncertainty, and stock market volatility in 15 European countries using a Time-Varying Parameter Vector Autoregression (TVP-VAR) model.After extracting time-varying coefficients, we employ a Dynamic Factor Model (DFM) to identify common factors driving these dynamics.Our findings highlight significant patterns influenced by major economic events such as the European debt crisis, Brexit, and the COVID-19 pandemic and provide practical implications for better anticipation and response to economic shifts.This enhances economic stability and growth and fosters a more informed and enlightened approach to economic policy-making.

ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCHVol. 58(4/2024)
Openalex Percentile: Top 6%
Market Dynamics and Volatility
3.39
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Evolving Economic Relationships: A TVP-VAR Analysis of Trade, World Uncertainty, and Stock Market Volatility in Europe — FILIP Radu Ion, Gheorghe Hurduzeu, et al. · ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH (2024) | TGRS Research Map | TGRS