Wavelet Coherence Approach Linking Russo-Ukrainian War, Oil Prices, Geopolitical Risk, Stock Market, and Policy Uncertainty in the Global Economy

Abstract

This paper investigates the multidimensional linkages among geopolitical risk (GPR), policy uncertainty (EPU), oil prices (WTI), and global stock markets (S&P 500 and RTSI) under the impact of the Russo-Ukrainian War (2021–2023). Using wavelet coherence (WTC) analysis, we explore both short- and long-term co-movements across the time-frequency domain. The results reveal strong synchronization patterns and directional causality among financial and energy variables, illustrating a closed feedback loop between local geopolitical instability and global economic volatility.

Methodology

We apply Continuous Wavelet Transform (CWT) and Cross Wavelet Transform (XWT) to quantify dynamic correlations and lead-lag relationships between the variables. The squared wavelet coherence (R^2(p,q)) serves as a localized correlation coefficient (0–1) across time and scale.
Monte Carlo simulations define the 5% significance contour. Arrow directions indicate causal flow:
→ positive correlation, ← negative correlation, ↗ variable X leads Y, ↘ variable Y leads X.
This approach allows us to distinguish scale-specific dependencies invisible to traditional VAR or Granger models.

Results

• S&P500–GPR: high-frequency coherence post-war indicates stock markets amplify geopolitical shocks.
• Oil–S&P500: strong bidirectional dependence; oil prices lead equity markets in early conflict phases.
• EPU–GPR: alternating short- and mid-term coherence shows mutual reinforcement between policy and geopolitical risk.
• RTSI–Oil: energy markets react immediately to Russian market fluctuations; long-term feedback through global energy channels.
• EPU–Oil: policy uncertainty initially lags oil volatility but dominates in the later phase.

Discussion

Findings demonstrate a closed cyclical mechanism:

War → ↑GPR → ↑EPU → ↓Stock Markets → ↑Oil Prices → ↑GPR.

This feedback loop highlights how geopolitical tensions propagate through financial and energy systems, offering a robust empirical framework for assessing cross-market contagion in crisis periods.

DOI

10.23977/ICEMESS2023.114

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Recommended citation: R. Zhang, Y. Shi, and X. Song (2023). "Wavelet Coherence Approach Linking Russo-Ukrainian War, Oil Prices, Geopolitical Risk, Stock Market, and Policy Uncertainty in the Global Economy." *Proceedings of the 2023 International Conference on Education, Management, Economics and Social Science (ICEMESS 2023)*. DOI: 10.23977/ICEMESS2023.114.
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