The Effects of Geopolitical Uncertainty in Forecasting Financial Markets: A Machine Learning Approach

Abstract

An important ingredient in economic policy planning both in the public or the private sector is risk management. In economics and finance, risk manifests through many forms and it is subject to the sector that it entails (financial, fiscal, international, etc.). An under-investigated form is the risk stemming from geopolitical events, such as wars, political tensions, and conflicts. In contrast, the effects of terrorist acts have been thoroughly examined in the relevant literature. In this paper, we examine the potential ability of geopolitical risk of 14 emerging countries to forecast several assets: oil prices, exchange rates, national stock indices, and the price of gold. In doing so, we build forecasting models that are based on machine learning techniques and evaluate the associated out-of-sample forecasting error in various horizons from one to twenty-four months ahead. Our empirical findings suggest that geopolitical events in emerging countries are of little importance to the global economy, since their effect on the assets examined is mainly transitory and only of regional importance. In contrast, gold prices seem to be affected by fluctuation in geopolitical risk. This finding may be justified by the nature of investments in gold, in that they are typically used by economic agents to hedge risk.

Which uncertainty is powerful to forecast crude oil market volatility? New evidence

“…Except for EPU, the linkage between financial asset volatility and Husted, Rogers, and Sun (2018)'s MPU index have also received attentions by many scholars (Kaminska & Roberts‐Sklar, 2018; Mei et al, 2019; Wohlfarth, 2018). Besides, some studies also identify the effect of GPR index proposed by Caldara and Iacoviello (2018) on oil price or volatility (Antonakakis, Gupta, Kollias, & Papadamou, 2017; Plakandaras et al, 2019; Plakandaras, Gogas, & Papadimitriou, 2018; Uddin et al, 2018). Finally, Baker et al (2016)'s EMV index which is related to equity market uncertainty can also influence the oil market returns and volatility (Aloui et al, 2016; Balcilar et al, 2016), because of the strong linkage between oil market and stock market (Boldanov, Degiannakis, & Filis, 2016; Ferreira, Pereira, Silva, & Pereira, 2019; Filis, 2010; Li & Wei, 2018).…”

Analyzing the degree of persistence of economic policy uncertainty using linear and non‐linear fourier quantile unit root tests

“…Plakandaras et al. (2019) tested the degree of persistence of 72 uncertainty indices using Hurst and Lyapunov exponents in rolling windows with the following results. (i) All uncertainty time series behave as a persistence process and predict that shocks to the series have long‐lasting effects.…”

“…However, the macroeconomic effects of the EPU index have investigated by huge number of empirical studies; a few empirical papers examined its stochastic properties. Plakandaras et al (2019) tested the degree of persistence of 72 uncertainty indices using Hurst and Lyapunov exponents in rolling windows with the following results. (i) All uncertainty time series behave as a persistence process and predict that shocks to the series have long-lasting effects.…”

“…Surveying the empirical literature indicates only three studies that analyzed the degree of persistence for the time series of the EPU index: Plakandaras et al. (2019), Gil‐Alana and Payne (2020), Solarin and Gil‐Alana (2021), Abakah et al. (2021), and Peng et al.…”

“…Surveying the empirical literature indicates only three studies that analyzed the degree of persistence for the time series of the EPU index: Plakandaras et al (2019), Gil-Alana and Payne (2020), Solarin and Gil-Alana (2021), Abakah et al (2021), andPeng et al (2022). As noted by Lin and Bai (2021), fluctuations of the EPU index reflect some synchronization with policy and economic events, like oil prices shocks and financial crises.…”