Suchergebnisse

PurposeThe study aims to examine the relationship among economic policy uncertainty (EPU), geopolitical-risks (GPR), the interaction (EPGR) of EPU and GPR and the returns of gold, silver, platinum, palladium and rhodium using monthly data from January (1997) to May (2021).Design/methodology/approachThe paper employs the Markov-switching and the novel Shi et al. (2020) bootstrap time-varying Granger-causality approach.FindingsThough the Markov-switching shows variation in the responses of precious metals to EPU, GPR and EPGR across low and high states, the paper observes the safe-haven potential of the precious metals in the high regime while the hedging potency is also evident in the results. To further substantiate the safe-haven and hedging properties, the time-varying Granger-causality shows the causal effect of EPU on all the selected precious metal returns coinciding with global events. While the authors show that GPR Granger causes platinum, palladium and rhodium consistently under the rolling/recursive-evolving tests, the authors cannot find the causal effect of GPR on gold and silver returns across the algorithms. The paper also observes persistence in the causal effect of EPGR on palladium and platinum across all the algorithms, while gold and rhodium only show consistency in the responses under the rolling- and recursive-evolving algorithms given the conditions of homoscedasticity and heteroscedasticity.Practical implicationsThe authors' results are essential to investors and policymakers since both typically leverage the hedging and safe-haven characteristics of precious metals to obviate downside risks during highly uncertain periods.Originality/valueThe authors' techniques allow examining the hedging and safe-haven properties of precious metals across regimes and date-stamp critical periods of causation inherent in the relationship.

Uncertainty may affect economic behavior of individuals and firms in a wide variety of ways, with typically negative consequences for economic growth. It is due to this fact, combined with rising political uncertainty observed lately in many countries, that uncertainty has gained increasing attention in economic literature, too. In this paper, we construct a measure of economic uncertainty for Finland based on Finnish news titles, collected from the YLE's (the Finnish broadcasting company) website. To construct the index, we utilize machine learning and natural language processing (NLP) techniques, and in this paper, specifically, a transformed naive Bayes text classifier. On basis of the model evaluation, the constructed uncertainty index seems helpful in giving a timely assessment of the current state of the Finnish economy. We find a strong negative correlation between our index and the consumer confidence index by Statistics Finland, and most remarkably, our index seems to lead the consumer confidence index by one month.