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Precious metals and currency markets during the Russia-Ukraine conflicts inflationary periods

Research in International Business and Finance

Indexing : Scopus-Q1, WoS: SSCI, ‘B’ category journal in ABDC, Listed in ABS-2, impact factor 6.5, HEC W-Category.
Abstract

The contemporary conflict between two countries Russia and Ukraine has caused intensification in the increasing prices of commodities and energy owing to the supply chain disruption and the sanctions imposed on both countries. The previous literature has validated that Russia-Ukraine conflict substantially affects financial and economic operations of other countries. Therefore, the key aim of conducting this study is to inspect the dynamic spillover connectedness between the four leading precious metals (such as Gold, Palladium, Platinum, and Silver) and seven major currency markets (including Euro, British Pound, Australian Dollar, Swiss Franc, Japanese Yen, Canadian Dollar, and Chinese Yuan). The study includes the dataset from 24 January 2022 to 31 May 2022 to cover the inflationary period. Accordingly, the Time-Varying Parameter Vector Autoregression framework is applied. Granger linear causality and BDS nonlinear causality techniques are also employed to examine the causal effect of geopolitical risk in aforementioned connectedness. The findings reveal that Platinum has a strong spillover towards all the considered currencies except the Japanese Yen. The increasing demand for Platinum during the conflict secured it to receive the spillover. While the Japanese Yen is a net transmitter of spillover indicating the Japanese Yen as sturdiest currency during the conflict. The causality test reveals that geopolitical risk causes spillover connectedness across the precious metals and the currency markets during inflationary period. This study is significant for policymakers, investors, and portfolio managers while developing strategies or making critical investment decisions.

Keyword

Dynamic Spillover Connectedness, Precious Metals, Currency Markets, Geopolitical Risk, Inflationary Period, Russia-Ukraine Conflict, Time-Varying Parameter Vector Autoregression.

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