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Using internet search keyword data for predictability of precious metals prices: Evidence from non-parametric causality-in-quantiles approach

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Indexing : Impact factor: 5.634, Scopus Q1, ABS, ABDC
Abstract

This investigation examines how Google trends-based information can influence predictability of precious metals prices by utilizing Linear Granger causality & non-parametric causality in quantiles approach. Data ranges from January (2004) to March (2021). We have incorporated the four most popular metals (i.e., Gold, Platinum, Palladium, & Silver) & Crude oil. Although findings obtained from linear Granger causality showed no causal link between Google trends series & oil and precious metals prices, rather findings obtained from the non-parametric test show the existence of a non-linear association among constructs. Non-parametric test results show Google trends series can predict the prices of precious metals. Therefore, we conclude that investors, before making investment decisions, first seek information available online, i.e., on Google Trends, to gain some insights about future price movement that would be ideal for any investor. Moreover, investors, policymakers can get noteworthy awareness from this research for thinking out of the box while making investments.

Keyword

Google trends, Precious metals, Crude oil, Non-parametric causality-in-quantiles, Investors

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