In this paper, we use Google Trends data for exchange rate forecasting in the context of a broad literature review that ties the exchange rate movements with macroeconomic fundamentals. The sample covers 11 OECD countries’ exchange rates for the period from January 2004 to June 2014. In out‐of‐sample forecasting of monthly returns on exchange rates, our findings indicate that the Google Trends search query data do a better job than the structural models in predicting the true direction of changes in nominal exchange rates. We also observed that Google Trends‐based forecasts are better at picking up the direction of the changes in the monthly nominal exchange rates after the Great Recession era (2008–2009). Based on the Clark and West inference procedure of equal predictive accuracy testing, we found that the relative performance of Google Trends‐based exchange rate predictions against the null of a random walk model is no worse than the purchasing power parity model. On the other hand, although the monetary model fundamentals could beat the random walk null only in one out of 11 currency pairs, with Google Trends predictors we found evidence of better performance for five currency pairs. We believe that these findings necessitate further research in this area to investigate the extravalue one can get from Google search query data.

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The literature has not settled down on safe haven property of gold in the emerging and developing countries. Therefore, we revisit the international evidence on hedging and safe haven role of gold for 34 emerging and developing countries with a span of daily data covering January 2000-November 2018. We employ the GARCH-copula approach to estimate the lower-tail extreme dependencies of the joint distribution of gold and equity returns. We also introduce a new definition for the strong safe haven property of an asset. Our findings indicate that while gold serves as a hedging instrument for all countries in our sample, we got evidence of weak safe haven property for gold, for domestic investors, only in 20 countries, and a strong safe haven asset (SHA) only in 9 countries.

In this article, we contribute to the current literature on market disciplining of the sovereign governments of the developing countries by distinguishing both sides of the market discipline hypothesis by adopting three-stage least square estimation to incorporate the contemporaneous feedback effects between primary structural budget balances and the country's default-risk premiums. We provide empirical evidence of a unidirectional causal relationship between a country's default-risk premium and primary structural budget balances with the direction flowing from primary structural budget balances to country's risk premium in 40 developing countries over the period . We also employ the Arellano-Bond dynamic panel generalized methods of moments estimation to control for this joint determination of primary structural budget balances and the country's default-risk premium, and find supportive evidence of undisciplined sovereign governments and of nonlinearly behaving well-functioning financial markets in the sample countries. (JEL C5, G1, G3)