The currency composition of international portfolio assets

Galstyan, Vahagn; Mehigan, Caroline; Mercado, Rogelio

doi:10.1016/j.jimonfin.2019.102132

Cited by 4 publications

(1 citation statement)

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“…More recent papers on the structure of bond markets that incorporate information on the currency denomination of bonds includeDu and Schreger (2016),Hale and Spiegel (2012) and Hale, Jones and Spiegel (2017), among others.2 The IMF has recently started to report aggregate, but not bilateral, data on currency composition in their CPIS dataset. For an analysis, seeGalstyan, Mehigan and Mercado (2017).…”

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Currency matters: Analyzing international bond portfolios

Burger

Warnock

2018

Journal of International Economics

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Currency denomination is a prominent feature in the analysis of the structure of international bond markets, but is largely absent from analyses of cross-border investment in debt securities. This omission owes in part to the limitations of widely used datasets such as the IMF's CPIS data (on positions) and its BOP data (on flows): Neither identifies the currency denomination of the underlying bonds and both combine bonds of various currencies in a single data point. In this paper we show that bonds denominated in the investor's currency are special. We show this indirectly in a global dataset of bilateral bond holdings-indirectly because the global holdings dataset does not differentiate by currency denomination-and then more directly in datasets of US holdings of foreign bonds that do differentiate by currency. We find that the share of a country's bonds denominated in investors' currencies is an important determinant of the amount of cross-border investment it receives; factors associated with greater (or less) cross-border investment in bonds differ by currency denomination; and one phenomenon of international portfolios-the ever-present home bias-in some cases actually disappears when bonds are denominated in the investor's currency, suggesting that the home bias is to some extent a home currency bias.

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confidence: 99%