Non-U.S. financial institutions hold precautionary positions in U.S. dollar assets as protection against financial shocks. This gives rise to a safety premium on the dollar. The premium varies over time and, hence, not only accounts for contemporaneous exchange rate dynamics but also helps to predict exchange rate trends. An IMF paper measures non-U.S. banks’ dollar demand for 26 economies as the ratio of assets denominated in dollar to total assets by nationality. Demand for U.S. dollars tends to surge following negative financial market shocks and causes dollar strength. Non-U.S. holdings of dollar assets have also been a highly significant predictor of dollar trends in subsequent years. Thus, large holdings have heralded dollar depreciation in the past.
Adrian, Tobias and Peichu Xie (2020), “The Non-U.S. Bank Demand for U.S. Dollar Assets”, IMF Working Paper, WP/20/101, June 2020.
The below are quotes from the paper. Cursive text and text in brackets have been added for clarity.
The post ties up with this site’s summary on implicit subsidies in financial markets, particularly the section on subsidy-based strategies in the FX market.
Causes of dollar demand from non-U.S. banks
“As financial intermediaries in the U.S. are better able to deal with funding problems following negative shocks, the United States consumes more…and runs a trade deficit based on higher financial income that it earns as compensation for greater risks it takes….The financial intermediaries in the rest of the world accumulate precautionary long positions in USD safer assets in order to [mitigate] negative shocks. When bad times hit, capital losses on the external portfolio of the U.S. lead to a wealth transfer to the rest of the world…The U.S. dollar emerges as the reserve currency because it appreciates during bad times, thus USD denominated assets represent global safe assets by providing a good hedge.”
“A number of papers document that there is a positive and countercyclical safety premium for the U.S. dollar… Our paper first documents the counter-cyclicality in USD asset demand of marginal investors by using a quantity measure, i.e., the USD asset share of non-U.S. banks…There is a ‘safe asset demand channel’ of non-U.S. financial intermediaries at play – the non-U.S. financial intermediaries pay a safety premium to hold the USD denominated assets…because…when negative shocks happen…the U.S. dollar appreciates contemporaneously.”
“The demand of USD denominated safe assets by non-U.S. banks [is] expected to be a function of the safety and liquidity of substitute assets and the balance sheet capacity of non-U.S. banks to bear risks…Intermediary balance sheet capacity is a significant pricing factor for risky assets…Higher USD safe asset demand from non-U.S. banks corresponds to lower balance sheet capacity of non-U.S. banks.”
“The demand for safe USD assets from non-U.S. banks is associated with a time-varying currency risk premium, so it not only helps account for contemporaneous changes in exchange rates, but also helps predict exchange rate dynamics over the longer horizon both in-sample and out of sample.”
Measuring dollar demand of non-U.S. banks
“We present a new measure of foreign ‘safe asset’ demand for the U.S. dollars, constructed as the share of non-U.S. banks’ USD assets…for 26 advanced and emerging economies…The USD asset share is computed for each economy as the ratio of assets denominated in USD to total assets of the non-U.S. banking system on nationality basis, based on where the ultimate parent of reporting banking-system is headquartered. The USD positions include international positions, that is the USD operations outside the U.S., and U.S.-based branch operations.”
“Our analysis is performed by aggregating non-U.S. banks’ balance sheets at economy level on nationality basis. Relying on USD balance sheets by nationality of reporting non-U.S. banks, a graphical representation of the different aggregates is shown in [the figure below].”
“The U.S. Treasury premium is positive across almost all economies, which suggests that investors are willing to pay a safety premium to hold U.S. Treasury securities relative to foreign government bonds in that economy…The average U.S. Treasury premium, i.e., the U.S. Treasury premium against a basket of 16 government bonds, is around 38 bps over the sample period.”
Dollar demand and concurrent exchange rate impact
“Demand for USD safe assets from financial intermediaries of the rest of the world increases strongly following negative shocks because of flight to safety…The USD exchange rate appreciates contemporaneously, thus lowering the investors’ expected future return from owning U.S. safe assets…There is a strong contemporaneous relationship between the exchange rate and the demand for USD assets from non-U.S. banks in the time series and…a causal interpretation using a set of novel instrumental variables.”
“Time-series regressions show that the non-U.S. bank demand for U.S. dollar assets significantly contributes to the explanation of contemporaneous movements in the USD exchange rate...The significance and economic magnitude are unchanged by including the U.S. Treasury premium and the home minus U.S. interest differential as controls. Furthermore, the USD asset share significantly correlates with 11 out of 16 bilateral USD exchange rate movements vis-à-vis individual foreign currencies.”
“We establish a causal relationship [empirically] using valid demand shifters…One instrumental variable is the Treasury premium of non-U.S. G10 countries, which is proportional to the convenience yield on substitute safe assets. A second instrumental variable is the sovereign risk of substitute Treasury securities from non-U.S. G10. These two instrumental variables used as demand shifters belong to the group that captures the safety and liquidity of non-U.S. G10 currencies that is the closest substitute for the USD assets. A third instrumental variable used as demand shifter is the shock to the leverage of non-U.S. banks (orthogonal to the leverage of U.S. banks), which relates to the balance sheet capacity of non-U.S. banks to bear risks.”
“Our findings suggest that the USD exchange rate vis-à-vis individual foreign currency of corresponding economy is, to a large extent, driven by a simple safe asset demand story from the perspective of non-U.S. banks. Higher demand for the USD by non-U.S. banks from that economy is driving down the currency where the respective banks are headquartered.”
“All three sets of instrumental variables are shown to be valid in a statistical sense, and economic intuition suggests that these are exogenous demand shifters. We find that…
- an increase in the Treasury premium of non-U.S G10 countries is significantly associated with decreasing demand for USD assets by non-U.S. banks,
- higher sovereign risk in Treasury securities of non-U.S. G10 countries is associated with a significant increase in the foreign demand for USD safe assets, and
- higher leverage of non-U.S. banks is significantly related to higher demand for safe USD assets.”
“A stronger USD coincides with a higher shadow cost of banks’ balance sheet capacity, so it can price the cross-section of covered interest parity deviations and is associated with lower growth of cross-border bank lending denominated in the USD.”
Dollar demand and subsequent exchange rate trends
“When there is a positive innovation to USD asset demand, the U.S. dollar appreciates contemporaneously, [but]…forecasting regressions…[show] a U.S. dollar depreciation one, two, three, and five years out. These forecasting results are statistically significant and economically large.”
“We document highly significant (i.e., at the 1% level) out-of-sample forecastability for the U.S. dollar exchange rates against a basket of 16 currencies, as well as for the vast majority of bilateral exchange rates. To our knowledge, the strength of out-of-sample forecasting power from a quantity variable is unprecedented in the literature on exchange rates.”
“As a robustness check, we augment 9 popular exchange rate models…with the USD asset demand from non-U.S. banks in out-of-sample forecasting tests. We find that the out-of-sample forecasting performance improves after we incorporate the average USD asset demand for all 9 models.”
“Average currency excess returns are systematically related to the cross-section of betas with respect to the USD asset share.”