Tails of Foreign Exchange-at-Risk (FEaR)
Daniel Ostry
Janeway Institute Working Papers from Faculty of Economics, University of Cambridge
Abstract:
I build a model in which speculators unwind carry trades and hedgers fly to relatively liquid U.S. Treasuries during global financial disasters. The net effect of these flows produces an amplified U.S. dollar appreciation against high-yield currencies in disasters and a dampened depreciation, or even an appreciation, against low-yield ones. I verify this prediction by examining deviations from uncovered interest parity (UIP) within a novel quantile-regression framework. In the tail quantiles, I show that interest differentials predict high-yield currencies to suffer depreciations ten times as large as suggested by UIP, while spikes in Treasury liquidity premia meaningfully appreciate the dollar regardless of the U.S. relative interest rate. A complementary analysis of speculators’ and hedgers’ currency futures positions substantiates my model’s mechanism and highlights that hedging agents imbue the U.S. dollar with its unique safe-haven status.
Keywords: Disaster Risk; Exchange Rates; Liquidity Yields; Quantile regression; U.S. Safety (search for similar items in EconPapers)
JEL-codes: C22 F31 G15 (search for similar items in EconPapers)
Date: 2023-06-07
New Economics Papers: this item is included in nep-mon, nep-opm and nep-rmg
Note: dao33
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://www.janeway.econ.cam.ac.uk/working-paper-pdfs/jiwp2311.pdf
Related works:
Working Paper: Tails of Foreign Exchange-at-Risk (FEaR) (2023) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:cam:camjip:2311
Access Statistics for this paper
More papers in Janeway Institute Working Papers from Faculty of Economics, University of Cambridge
Bibliographic data for series maintained by Jake Dyer ().