ANALYTICAL Strains in Offshore US Dollar Funding during the COVID-19 Crisis - Some Observations - International Monetary Fund
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ANALYTICAL
NOTES
Strains in Offshore US Dollar
Funding during the COVID-19 Crisis
Some Observations
NOTE 20/01Strains in Offshore US Dollar Funding
during the COVID-19 Crisis
Some Observations
Adolfo Barajas, Andrea Deghi, Salih Fendoglu, and Yizhi Xu
July 2020
I N T E R N A T I O N A L M O N E T A R Y F U N D©2020 International Monetary Fund
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Names: Barajas, Adolfo. | Deghi, Andrea. | Fendoglu, Salih. | Xu, Yizhi (Economist). | International
Monetary Fund. Monetary and Capital Markets Department, issuing body. | International Monetary
Fund, publisher.
Title: Strains in offshore US dollar funding during the COVID-19 crisis : some observations / Adolfo
Barajas, Andrea Deghi, Salih Fendoglu, and Yizhi Xu.
Other titles: MCM analytical notes (International Monetary Fund).
Description: Washington, DC : International Monetary Fund, 2020. | MCM analytical notes (Inter-
national Monetary Fund). | July 2020. | Includes bibliographical references.
Identifiers: ISBN 9781513550336 (paper)
Subjects: LCSH: Dollar, American. | Banks and banking, International. | COVID-19 (Disease).
Classification: LCC HG540.B37 2020
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www.elibrary.imf.orgSTRAINS IN OFFSHORE US DOLLAR FUNDING DURING THE COVID-19
CRISIS: SOME OBSERVATIONS
This note analyzes recent trends in offshore US dollar more volatile in nature. Analysis in the October 2019
funding markets and explores the drivers of dollar funding GFSR has shown that tightness in offshore US dollar
costs during the COVID-19 pandemic crisis. Preliminary funding conditions therefore can translate into finan-
evidence suggests that only part of the sharp increase in cial stress in the home economies of the global non-US
observed dollar funding costs can be attributed to the banks, and can be transmitted to other economies via
standard supply- and demand-side factors analyzed in cutbacks in cross-border lending. This was the case
the October 2019 Global Financial Stability Report during the 2008–09 global financial crisis.
(GFSR), including the dollar funding fragility of non-US Strains in US dollar funding re-emerged toward
global banks. Changes in market structure since the global the end of the first quarter of 2020, particularly after
financial crisis, as well as heightened uncertainty and the World Health Organization (WHO) declared the
tensions in the commercial paper market, may provide COVID-19 outbreak a pandemic on March 11. This
further explanations for the movements in dollar funding note takes stock of this episode, focusing on global
costs in late March 2020. The US Federal Reserve’s swap non-US banks and developments in US dollar funding
line arrangements have helped lessen strains in dollar conditions. It first presents recent developments in
funding markets, but funding pressure remains significant offshore US dollar funding costs in March, as reflected
for some emerging market economies, notably those with- in a widely used measure: the cross-currency basis. It
out access to the swap lines. Furthermore, tighter dollar then discusses the role of traditional as well as new
funding conditions appear to have accompanied increases drivers in the surge in the US dollar funding costs
in financial stress in the home economies of affected in March, the possible role of the Federal Reserve’s
non-US global banks and to have generated adverse spill- announcements of swap lines with major central
over effects in the form of cutbacks in cross-border lending. banks, and whether there are signs of financial stress in
home economies of global non-US banks or in their
As a result of US dollar dominance in international cross-border lending.
trade and financial transactions, disruptions in US
dollar funding outside the United States have been
found to have implications for global financial stability. The Cross-Currency Basis
The US dollar is the most common invoice currency in The cross-currency basis is a measure of tightness
world trade, a substantial portion of foreign exchange of US dollar funding conditions. It is defined as the
transactions worldwide involve US dollars (Gopinath difference between the direct cost of funding in US
2015; Gopinath and Stein 2018; Bräuning and Ivash- dollar wholesale markets and the cost of synthetic US
ina 2019; Bank for International Settlements 2019), dollar funding—that is, funding in another currency
and financial flows are similarly dominated by the US and using foreign exchange derivatives to convert to
dollar, with nonfinancial firms worldwide expressing a US dollars. Demand for synthetic funding arises from
preference for financing in this currency. Furthermore, global non-US banks filling the gap between their US
global non-US banks play a key role in US dollar lend- dollar assets and direct funding in US dollars, and
ing around the world, and given that their access to from institutional investors outside the United States
stable US dollar deposits outside the United States is who hold a significant portion of their assets in US
limited, they tend to resort to international wholesale dollars. Supply is provided by banks and, increasingly,
markets, a source that is generally shorter-term and by other financial intermediaries, such as prime money
market funds. When direct US dollar funding con-
Prepared by Adolfo Barajas, Andrea Deghi, Salih Fendoglu, ditions tighten, demand for synthetic dollar funding
and Yizhi Xu. The authors thank Tobias Adrian, Fabio Natalucci, increases, widening the cross-currency basis; that
Mahvash Qureshi, Jerome Vandenbussche, Patrick McGuire, Stefan
Avdjiev, and Swapan-Kumar Pradhan for their valuable comments.
is, making it more negative. The same occurs when
International Monetary Fund | July 2020 1MCM ANALYTICAL NOTE #1
Figure 1. Trends in the Cross-Currency Basis (CCB)
1. Recent Developments 2. CCB Comparison with GFC Peak
(Basis points) (Basis points)
80 100
25th to 75th percentile
40 Median
0
0
–40 –100
–80
–200
–120 11–18 March 2020
Peak Oct. 2008–March 2009
–160 –300
31 Dec. 31 Jan. 29 Feb. 31 Mar. 30 Apr. JPY CAD MXN HKD EUR GBP
Sources: Bank for International Settlements; Bloomberg Finance L.P.; and IMF staff calculations.
Note: Cutoff date in panel 1 is April 30, 2020. In panel 2, the average cross-currency basis (CCB) during the peak of the global financial crisis (GFC)
(2018:Q4–2019:Q1) is compared with the average in the period March 11–18, 2020 (when the WHO declared that the outbreak was a pandemic). In panel
1, the sample comprises the Australian dollar, Brazilian real, British pound, Canadian dollar, Chinese renminbi, Danish krone, euro, Hong Kong dollar,
Indian rupee, Japanese yen, Malaysian ringgit, Mexican peso, New Zealand dollar, Norwegian krone, Philippine peso, Russian ruble, Singapore dollar, South
African rand, South Korean won, Swedish krona, Swiss franc, Thai baht, and Turkish lira. In panel 2, horizontal lines correspond to the sample median of
CCB during the peak of the GFC (dotted line) and in the period March 11–18, 2020 (dashed line). Figure uses International Organization for Standardiza-
tion (ISO) country codes. CAD = Canadian dollar; EUR = euro; GBP = British pound; HKD = Hong Kong SAR dollar; JPY = Japanese yen; MXN =
Mexican peso.
the supply of synthetic US dollar funding declines. below what was observed during the peak of the global
Conversely, when US dollar funding conditions are financial crisis, for some currencies—including the
relatively loose, the basis exhibits small, or even pos- Canadian dollar, Hong Kong SAR dollar, and Mexican
itive, values. peso—the widening has been larger than during the
global financial crisis (Figure 1, panel 2).2
In general, the sharp widening of the cross-currency
Developments as the Pandemic Evolved basis coincided with the declaration of COVID-19 as
Signs of stress in offshore US dollar funding markets a global pandemic. The cross-currency basis started to
erupted in mid-March as the COVID-19 pandemic widen across economies as the number of confirmed
spread across the world. The cross-currency basis COVID-19 cases began to rise (Figure 2), and more
widened significantly for major advanced and emerging sharply immediately after the WHO declared the
market economies in mid-March, with the median outbreak a global pandemic on March 11, 2020. The
widening by about 55 basis points compared with cross-currency basis widened by about 40 basis points
early January (Figure 1, panel 1). The cross-currency and 70 basis points in advanced and emerging market
basis has narrowed more recently and has moved into economies, respectively, in the week following the
positive territory for several currencies, such as the announcement.
euro, Japanese yen, British pound sterling, and Swiss Despite these general trends, it is worth noting
franc, though it remains negative and wider than last that movements in the cross-currency basis have not
year for some emerging market currencies, such as the been uniform across economies. For example, among
Malaysian ringgit and the Philippine peso.1 Although advanced economies, the Japanese yen widened by
the median basis at its mid-March peak was still well about 80 basis points in the week following the WHO
announcement, compared with 43 basis points for the
1The currencies that have experienced the largest change from a
negative basis in mid-March to a positive basis in early April include 2The three-month Mexican peso basis was positive early on during
the Japanese yen, the Mexican peso, the Swiss franc, the Danish the global financial crisis and turned negative only in the second half
krone, and the euro. The cut-off date for the analysis in this note is of 2009; it remained mostly negative thereafter. See Bush (2019) for
April 30, 2020. more details.
2 International Monetary Fund | July 2020Strains in Offshore US Dollar Funding during the COVID-19 Crisis: Some Observations
Figure 2. Cross-Currency Basis and Cumulative Confirmed COVID-19 Cases
1. Advanced Economies 2. Emerging Market Economies
(Left scale = basis points; right scale = percent) (Left scale = basis points; right scale = percent)
60 0.28 50 0.016
COVID-19 declared COVID-19 declared
pandemic by WHO pandemic by WHO
20 0.21 –10 0.012
–20 0.14 –70 0.008
3-month CCB
Cumulative COVID-19
–60 3-month CCB 0.07 –130 0.004
cases (pct of population)
Cumulative COVID-19
cases (pct of population)
–100 0 –190 0
31 Dec. 31 Jan. 29 Feb. 31 Mar. 30 Apr. 31 Dec. 31 Jan. 29 Feb. 31 Mar. 30 Apr.
Sources: Bloomberg Finance L.P.; European Centre for Disease Prevention and Control; and IMF staff calculations.
Note: Panels 1 and 2 show three-month cross-currency basis (CCB) based on LIBOR rates (red lines, left axis) against the cumulative number of COVID-19
cases expressed as a percentage of the population (blue line, right axis). LIBOR = London interbank offered rate; WHO = World Health Organization.
Canadian dollar. Likewise, in the emerging market effect, by dampening the demand for risky investments
group, the Malaysian ringgit and Philippine peso basis denominated in dollars.3
widened by about 90 basis points, but the Mexican Country-specific funding vulnerability—proxied
peso by only 30 basis points. by the gap between US dollar assets and liabilities—
also seems to have played a role in influencing the
cross-currency basis. As shown in the October 2019
Drivers of the Cross-Currency Basis GFSR, the gap between US dollar assets and liabili-
Previous research, including in the October ties, known as the cross-currency funding gap, is an
2019 GFSR, has identified a set of factors that important driver of the potential need for non-US
generally drive the variation in the movement of banks to resort to synthetic dollar funding. The aggre-
the cross-currency basis across economies. Most of gate cross-currency funding gap and the gap scaled by
these factors moved in the direction of widening US dollar assets, known as the cross-currency funding
the cross-currency basis in March 2020. For exam- ratio, have increased for many countries. However,
ple, increases in the term spread differential (as the there is considerable variation across economies
Federal Reserve drastically reduced the target interest (Figure 4, panels 1 and 2). Notably, economies with a
rate in response to the COVID-19 crisis), the broad higher cross-currency funding ratio before the onset of
US dollar index, and the bid-ask spread have exerted the current pandemic (such as Japan) have experienced
upward pressure on US dollar funding costs (Figure 3, a significantly wider cross-currency basis (Figure 4,
panels 1 and 2). The London interbank offered rate– panel 3).4
overnight index swap (LIBOR-OIS) spread, which
reflects the freezing up of short-term funding markets 3As shown in the October 2019 GFSR, an increase in the VIX is
in the United States, also has a widening effect on likely to reduce demand for risky investments denominated in US
dollars, thereby alleviating pressure on the cross-currency basis. This
the cross-currency basis, as does the rising implied is because the estimated model controls for domestic risk in home
volatility of domestic currencies of the home econo- economies through a measure of implied foreign exchange volatility
mies. By contrast, the rapid increase in the Chicago so that the VIX captures the riskiness of dollar-denominated assets.
4The October 2019 GFSR shows that the cross-currency funding
Board Options Exchange Volatility Index (VIX), from ratio amplifies the effect of other drivers on the cross-currency basis.
around 10 in early January to above 80 in late March Thus, for the same increase in a given driver, a country with a larger
(Figure 3, panel 3), is expected to have a narrowing cross-currency funding ratio tends to experience larger widening
of the cross-currency basis. However, due to data limitations, the
CCFR can be computed only up to third quarter of 2019 for some
currencies, the first quarter of 2018 for others.
International Monetary Fund | July 2020 3MCM ANALYTICAL NOTE #1
Figure 3. Drivers of US Dollar Funding Costs
1. LIBOR-OIS and Term Spread Differential 2. Bid-Ask Spread and FX Volatility 3. USD Index, VIX, and Infectious Disease EMV
(Left scale = percent; right scale = percent) (Basis points) (Index)
2 0.4 18 100 130
Term spread differential (lhs) Bid-ask spread VIX (lhs)
LIBOR-OIS spread (rhs) FX volatility ID EMV (lhs)
USD index (rhs)
1 0.3 75 125
12
0 0.2 50 120
6
–1 0.1 25 115
–2 0 0 0 110
1 Jan. 31 Jan. 1 Mar. 31 Mar. 30 Apr. 1 Jan. 31 Jan. 1 Mar. 31 Mar. 30 Apr. 1 Jan. 31 Jan. 1 Mar. 31 Mar. 30 Apr.
Sources: Bank for International Settlements; Bloomberg Finance L.P.; and IMF staff calculations.
Note: In panels 1 and 2, sample medians are displayed for all series. In panel 3, the Infectious Disease Equity Market Volatility (ID-EMV) is a market
volatility indicator constructed through the newspaper-based tracker, and augmented with tracking of infectious disease-related words (Baker and others
2020). The sample comprises the Australian dollar, Brazilian real, British pound, Canadian dollar, Chinese renminbi, Danish krone, euro, Hong Kong SAR
dollar, Indian rupee, Japanese yen, Malaysian ringgit, Mexican peso, New Zealand dollar, Norwegian krone, Philippine peso, Russian ruble, Singapore dollar,
South African rand, South Korean won, Swedish krona, Swiss franc, Thai baht, and Turkish lira. FX = foreign exchange; ID-EMV = Infectious Disease Equity
Market Volatility; lhs = left-hand scale; LIBOR-OIS = London interbank offered rate–overnight index swap; rhs = right-hand scale; USD = US dollar; VIX =
Chicago Board Options Exchange Volatility Index.
Figure 4. Non-US Banks’ US Dollar Cross-Currency Funding Gap
1. Aggregate Cross-Currency Funding 2. Cross-Currency Funding in Selected Economies 3. CCB Change and CCFR
(Left scale = percent; (Left scale = percent; (x-axis: percent; y-axis: basis points)
right scale = trillions of USD) right scale = billions of USD)
20 2 40 1200 240
CCFR CCFR (lhs)
CCFG (rhs) CCFG (rhs)
30 900 160
15 1.5
CCB change
20 600 80
10 1
10 300 0
5 0.5
0 0 –80
0 0 –10 –300 –160
2000 05 10 15 20 –80 –40 0 40
JPN
CAN
DEU
ITA
NLD
SWE
CHE
ESP
GBR
FRA
CCFR
Sources: Bank for International Settlements; Bloomberg Finance L.P.; and IMF staff calculations.
Note: Panel 1 shows the difference between USD assets and liabilities, the cross-currency funding gap (CCFG), and the cross-currency funding ratio (CCFR),
ratio of the CCFG to USD assets, for a balanced sample of 13 economies that are home to global non-US banks. The balanced sample includes Australia,
Austria, Canada, France, Germany, Italy, Japan, Netherlands, Norway, Spain, Sweden, Switzerland, and United Kingdom. Panel 2 shows the latest available
(2019:Q3) CCFG and CCFR for selected economies. Panel 3 shows a scatter plot of the change in the cross-currency basis (CCB) (calculated as the difference
between the average value in the period March 11–18, 2020, and the last week in December 2019) against the latest observation for the CCFR constructed
for an extended sample of currency areas. The CCFR for the euro area is computed as the simple average of euro area countries with available CCFR data. The
slope of the fitted line is statistically significant at the 10 percent level (p-value = 0.06). Non-US banks’ US dollar balance sheet aggregates are constructed
using cross-border positions plus those in non-domestic branches’ positions. Figure uses International Organization for Standardization (ISO) country codes.
lhs = left-hand scale; rhs = right-hand scale; USD = US dollars.
4 International Monetary Fund | July 2020Strains in Offshore US Dollar Funding during the COVID-19 Crisis: Some Observations
Figure 5. Actual and Predicted Cross-Currency Basis: Standard Model
1. Actual and Predicted CCB in March 2020 2. Residuals Comparison with Global Financial Crisis
(Basis points) (Basis points)
170
SEK Predicted Peak Oct. 2008–Mar. 2009
3-month CCB Mar. 2020
MYR 100
Apr. 2020
JPY
HKD 30
GBP
EUR –40
CHF
–110
CAD
AUD
–180
–150 –100 –50 0 50 100 150 200 AUD CAD CHF EUR GBP HKD JPY MYR SEK
Sources: Bank for International Settlements; Bloomberg Finance L.P.; and IMF staff calculations.
Note: Panel 1 compares the average of the actual three-month cross-currency basis in March 2020 with the predicted obtained from the standard model (that
is, the October 2019 Global Financial Stability Report model) estimated over the 2006M1–2020M4 period. Panel 2 compares the forecast error (“residuals”;
that is, actual cross-currency basis minus the predicted value) in March and April with the average in-sample prediction error during the peak months of the
global financial crisis. Figure uses International Organization for Standardization (ISO) country codes. AUD = Australian dollar; CAD = Canadian dollar;
CHF = Swiss franc; EUR = euro; GBP = British pound; HKD = Hong Kong dollar; JPY = Japanese yen; MYR = Malaysian ringgit; SEK = Swedish krona.
The standard drivers of the cross-currency basis, (Figure 3, panel 3).6 Furthermore, the COVID-19
however, explain only part of the variation. Compar- shock differs in nature from that of the global financial
ing the actual cross-currency-basis average value in crisis, which was a financial sector shock that propa-
March with predictions generated from a model that gated from US short-term funding markets to global
includes the standard drivers as explanatory vari- US dollar funding markets. In the current episode, the
ables, reveals that a portion of the widening remains shock pertains to the real sector, which is increasingly
unexplained. Predicted values point to a substantial causing liquidity shortages for companies fighting to
narrowing of the cross-currency basis in five of the stay afloat amid a shutdown in activity, while at the
nine analyzed currencies, whereas the cross-currency same time reducing demand for credit for international
basis has in fact widened in all but one (Figure 5, trade purposes or cross-border investment activities.
panel 1).5 In general, the March prediction error is In addition, there has been unprecedented fiscal and
in the ballpark of what was observed when the basis monetary policy support in the United States and
at its peak during the global financial crisis (Figure 5, across the world. As a result of the multiple factors
panel 2), although in some of the currencies (such as at play, the nature, scale, and speed of propagation
the Canadian dollar, the Hong Kong SAR dollar, the of this shock may not be fully captured by tradi-
Japanese yen, and the Malaysian ringgit), the error tional models.7
was noticeably larger in March.
The prediction errors in the recent period suggest
that there are other factors at play. These may include
a magnified impact of existing vulnerabilities as the 6The Infectious Disease Equity Market Volatility Index, developed
risk-off sentiment intensified, an overreaction in US by Baker, Bloom, and Davis (2020), combines three indicators:
dollar funding markets, or the unprecedented increase stock market volatility, newspaper-based economic uncertainty, and
in uncertainty caused by the pandemic as reflected in newspaper-based tracking of infectious disease–related words to
capture real-time forward-looking uncertainty related to the spread
an Infectious Disease Equity Market Volatility Index of infectious diseases.
7Additional specifications of the model were estimated that
included nonlinear terms for the VIX, as well as its interaction with
variables such as the cross-currency funding ratio. These augmenta-
5Predictions are generated for currencies for which data are avail- tions helped to improve the fit of the model and lower the forecast
able for all relevant variables in the baseline model. error for a majority of currencies.
International Monetary Fund | July 2020 5MCM ANALYTICAL NOTE #1
Structural Developments since the Global synthetic USD funding from foreign currency swap
Financial Crisis markets. Furthermore, tightening in the commercial
Certain developments in the market structure since paper market also led corporate borrowers to draw
the global financial crisis may have contributed to the down credit lines from global US banks, reducing their
recent tightening in US dollar funding markets. First, capacity to supply foreign currency hedging.
institutional investors, including insurers and pension The overall strain in the prime commercial paper
funds, hold globally diversified portfolios and engage market was accompanied by a squeeze toward shorter
into swap agreements to strategically hedge foreign cur- maturities, which would increase the rollover risk of
rency investments. In recent years, their portfolios have US dollar funding for both firms and banks. At the
surged along with their hedging needs. As reported in beginning of this year, yield spreads of commercial
the Bank for International Settlements Semi-annual paper instruments over the target federal funds rate at
Over-The-Counter Derivatives Statistics the total different maturities were in general very low and with
notional amounts outstanding for foreign exchange an almost flat term structure. As of March 16, 2020,
contracts at the end of June 2019 was $92 trillion, however, the three-month spreads for nonfinancial
with foreign currency swaps estimated to account for and financial commercial paper rose to more than 110
about 30 percent of outstanding notional amounts.8 basis points (Figure 6, panel 3). Responding to the
Anecdotal evidence suggests that institutional inves- market strains, the Federal Reserve introduced a new
tors may have contributed to about 65 percent of the commercial paper funding facility similar to that used
increase of the local hedging demand since the global during the global financial crisis. Despite the mini-
financial crisis (Goldman Sachs 2018). Nonfinancial mal initial use of the facility due to its pricing,10 the
firms seeking to borrow opportunistically in markets intervention seems to have helped to ease the pressures
where credit spreads are narrower could also prop up in the market.
the demand for synthetic dollar funding in order to
avoid currency mismatches (Borio and others 2016). Impact of Central Bank Swap Lines
This is particularly relevant in emerging market econ-
omies, where reliance of firms and quasi-sovereigns To alleviate the growing stress in US dollar funding
on dollar liquidity has also been rising rapidly in the markets, the Federal Reserve enhanced dollar liquidity
last decade.9 arrangements with foreign central banks. On March
The size of the nonfinancial commercial paper 15, 2020, the Federal Reserve announced a coordi-
market, where considerable stress has been observed in nated action with five central banks (Bank of Canada,
the current episode, has also increased almost threefold Bank of England, Bank of Japan, European Central
over the last decade. As the COVID-19 pandemic Bank, Swiss National Bank) to enhance the provi-
unfolded, there has been a dramatic shift of money sion of liquidity by lowering the pricing on standing
market investors away from prime money market US dollar liquidity swap arrangements by 25 basis
funds into government money market funds (Figure 6, points.11 Given the continued pressure in the markets,
panel 1). As prime money market funds are an import- however, the Federal Reserve announced additional
ant investor in commercial paper, the outflow contrib- swap lines on March 19, 2020, with nine other central
uted to a sharp increase in funding costs in commercial banks/monetary authorities (Australia, Brazil, Den-
paper markets (Figure 6, panel 2). This further tight- mark, Korea, Mexico, New Zealand, Norway, Singa-
ened the funding available for large corporations, nota- pore, Sweden).
bly foreign firms seeking direct USD funding. Stress in
this market likely put additional strains on obtaining
10The initial pricing to access the facility was three-month OIS
rate plus 200 basis points, whereas the three-month financial, non-
8Seehttps://stats.bis.org/statx/srs/table/d6?f=pdf. financial, and asset-backed commercial paper three-month rates were
9Chui, Curuk, and Turner (2016), for example, provide evidence well below OIS rate plus 200 basis points at the time of the policy
that foreign currency liabilities of emerging market firms is likely not announcement.
fully hedged by foreign currency revenue or foreign exchange deriv- 11To increase the swap lines’ effectiveness, the foreign central
atives. Bruno and Shin (2017, 2020) show evidence on emerging banks with standing US dollar liquidity operations also agreed to
market nonfinancial firms’ tendency to engage in USD carry trade begin offering US dollars weekly in each jurisdiction, with 84-day
and how such activity combined with their building of cash balances maturity, in addition to one-week-maturity operations already in
may make them more vulnerable to a stronger US dollar. place. The changes took effect during the week of March 16, 2020.
6 International Monetary Fund | July 2020Strains in Offshore US Dollar Funding during the COVID-19 Crisis: Some Observations
Figure 6. Trends in the Commercial Paper Markets during COVID-19
1. MMF Shift from Prime to Government 2. Spread of CPs Yields over OIS 3. Money Market Yield Curves on March 16
(Billions of US dollars) (Percent) (Percent at each maturity)
5,000 3 2.0
Govt MMFs ABCP ABCP Fin. CP
Prime MMFs Non-Fin. CP Non Fin. CP LIBOR
4,000
2 1.5
3,000
1 1.0
2,000
0 0.5
1,000
0 –1 0
Dec. 2018 Apr. 19 Aug. 19 Dec. 19 Apr. 20 1 Jan. 31 Jan. 1 Mar. 31 Mar. 30 Apr. 0 15 30 45 60 75 90
Sources: Crane Data’s Money Fund Intelligence; Thomson Reuters Datastream; and IMF staff calculations.
Note: Panel 1 shows (monthly) total asset in money market funds (MMF) by type of fund. Panel 2 shows the difference between the interest rates paid by
different types of US commercial paper (at three-month maturity) and the OIS-three month rate at daily frequency. The vertical line in panel 2 corresponds to
March 17, 2020, when the US Federal Reserve Board announced the establishment of a Commercial Paper Funding Facility (CPFF). Panel 3 shows the term
structure of commercial paper and LIBOR spreads, calculated as the money market rate less the federal funds target rate at each maturity (in days on the
x-axis). This term structure shown is as of March 16, 2020. ABCP = asset-backed commercial paper; Fin.CP = financial commercial paper; Non-Fin. CP =
non-financial commercial paper; OIS = overnight index swap.
The swap lines appear to have had a significant Home Country Financial Stress and
impact on US dollar funding conditions. Results from Spillover Effects
a regression equation that controls for the standard An increase in US dollar funding costs tends to be
drivers as well as two additional domestic variables, the associated with intensifying financial stress in the home
banking system expected default frequency (EDF) and economies of global non-US banks. The analysis in the
the ratio of international reserves to GDP, show that October 2019 GFSR showed that an increase in US
the announcements are associated with a significant dollar funding costs is generally associated with intensi-
narrowing of the cross-currency basis by about 80 basis fying financial stress in the home economies of global
points for swap line currencies, including those with an non-US banks, as reflected in measures of financial sec-
outstanding swap line and those who gained access to tor risk such as expected default frequency. The March
the new swap lines. On the other hand, the effect on 2020 episode follows this pattern, with the tightening
non-swap-line currencies is not statistically significant of US dollar funding conditions accompanied by an
(Figure 7, panel 1).12,13 increase of about 0.3 percentage point in the expected
default frequency in home economy banking systems
(Figure 8, panel 1). On average, the increase has been
12These results are consistent with those obtained by Cetorelli,
Goldberg, and Ravazzolo (2020), who undertook event studies on
larger for emerging market economies that are home to
the effects of policy announcements of the Federal Reserve swap line global non-US banks than for advanced home econo-
on the cross-currency basis within a two-day window. mies (0.4 versus 0.2 percentage point, respectively).
13It should be noted that around the time of the swap announce-
Expected default frequency has responded little to
ments, other policy actions were taken both by the Federal Reserve
and on the fiscal front, which may have helped to improve investor swap line arrangements. Although expected default fre-
risk sentiment and have had an impact on US dollar funding quency in advanced home economies appears to have
conditions. In particular, on March 31, the Federal Reserve also declined after March 15, 2020, the difference between
announced the establishment of a temporary repurchase agreement
facility for foreign central banks and other international monetary the average pre- and post-swap-line expected default
authorities (FIMA Repo Facility), which allows FIMA account frequency is statistically insignificant, which suggests
holders to enter into repurchase agreements with the Federal Reserve
to temporarily exchange their US Treasury securities held with the
Federal Reserve for US dollars. The facility became effective April account holders is not publicly available to do a meaningful analysis
6, 2020, but information on individual repurchases by the FIMA of its impact.
International Monetary Fund | July 2020 7MCM ANALYTICAL NOTE #1
Figure 7. Effect of New Swap Line Announcements
1. Effect of Swap Line on CCB 2. Currencies with Outstanding Swap Lines 3. Currencies with Recent Swap Lines
(Basis points) (Basis points) (Basis points)
120 90 90
CAD CHF SEK NOK
EUR JPY SGD MXN
GBP DKK
80 30 30
40 –30 –30
0 –90 –90
–40 –150 –150
Outstanding New Non 5 Mar. 13 Mar. 21 Mar. 29 Mar. 5 Mar. 13 Mar. 21 Mar. 29 Mar.
swap line swap line swap line
Sources: Bloomberg Finance L.P.; and IMF staff calculations.
Note: Panel 1 shows the estimated impact of the recent swap line announcements on the three-month cross-currency basis (CCB), controlling for foreign
exchange implied volatility, the bid-ask spread, the US dollar index, the Chicago Board Options Exchange Volatility Index, expected default frequency of the
home economy banking sector, LIBOR-OIS spread, and international-reserves-to-GDP ratio. Coefficients are estimated using a staggered difference-in-differ-
ence model over the period from February 1, 2020, to April 30, 2020. Two treatment groups are defined for the currencies with outstanding swap lines and
those with new swap lines agreement. Post periods dummies are defined accordingly. The dates of the announcements are (1) March 15, when the central banks
of Canada, euro area, Japan, Switzerland, the United Kingdom, and the United States enhanced the provision of liquidity via the standing US dollar liquidity
swap line arrangements; and (2) March 19, when the Federal Reserve announced the establishment of new temporary US dollar swap lines with nine additional
central banks. Swap line currencies correspond to the Australian dollar, Brazilian real, Canadian dollar, Danish krone, euro, British pound, Japanese yen,
Mexican peso, New Zealand dollar, Norwegian krone, Singapore dollar, South Korean won, Swedish krona, and Swiss franc. Non-swap-line currencies
correspond to the Chinese renminbi, Hong Kong SAR dollar, Indian rupee, Israeli shekel, Malaysian ringgit, Philippine peso, Russian ruble, South African rand,
and Thai baht. LIBOR-OIS spread series is replaced with the sample median for advanced or emerging market economies when missing. A solid bar denotes
significance at 10 percent or lower. Panels 2 and 3 show the three-month CCB for selected currencies in the period around the swap line announcements.
Vertical lines indicate the date of the swap line announcements. Figure uses International Organization for Standardization (ISO) country codes. CAD =
Canadian dollar; CHF = Swiss franc; DKK = Danish krone; EUR = euro; GBP = British pound; JPY = Japanese yen; MXN = Mexican peso; SEK = Swedish
krona; NOK = Norwegian krone; SGD = Singapore dollar.
that a host of other factors affecting banking systems The rise in financial stress across home and recipient
may be weighing in.14 economies is also manifested in a tightening of domes-
Tighter US dollar funding conditions are also tic financial conditions, which turns out to be posi-
associated with an uptick in financial stress in recipient tively correlated with widening of the cross-currency
economies. Banking system expected default frequency basis (Figure 8, panel 3).
in recipient economies has increased by about 0.4 per- The financial strains arising in recipient economies
centage point on average since the end of February may be at least partly attributed to the retrenchment
(Figure 8, panel 2). As with home economy financial in cross-border lending. Available syndicated-loan-level
stress, the impact on recipient economies has been data suggest that the US dollar share of this lending
greater for emerging markets, with an average increase declined in the first quarter of 2020 and that this
in expected default frequency of 0.8 percentage point. decline was more pronounced for home economies
experiencing sharper widening of the cross-currency
basis. Furthermore, emerging market economy borrow-
14The effects of the swap line announcement are difficult to sepa-
rate from those of Federal Reserve policies providing liquidity to the
ers were particularly affected by this decline in lending
market around that time, but this result holds if other factors, such (Figure 8, panel 4).15
as the bid-ask spread, the US dollar index, and the VIX, are included
in the model to capture the possible impact of other policies on
liquidity conditions and broader risk sentiment. Among others, 15Complementing syndicated loan data with fund portfolio
another concurrent factor driving banks’ expected default frequency flows data, the analysis shows that the sharp decline in bond and
is the degree of riskiness of their loan portfolios. Elevated credit risks equity flows to emerging markets during the first quarter of 2020
at the outset of the crisis may also partially mute the effect of swap is also associated with the widening of the cross-currency basis in
lines on home/recipient economy bank expected default frequency. lending economies.
8 International Monetary Fund | July 2020Strains in Offshore US Dollar Funding during the COVID-19 Crisis: Some Observations
Figure 8. Financial Stress in Home and Recipient Economies
1. Expected Default Frequency (EDF): Home Economies 2. Expected Default Frequency (EDF): Recipient Economies
(Percent) (Percent)
2.00 3.0
EMs WHO declares Federal Reserve EMs WHO declares Federal Reserve
AEs COVID-19 as a strengthens AEs COVID-19 as a strengthens 2.5
1.50 Home pandemic swap lines Recipient pandemic swap lines
economies (March 11) (March 15) economies (March 11) (March 15) 2.0
25th to 75th 25th to 75th
1.00 percentile percentile 1.5
1.0
0.50
0.5
0.00 0.0
31 Dec. 31 Jan. 29 Feb. 31 Mar. 30 Apr. 31 Dec. 31 Jan. 29 Feb. 31 Mar. 30 Apr.
3. Change in FCI vs. Change in CCB 4. USD Share of Syndicated Lending and USD Funding Conditions
(x-axis: basis points; y-axis: index) (x-axis: basis points; y-axis: percent)
1.5 80
EM firms 60
syndicated lending (percent)
AE firms
Change in USD share of
1
40
y = 0.1695x + 15.756
2 20
FCI change
0.5 R = 0.0511
0
0 –20
y = 0.1782x – 14.548 –40
–0.5 R 2 = 0.0919
–60
–1 –80
–200 –100 0 100 200 300 –110 –60 –10 40
CCB change CCB change
Sources: Bloomberg Finance L.P.; Dealogic; Haver Analytics; Moody’s Analytics CreditEdge; and IMF staff calculations.
Note: Panel 1 shows the average expected default frequency (EDF) of banking systems for a sample of 24 home economies based on the October 2019 Global
Financial Stability Report, Chapter 5. Panel 2 shows the average bank EDF for a total of 27 recipient economies. Panel 3 shows the relationship between the
change in the domestic financial conditions index (FCI) during 2020:Q1 and the change in the cross-currency basis (CCB) calculated as the difference
between the average value in the period March 11–18, 2020, and the last week in December 2019 covering all economies (both home and recipient) with
available data for a total of 19 observations. The slope of the fitted line is statistically signficant at the 10 percent level (p-value = 0.06) in panel 3. Panel 4
shows the change in the share of US dollar lending in total syndicated lending (between end-December 2019 and end-March 2020) against the change in the
average CCB between December 24–31, 2019, and March 11–19, 2020, controlling for the average US dollar lending share in 2019 for both advanced
economy (AE, red dots) and emerging market (EM, green dots) borrowers. Each dot represents a lending country. The sample includes Australia, Canada,
China, Denmark, euro area, Hong Kong SAR, India, Japan, Malaysia, Norway, Singapore, Korea, Sweden, Switzerland, and the United Kingdom. The slope
of both fitted lines is statistically significant at the 5 percent level. WHO = World Health Organization.
Conclusion sharp jump in the VIX has operated in the opposite
The COVID-19 crisis undoubtedly resulted in tighter direction, as suggested by the model presented in
US dollar funding conditions, on balance affecting the October 2019 GFSR.
financial systems throughout the world. The preliminary • Predictions based on standard cross-currency-basis
analysis presented here suggests the following: models tend to underestimate the actual widening
• The sharp increase in US dollar funding costs that took place. Although the prediction error is not
that materialized in mid-March—as evidenced too far out of line with what was observed during
by the widening cross-currency basis for many the global financial crisis, a number of factors may
major currencies—could be partly explained by the explain the visibly sharper widening during March:
standard drivers of the cross-currency basis. Sev- structural changes in dollar funding markets over
eral factors, such as an increase in the term spread the past 10 years and an unprecedented level of
differential, the broad US dollar index, the bid-ask pandemic-related uncertainty together with disrup-
spread, and the LIBOR-OIS spread, have exerted tions to the commercial paper market during the
upward pressure on US dollar funding costs. The recent episode.
International Monetary Fund | July 2020 9MCM ANALYTICAL NOTE #1
• Also relevant are the differences between the recent Baker, Scott R., Nicholas Bloom, Steven J. Davis, Kyle J.
COVID-19 shock and that of the global financial Kost, Marco C. Sammon, and Tasaneeya Viratyosin. 2020.
crisis—in particular the implications in terms of “The Unprecedented Stock Market Impact of COVID-19.”
solvency rather than liquidity for corporates—that NBER Working Paper 26945, National Bureau of Economic
Research, Cambridge, MA.
underscores the need for better understanding of the
Bank for International Settlements (BIS). 2019. Triennial Cen-
transmission channels and associated vulnerabilities
tral Bank Survey of Foreign Exchange and Over-the-Counter
beyond the commonly recognized demand and sup-
(OTC) Derivatives Markets in 2019. Basel. https://www.bis
ply drivers for synthetic US dollar funding. As more .org/statistics/rpfx19.htm
data become available, further research could revisit Borio, Claudio EV, Robert N. McCauley, Patrick McGuire,
the drivers of the cross-currency basis in light of the and Vladyslav Sushko. 2016. “Covered Interest Parity Lost:
recent experience. Understanding the Cross-Currency Basis.” BIS Quarterly
• The Federal Reserve’s swap line arrangements have Review (September): 45–64.
helped lessen strains in US dollar funding markets, Bräuning, Falk, and Victoria Ivashina. 2019. “U.S. Monetary
leading to a narrowing of the cross-currency basis. Policy and Emerging Market Credit Cycles.” Journal of Mone-
On average, the cross-currency basis reverted to zero tary Economics 112 (June): 57–76.
in April, though for some emerging market econ- Bruno, Valentina, and Hyun Song Shin. 2017. “Global Dollar
Credit and Carry Trades: A Firm-Level Analysis.” The Review
omies, the cross-currency basis is still wider than
of Financial Studies 30 (3): 703–49.
historical norms.
Bruno, Valentina, and Hyun Song Shin. 2020. “Currency
• Tighter US dollar funding conditions have coin-
Depreciation and Emerging Market Corporate Distress.”
cided with some financial stress in the home econo- Management Science 66 (5): 1783–2290.
mies of affected non-US global banks, as indicated Bush, Georgia. 2019. “Bank Foreign Currency Funding Gap and
by the uptick in banking sector expected default fre- Currency Markets: The Case of Mexico Post GFC.” Banco de
quency during the first quarter of 2020. Of course, México Working Paper, Mexico City.
US dollar liquidity is only one factor weighing on Cetorelli, Nicola, Linda S. Goldberg, and Fabiola Ravazzolo.
these banking systems, but that could undermine 2020. “Have the Fed Swap Lines Reduced Dollar Fund-
their resilience if the situation worsens. ing Strains during the COVID-19 Outbreak?” Liberty
• Tight dollar liquidity conditions, moreover, have Street Economics. Federal Reserve Bank of New York, New
also been associated with negative spillovers to York, May 22.
Chui, Michael KF, Emese Kuruc, and Philip Turner. 2016. “A
economies that borrow in US dollars—with
New Dimension to Currency Mismatches in the Emerging
available information suggesting that home econ-
Markets Non-Financial Companies.” BIS Working Papers
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550, Bank for International Settlements, Basel.
costs have tended to shift away from US dollar Goldman Sachs. 2018. “A New Barrier to Capital Flows:
cross-border lending, especially to emerging market USD-Funding Premium.” Asia Economic Analyst, Seoul.
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