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CIP deviations, the dollar, and frictions in international capital markets

This is a survey chapter, written for Volume V of the Handbook of International Economics, rather than a paper presenting new results; its claims are drawn from the literature it reviews and its own descriptive statistics. (The full text used here is the freely available NBER working-paper version of May 2021.) The organising fact is the dollar’s outsized role in global finance: the United States is about 15 percent of world trade and 25 percent of global GDP, but the dollar accounts for roughly 50 percent of cross-border loans and international debt securities, 90 percent of FX transactions, 60 percent of official reserve holdings and 50 percent of trade invoicing. Because “the global market for dollar funding is highly fragmented” and many participants who need dollars cannot reach dollar-rich lenders directly, large global banks have to intermediate – and since the Global Financial Crisis their balance sheet constraints have tightened, partly through regulatory reform. The most visible symptom is the failure of covered interest rate parity, measured by the cross-currency basis: the difference between the cash-market dollar rate and the synthetic dollar rate implied by borrowing in foreign currency and swapping into dollars. The chapter documents a sharp pre- and post-crisis dichotomy – CIP “held remarkably well prior to the GFC,” with only fleeting deviations of 30 seconds to 40 minutes – and shows the post-crisis deviations survive replacing Libor with OIS or with government-collateralised repo rates, so they are not simply a credit spread. Three stylised facts follow. The basis is generally negative, with the Australian and New Zealand dollars the G10 exceptions; it correlates 90 percent in the cross-section with the level of nominal interest rates since 2008, which means the hedged CIP arbitrage runs opposite to the unhedged carry trade; and it has a strong factor structure, with the first principal component of quarterly changes in the five-year G10 bases explaining 51 percent of variation over 2008Q1-2020Q3 and correlating 96 percent with the average basis, so the basis widens in bad times alongside a strong broad dollar, high VIX, wide BBB-Treasury spreads and negative intermediary capital shocks. The explanatory framework is a supply-and-demand diagram for swapped dollars. Pre-crisis supply was perfectly elastic at a zero basis; post-crisis the leverage ratio requirement, which “mandate[s] banks to maintain capital against all assets, regardless of their risk characteristics,” makes even a riskless matched-book trade costly, tilting the supply curve upward so that demand shifts now move the equilibrium basis. On the demand side the chapter identifies three client types willing to pay the basis as an intermediation fee: non-top-tier non-US banks with local-currency insured deposits but dollar assets, non-US institutional investors with local-currency liabilities and dollar portfolios, and multi-currency corporate issuers exploiting currency-segmented bond markets. Central bank swap lines are the crisis backstop, priced at a fixed spread over OIS that fell from 100 basis points in the Global Financial Crisis to 50 in November 2011 and 25 in March 2020, with peak outstanding of about $580 billion in 2008-09, $110 billion in the European debt crisis and $450 billion during COVID. The chapter then separates government bond CIP deviations, which need not be arbitrage at all, since they can reflect sovereign default risk, capital controls and market segmentation, or cross-country differences in convenience yields. A final section surveys two views of what CIP deviations mean for exchange rates – one treating them as a signal of intermediaries’ risk-bearing capacity, the other as a determinant working through bond convenience yields – and the chapter closes with open questions about whether post-crisis regulation is calibrated correctly, about the growing role of non-banks, and about the macroeconomic consequences.

Deviations from Covered Interest Rate Parity

Covered interest rate parity is the no-arbitrage relation that pins the forward exchange rate to the spot rate and the interest differential; the paper’s own description is that it is “presented in all economics and finance textbooks and taught in every class in international finance.” This paper documents that it is systematically and persistently violated among G10 currencies after the 2008 crisis, establishes that the violations are genuine arbitrage rather than compensation for credit risk or transaction costs, and traces them to the cost of using a bank balance sheet. (The magnitudes cited here come from the February 2017 NBER working-paper version, the freely available full text this summary rests on; the published version appeared in the Journal of Finance in 2018.) The scale of the market matters for how surprising this is: $61 trillion notional outstanding and $3 trillion average daily turnover. Over 2010-2016 the average annualised absolute Libor cross-currency basis is 24 basis points at three months and 27 basis points at five years, but those averages conceal a lot – the five-year yen basis was close to -90 basis points at the end of 2015, larger in magnitude than the roughly -70 basis point five-year Libor differential between Japan and the United States. Two moves rule out the standard explanations. The credit-risk story, that interbank panels differ in creditworthiness, is tested directly on panel banks’ CDS spreads and finds little support; more decisively, the authors recompute the basis on instruments with no credit-risk difference at all – general collateral repos, which are fully collateralised, and Kreditanstalt für Wiederaufbau bonds, fully backed by the German government – and the basis survives. The repo basis is persistently and significantly negative for the yen, Swiss franc and Danish krone, ranging from -16 basis points for the euro to -36 for the Danish krone, and the KfW basis is significantly non-zero for the euro, Swiss franc and yen (about -14, -24 and -30 basis points) while being effectively zero for the Australian dollar. Net of measured transaction costs, the resulting arbitrage profits run from 9 to 20 basis points annualised, with standard deviations of 5 to 23 basis points – small numbers, but with zero conditional volatility over the fixed investment horizon, so the Sharpe ratios are infinite. On explanation, the paper advances a two-factor hypothesis: costly post-crisis financial intermediation, which explains why the deviations are not arbitraged away, plus persistent international imbalances in funding supply and investment demand across currencies, which explains why the basis lines up with the level of nominal rates. Four empirical characteristics follow. First, the deviations spike at quarter ends, and the timing is sharp in a way that identifies the mechanism: the one-month deviation jumps exactly one month before quarter end, the one-week deviation exactly one week before, while a three-month contract – which appears on a quarter-end report whenever it is executed – shows no such pattern. Second, using the Fed’s interest on excess reserves in place of Libor/OIS/repo as the direct dollar funding cost, as a proxy for the shadow cost of leverage, explains about one-third of the one-week deviations; also investing at foreign central banks’ deposit facilities shrinks the average basis from -26 (Libor) and -28 (OIS) basis points to -8, which the conclusion describes as accounting for two-thirds of the deviations – while still leaving -12 to -15 basis points for the krone, franc and yen. Third, the basis is positively correlated with the level of nominal interest rates, with a 89 percent correlation between five-year Libor bases and five-year Libor rates across G10 currencies, so the hedged arbitrage trade is long low-rate and short high-rate currencies – exactly the reverse of the unhedged carry trade. Fourth, the basis co-moves with other near-risk-free fixed-income spreads, notably the KfW-over-bund basis and the US Libor tenor basis. The authors are careful about what they have and have not shown: they present “the first international evidence on the causal impact of recent banking regulation on asset prices,” but state that assessing the welfare cost “is behind the scope of this paper; it would necessitate a general equilibrium model.”

Local Currency Sovereign Risk

Sovereigns that borrow in their own currency can always print the money to pay, so a common modeling assumption is that such debt is free of default risk; this paper builds a measure to test that and finds it false. The authors define the local currency credit spread as the yield on a local-currency (LC) government bond minus a synthetic LC risk-free rate assembled from the U.S. Treasury yield plus the long-dated forward premium implied by cross-currency swaps – equivalently, the promised dollar spread a global investor locks in by holding the LC bond with a matched swap, and equivalently the size of the failure of long-term covered interest parity between emerging-market and U.S. government bond yields. Using a new hand-built dataset of daily zero-coupon LC and foreign-currency (FC) yield curves and swap curves for 10 emerging markets from January 2005 to December 2011, at a 5-year benchmark tenor, they find the mean spread of LC nominal yields over U.S. Treasuries is 5 percentage points, of which their decomposition attributes 3.72 points to currency risk and 1.28 points to credit risk. The LC credit spread averages 128 basis points, is positive and statistically significant for every one of the ten countries, and stays significantly positive even after deducting half the bid-ask spread on the swaps to allow for transaction costs (that half-spread averages 19 basis points). It is nonetheless generally lower than the same sovereign’s FC credit spread, which averages 195 basis points – a gap of 67 basis points, widening to 86 basis points once swap transaction costs are netted out – and significantly negative in every country except Brazil, where a financial-transactions tax on foreign fixed-income investment drove the two apart. The two spreads also differ in structure: the first principal component explains only about 53 percent of LC credit spread variation across countries versus over 81 percent for FC spreads, and FC spreads are far more tightly tied to global risk factors (a 93 percent correlation between the first principal component of FC spreads and the VIX, against 76 percent for LC spreads). The ex-ante pattern is mirrored ex post: once currency risk is swapped away, LC bond excess returns carry no significant loading on global equity returns while FC excess returns do, so hedged LC debt is safer than FC debt on this measure despite the reputation of emerging-market local debt. Turning to why the spreads differ, the paper distinguishes differential cash-flow risk, differential liquidity, and differential pass-through of global risk aversion, and shows in panel regressions with country fixed effects that the VIX and bid-ask liquidity measures alone explain 46.7 percent of the within-country variation in the LC-minus-FC spread differential – the large majority of what is explained even after a full set of local and global macroeconomic fundamentals is added. The scope conditions matter: ten countries, a single seven-year window spanning the global financial crisis, a 5-year tenor, and a measure that is model-free about default but silent on which of taxes, convertibility restrictions, selective default, or risk premia drives the level of the spread in any individual country.

Quantitative Tightening Around the Globe: What Have We Learned?

Drawing on the recent experience of seven advanced-economy central banks (Australia, Canada, the euro area, New Zealand, Sweden, the UK and the US), this paper offers the first cross-country assessment of quantitative tightening (QT) — the unwinding of bond holdings accumulated under quantitative easing. In an event study that pools QT announcements across countries and over time while controlling for policy-rate surprises and economic data surprises, the authors estimate that a QT announcement corresponds to a small but significant increase of about 4–8 basis points in government bond yields at horizons of one year and longer, with an effect of about zero at three months; aggregating announcements by country over 2021–2023 gives cumulative increases in yields averaging roughly 20–26 bps, with substantial heterogeneity across countries — from no impact up to about 69 bps for the UK. These effects are larger for “Main Announcements” carrying concrete program details, for active bond sales than for passive run-off, and when the program involves government bonds; estimated effects on equity indices, exchange rates, financial conditions indices and inflation compensation point in the direction of tighter financial conditions but are usually statistically insignificant, the noteworthy exceptions being a significant decline in corporate bond indices and in the government bond “convenience yield.” Implementing QT shows no significant pricing effect for government bonds on the narrow implementation dates — including no difference between securities actively sold and comparable securities not sold on the same date — but over time is consistent with a significant reduction in banking-system liquidity balances, a modest rise in overnight funding spreads, and a decline in the convenience yield, while the authors find no evidence that QT has directly worsened government bond market liquidity or weakened auction demand. As central banks stepped back, domestic nonbank investors absorbed an important share of the shift — in the US, the “households” category (which includes hedge funds) has been a particularly important replacement for the Fed’s unwind. The authors explicitly caution against a causal interpretation and stress that almost all these episodes occurred during the unusual post-pandemic recovery alongside aggressive rate hikes, rest on limited observations, and may understate the true impact; on their reading QT has had more of an impact than watching “paint dry,” but far less than simply reversing the effects of QE programs launched during periods of market stress.

The Dollar, Bank Leverage, and Deviations from Covered Interest Parity

The full text used here is BIS Working Paper No. 592 (revised July 2017), the freely available version of the paper published in American Economic Review: Insights in 2019. The question it takes up is why apparently risk-free arbitrage opportunities persist in the largest currency market in the world, and its answer begins with an observation about what the textbook argument leaves out: “in textbooks, there are no banks. In practice, though, such arbitrage typically entails borrowing and lending through banks, and the competitive assumption is violated due to balance sheet constraints that place limits on the size of the exposures that can be taken on by banks. Even for non-banks, their ability to exploit arbitrage opportunities rely on banks to provide leverage. Hence, if deviations from CIP persist, it must be because banks do not or cannot exploit such opportunities.” From there the paper documents a “triangular relationship” joining the strength of the dollar, the cross-currency basis and cross-border dollar bank lending, and argues that all three are readings of one thing: the shadow price of bank leverage, for which the dollar spot rate serves as a barometer. The evidence has four parts. First, time-series regressions on the ten most liquid currencies against the dollar (Australian, Canadian and New Zealand dollars, Swiss franc, Danish and Norwegian krone, euro, pound, yen, Swedish krona) over 1 January 2007 to 2 February 2016: a one percentage point appreciation of the broad dollar index is associated with a 2.6 basis point fall in the three-month basis without controls and 2.1 with them, against a 7 basis point standard deviation of daily basis changes; at quarterly frequency the five-year basis coefficient runs -1 to -1.4, so a one standard deviation move in the index (3 percent) implies a 3-4 basis point reduction, and the dollar alone explains 19 percent of the time-series variation. Results are similar and more significant in a post-January-2009 subsample, so they are not a crisis artefact. Second, an asset-pricing result in the cross-section: currency-specific dollar betas correlate with the mean basis at 85 percent for the three-month and 97 percent for the five-year horizon, with a unit increase in beta magnitude corresponding to 11 and 26 basis points of expected CIP-trade return respectively – and with a striking reversal of roles, since “the classical ‘safe haven’ currencies, such as the Japanese yen and the Swiss franc, have the highest exposure to the dollar factor, and high-yielding ‘carry’ currencies, such as the Australian dollar and the New Zealand dollar, have the lowest.” An out-of-sample event study of the 3.9 percent dollar appreciation between 8 and 29 November 2016 confirms it: the basis widened for all G10 currencies, most for the yen (from -70.3 to -90.5 basis points), and the post-election dollar beta correlates with the basis at 98 percent. Third, panel regressions with borrowing-country fixed effects show quarterly growth in dollar-denominated cross-border lending falling with both the broad dollar index and the bilateral rate, jointly and separately, for all sectors and for bank and non-bank borrowers alike – evidence, the authors argue, that the index “has explanatory power over and above the bilateral dollar exchange rate.” Fourth, 51 internationally active G10 banks: a 1 percent broad dollar appreciation goes with a 2 percent decline in bank equity, falling to 0.27 percent once market returns are controlled for, and the interaction with the five-year basis is significantly positive, so banks in currency areas with a more negative basis suffer more. The mechanism offered is the risk-taking channel of Bruno and Shin, in which a weaker dollar flatters dollar borrowers’ balance sheets, reducing tail risk in creditors’ portfolios and freeing capacity under a value-at-risk constraint; this is what the authors call the financial channel of exchange rates, and they emphasise that it “may operate in the opposite direction to the net exports channel.” The triangle is shown to hold for the euro in the post-crisis sample but not for other major currencies, which the authors read as pointing “to the unique role of international funding currencies.”