Andrea Buraschi Booth School of Business and Imperial College London

with

E. Sener and M. Menguturk Imperial College London

The Geography of Risk Capital and Limits to Arbitrage

Law of One Price (LoP)

• Two assets generating equal cash-flows must have equal values. • Otherwise, there exists an LOP violation, such as arbitrage.

• If there is an LOP violation in the market, it should be short-lived.

• In a frictionless economy, prices must converge as arbitrageurs provide liquidity necessary to convergence and ensure LOP.

• If arbitrageur face frictions, than he may no longer be able to provide liquidity.

• We try to identify the nature of these frictions.

It is good for a scientific enterprise, as well as for a society, to have well established laws. Physics has excellent laws, such as the law of gravity. What does economics have? The first law of economics is clearly the law of supply and demand, and a fine law it is. We would nominate as the second law “the law of one price”. Lamont and Thaler (2003)

Ecosystem of Arbitrage

HF Prime Broker

Investment Bank Secured / Collateral

Borrowed Security

Short / Long

Hedge Fund Capital Structure

Investment Bank Capital Structure

Unsecured Loan (CP) Equity (Insured deposits)

Limited Partners

Assets

FED Provider of Liquidity?

Proprietary Trading Desk

Short / Long

What Are Potential Frictions and .. .. did policy interventions help?

Frictions 3: Leverage Constraints

Secured Funding (collateral)

Frictions 3: Leverage Constraints Unsecured Funding

Frictions 2: Short-Selling

Frictions 1: Liquidity

Using Cross-sectional International Data • We use: We use a simple arbitrage relationship (Covered Interest Parity) that relates two Eurobonds issued by the same issuer in two different (foreign) currencies. We build a panel dataset for the Basis(bond) of bond pairs to study the dynamics of the Basis during the Crisis and differences across different markets. • We find:

• LOP relationship is violated in 2007-2008 Crisis: large and long-lived. • Significant cross-sectional differences in Basis(bond) • Significant time-variation and state-dependence

• We ask:

• What are the main sources of frictions for these deviations? - Liquidity / Short-selling constraints / Leverage Constraints / Risk aversion? • What are the geographical differences in these deviations? • What are the policy implications (in any)?

• We conclude: • We do not find evidence supporting (a) Liquidity; (b) Short-selling constraints • We find support for other type of institutional frictions.

Explanations of Limits to Arbitrage Four main channels in Limits to Arbitrage Literature

1. Liquidity Frictions: Arbitrageur concerned about future market impact of its positions in an illiquid market. Amihud and Mendelson (1986), Fletcher and Taylor (1996); Duffie, Garleanu, and Pedersen (2007), Brunnermeier and Pedersen (2009); Fontaine and Garcia (2009); Coffey, Hrung, and Sarkar (2009); Fong, Valente, and Fung (2010) 2. Short-selling Constraints: A necessary condition for LOP is the possibility to short-sell an asset. Harrison and Kreps (1987), Diamond and Verrecchia (1987), Scheinkman and Xiong (2003), Tuckman and Vila (1992); Ofek, Richardson, and Whitelaw (2004); Gromb and Vayanos (2010); 3. Leverage Constraints and Funding Costs: Failure of capital structure of arbitrageur: given a balance sheet shock caused by an initial dislocation that induce initial failure of the LOP, if arbitrageur can borrow, than he can absorb the initial loss. Otherwise, he may be forced (margin requirements) to liquidate, inducing an amplification of the LOP deviation. Shleifer and Vishny (1997); Gromb and Vayanos (2002); Liu and Longstaff (2004); Garleanu and Pedersen (2011); Liu and Mello (2011); Mitchell and Pulvino (2012); Gabaix, Krishnamurthy, and Vigneron (2007); Griffoli and Ranaldo (2011). 4. Macro demand/wealth shocks: Wealth shocks can interact with other frictions to amplify initial LOP deviations. See Shleifer and Vishny (1997), and Gromb and Vayanos (2010).

Simple Parity Condition

• Having the same recovery rates, the following must hold:

• Thus if CIRP holds:

FX-Covered Sovereign Basis

• If a single sovereign issues two discount bonds with maturity T in two different currencies (i.e. Usd and Eur):

𝐴 = 𝜋𝑟2

( )(1 ( , ) ( , )) (1 ( , ) ( , ))( , )

d d d e e eX tR t T S t T R t T S t TF t T

δ δ+ + = + +

0

( )0 ) ( , ) ( , )( , )

d e d e

By CIRP

X(t) X t1+ R (t,T)- (1+ R (t,T) S t T S t TF(t,T) F t T

=

= + −

( )0 ( , ) ( , )( , )

d eX tS t T S t TF t T

= −

Implementation via Asset Swap

• Two ways to implement the LOP: (a) on a zero coupon yield basis (this requires interpolation); (b) via asset swaps.

• EXAMPLE. Brazil issues two bonds maturing on March 7 2015, one denominated in USD and one in EUR.

• Take the 7.375% Eur bond and do an asset swap to convert into Usd cash flows using traded FX forward strips. This creates a synthetic Usd-denominated bond.

• If cash flows were identical, LOP applies. • We match the face value, the coupon stream do not match exactly. Thus, we

define:

• The difference in the two bond spreads is equal to the cost of hedging the FX risk.

• If there is a LOP violation in the market, what is the nature of the frictions?

( ) ( )usd EurBasis Yield B Yield B= −

Selection of Sample EM Eurobond Market

Looking for sovereign issuers of pairs of bonds in two foreign currencies (USD and Euro)

These EM Eurobonds provide seemingly unrelated assets to help identify some of the potential frictions

EM Eurobond Markets

(2005- 2010)

1. Large market (sovereign bonds) 2. Liquid (small search / transaction costs) 3. Deep CDS market 4. Seemingly remote from the shock. These

countries have been upgraded during the Crisis 5. Simple parity condition: same recovery rate 6. Convergence of arbitrage at maturity, or at

default.

Data Set #1 • We focus on three sovereign (non USD and Euro) countries:

• Turkey, Brazil and Mexico

• Split sample in four : Pre-Crisis, Liquidity and Credit crises, and Post-Crisis Periods)

Eurobond Default and the Paris Club

• The Paris Club coordinates the “comparability of treatment” clause, to ensure equal exposure of all creditors to the same sovereign debt (independent of currency denomination or maturity)

• This is designed to avoid selective default. • All our bonds are regulated under the same jurisdiction (New York State Law) and

by very similar collective action rules (qualified majority consent: 75% threshold). Equal recovery rates.

• Example: Ukraine Case (2000)

• In 2000, Ukraine defaults on both DM and USD eurobonds

• Exchange proposal: In the workout, Bondholders could eventually choose between two 7-year coupon amortization bonds denominated either in usd or euro. The difference in costs between DM and USD bondholders was effectively the same.

• Symmetric treatment: Equal usd and euro haircuts

Brazil

Mexico

Turkey

Size of Dislocation

• On October 8th 2008, Basis for 2015 Brz was 104 bp after fees • On October 10th 2008, Basis for 2010 Brz was 407 bp after fees • Between Oct 23rd – Oct 31st 2015 Brz Basis ranges between 250bp - 345bp • At the same time, large Basis for Mexican and Turkish bonds

In Dollar Terms Dollar Mispricing after FX hedging and transaction cost adjustment

In dollar terms the size of the risk arbitrage is very large: between 4 and 14 dollars per 100/notional

Frictions

Which of the following channels are significant?

1. LIQUIDITY RISK?

3. SHORT-SELLING CONSTRAINTS?

4. LEVERAGE AND FUNDING COSTS?

2. FX CORRELATION RISK?

FX-Liq: Latent Liquidity based on Griffoli and Ranaldo (2011) FG-Liq: Global Bond market liquidity factor (US, EU Treasuries)

Explanation 2: Correlation USDEUR-Default Risk?

• In case of default, the trader could find himself under-hedged or over-hedged, depending on what happened to the value of the EURUSD swap in the meanwhile.

• Technically the economic value of the residual risk is equal to the value of a “Extinguishable Cross-currency EURUSD Swap”, which depends on the correlation of Brazil default events and the EURUSD exchange rate.

• This is unlikely to be the main explanation: 1. We have data on the spread between USD-CDS and EUR-CDS to minimize residual

FX risk. We have data on EU countries (likely to offer an upper bound).

2. MEX and BRZ trade rich in USD, thus one would buy the EUR bond and sell forward the EUR cash flows in the FX market for USD. The USD revalued slightly (conditional on default, see spread). However, the TUR bond was trading cheap in USD, which requires the opposite assumption in terms of correlation with the other pattern.

Explanation 3: Short Selling Constraints?

Data on Sovereign Repo Market:

• Data Explorers (later acquired by Markit): Data provided by major prime brokers, custodians, and the lending desks of asset managers and hedge funds that actually lend/borrow these securities (over 100 participants).

• Daily dataset on bond lending and borrowing

• Covers approximately 85% of the OTC securities lending market. 1. Total available lending, “Supply” filtered by “active” 2. Loan fees (cost of borrowing), value weighted average of all applicable

transaction-level securities lending fees weighted by loan value. 3. Total Amount Lent out 4. Actual Loan Transactions

• Used to obtain active loan utilizations and borrowing costs of Euro- and USD-denominated bonds across the three EM countries.

Libor - OIS

U.S. MBS - Repo

Available Stock of Lendable Assets

• Inventory dropped; Total Transaction dropped even more; Loan fees increased but not very much: the evidence seems more consistent with risk reduction.

Economic Risk Factors and Controls

The Cross-Section

• The most interesting thing (and inconsistent with many models of Limits to Arbitrage is that the sign of the Basis is different in the cross-section:

• The correct strategy for the trader is: • Turkey – Long USD bonds and Short Euro bonds • Mexico and Brazil – Long Euro bonds and Short USD bonds

• This cannot be explained by a single common risk factor affecting all these markets at the same

time (i.e. violations of the CIP)

The Geography of the Basis

The Geography of the Basis

• Possibility that frictions work at the geographical / institutional level

• CONJECTURE (Ivashina, Scharfstein, and Stein (2012)): • Suppose that Turkey is 100% financed by EU banks (and opposite for MEX and BRZ) • A European bank can finance:

• Euro loans by Euro insured deposits (domestic financing) • USD loans by USD-denominated CP paper (“wholesale financing”, with CP paper bought by US mutual funds)

• The presence of an insurance subsidy may create a differential in funding costs • It is known that the wholesale financing channel was in distress. The differential may

increase funding costs of USD denominated assets (and the opposite for MEX and BRZ, if these are financed by dollar-based financial institutions)

• Two important objections: a) EU banks could raise EUR and exchange them in the forward USDEUR market.

Higher credit risk does not necessarily imply LOP deviations: thus, this conjecture also requires limited capacity in the forward FX market to induce a LOP violation. With no frictions in forward market the USD supply is unaffected, one would simply see a change in the borrowing market.

a) U.S. banks could fill-in the gap and lend USD directly to Turkey.

But why did not they do it in the first place? Maybe the same institutional friction is in place.

The Geography of the Basis

Commercial Paper Market in 2007-2008

• Fed-ECB currency swap facilities (December 2007) was in part motivated by the need to partially relax this constraint.

• Stress in money markets starts in mid-2007 (BNP Paribas, Credit Agricole, Soc Gen) FT (August 13, 2007): “European financial institutions are finding it difficult to secure dollar funding to support conduits or which they had committed backup (dollar) liquidity.”

• The story here is not one of “capital-crunch” (Peek and Rosengreen 1997) where a shock to balance sheet of a bank affects its overall lending , but one affecting the financing of different assets.

• The general increase in counterparty risk and the capital repatriation of U.S. financial institutions reduced the supply of dollars in the interbank market, giving rise to a cross-section dispersion in capital availability.

• Is there empirical evidence of a geography of funding capital?

• From BIS: detailed data on the geographical distribution of bank holdings: • All contractual lending by the head office, and all its branches (and subsidiaries)

on a worldwide consolidated basis but disaggregated by country exposure.

• We strip out all other forms of lending to focus exclusively on sovereign bond exposure.

• The classification is based on “Ultimate Risk” (as opposed to “Immediate Borrower”). Namely, the country where the guarantor of the claim is located, or in other words, where the domestic bank head office is located. The exposures of the foreign branches and subsidiaries are included.

• Example: a purchase by the Morgan Stanley London branch of Turkish bonds, for instance, contributes to the exposure of its U.S. head office.

Data on Geographical Exposure

The Case of Turkey

• At the same time: - European banks USD unsecured funding costs peaked in Summer 2007, and then

again immediately after Lehman. - Which was the result of a dynamics both in the deposit and CP markets.

• TRYUSD Basis Swap turns negative:

Unsecured cost of borrowing USD increases to 250 bps.

• USD assets become much more expensive to fund

• Regression 1.

• Regression 2 (Diff-in-diff). Use Turkey as a control group

,

| ( ) | ' | ( ) |

| ( ) | ' | ( ) |

TR t t

Mx Br t t

Basis bond Usd CP Euro Dep

Basis bond Eur CP Usd Dep

β ε

β ε

∆ = ∆ − +

∆ = ∆ − +

,

,

,

,

| ( ) | | ( ) |'| ( ) | | ( ) |

| ( ) | | ( ) |'| ( ) | | ( ) |

MX t tt

TR t t

BR t tt

TR t t

Basis bond Eur CP Usd DepBasis bond Usd CP Euro Dep

Basis bond Eur CP Usd DepBasis bond Usd CP Euro Dep

β ε

β ε

∆ ∆ −= +

∆ ∆ −

∆ ∆ −= +

∆ ∆ −

Regression Set-up

Immediately after Lehman:

• Substantial drop in USD deposit

• Capital hoarding and repatriation?

Immediately after Lehman:

• Substantial increase of USD deposit rate from -20bps to +80bps

• Capital hoarding and repatriation?

Frictions and Price Discovery

Frictions and Price Discovery • If it is really a friction-based story, it is likely that the friction is visible if we estimate

an error correction setting. • The arbitrage relation suggests a natural specification: a b

t t tz S kS= −

The Role of the Central Banks

Monetary Interventions: Were they effective? … and on what frictions?

Questions: • Did U.S. liquidity/monetary interventions helped relaxing some of these frictions? In particular, given

that an important friction seems related to the Unsecured and FX markets, did SWAP extensions and purchase of CP paper help?

• Note: Turkey did not have access to the SWAP program, so that Turkey provides a control group.

• If arbitrageurs are contemporaneously present in multiple asset markets, balance sheet shocks to arbitrageurs can give rise to contagion effects across assets that are seemingly unrelated (Gromb and Vayanos, 2009).

Liquidity Phase: 1. Term Auction Facilities (TAF): To lend USD funds directly to depository institutions for a fixed

term (28 or 84 days). December 12, 2007; then January and February 2008. Limited supply of USD capital

2. Swap Lines Opened with Central Banks December 12, 2007 ECB and Swiss National Bank

Credit Phase: 3. FX Swap Lines; TARP; MBS Purchases; TALF

Swap Lines Opened with Central Banks Date Central Bank September 18, 2008 ECB, Bank of Japan, Bank of England, Bank of Canada September 24, 2008 Reserve Bank of Australia, Sveriges Riksbank, Norges Bank, Danmarks Nationalbank October 28th, 2008 Reserve Bank of New Zealand October 29th, 2008 Banco Central do Brasil, Banco de Mexico, Bank of Korea, Monetary Authority of Singapore

Mexico used it on 21 April, 16 July, and 14 October 2009 (tenor 88 days, 3.22bn/each) Turkey did not receive USD funding via swaps at any time. 4. Commercial Paper Funding Facility (07 October 2008): PAF

Monetary Interventions: Event Study Design

Event-Time Analysis

Compute changes in the basis in the period following an announcement (1W, 2W, 3W), with respect to changes in the control group (Turkey) Investigate impact of different announcements on the basis for country j at maturity m, period 17 Nov 2006 – 26 Mar 2010;

5 6 7[ ] [ ] m m mTR MEX j t t t tBasis Basis SWAP PAF PAT Controls Lagsα β β β ε∆ −∆ = + + + + + +

5 6 7[ ] [ ] m m mTR BRZ j t t t tBasis Basis SWAP PAF PAT Controls Lagsα β β β ε∆ −∆ = + + + + + +

Conclusions: Ecosystem of Arbitrage

HF Prime Broker

Investment Bank Secured / Collateral

Borrowed Security

Short / Long

Hedge Fund Capital Structure

Investment Bank Capital Structure

Unsecured Loan (CP) Equity (Insured deposits)

Limited Partners

Assets

FED Provider of Liquidity?

Proprietary Trading Desk

Short / Long

What Are Potential Frictions and .. .. did policy interventions help?

Frictions 3: Leverage Constraints

Secured Funding (collateral)

Frictions 3: Leverage Constraints Unsecured Funding

Frictions 2: Short-Selling

Frictions 1: Liquidity

Conclusions • Sovereign Bond Basis is time-varying and state-dependent.

• FOUR POTENTIAL EXPLANATION IN THE LIMITS TO ARBITRAGE LITERATURE:

• Liquidity. No: There is something more to the story

• Short-Selling Constraints. No: Loan inventory and transaction quantity are significant, but the insignificance of Loan Fees suggest that short-selling constraints is not the main part of the story

• Funding Liquidity and Leverage Constraints: Unsecured Funding channel is important

• Macro Demand Risk: Macro-activity shocks and Discount rate risks clearly interact with these

frictions. • The existence of a geography of funding markets highlights the importance of knowing the characteristics of

bank exposure distribution in order for Central Bank interventions to be effective.

THANK YOU