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Do Liquidity Or Credit Effects Explain the Behavior of the LIBOR-OIS Spread?

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Do Liquidity Or Credit Effects Explain the Behavior of the LIBOR-OIS Spread? Do liquidity or credit effects explain the behavior of the LIBOR-OIS spread? Russell Poskitta a Department of Accounting and Finance, University of Auckland, New Zealand Abstract: This paper decomposes the LIBOR-OIS spread into credit risk and liquidity components using premia of credit default swaps written on LIBOR panel banks as a proxy for the credit risk premia. The decomposition analysis reveals that changes in liquidity rather than changes in credit risk lie behind the major swings in the LIBOR-OIS spread over the course of the global financial crisis. Regression analysis shows that the behavior of the credit risk component is well-explained by a structural model of default. The behavior of the residual liquidity component is also well-explained by two liquidity variables derived from the offshore market for three-month US dollar funding. I find evidence of liquidity variables affecting the credit risk premia but no evidence of credit variables affecting the liquidity premia. (198 words) Key words: LIBOR-OIS spread, credit risk, liquidity premia, financial crisis JEL classification: G01, G10, G15 * Corresponding author. Address: University of Auckland Business School, Private Bag 92019, Auckland 1142, New Zealand. Tel: +64 9 373 7599; Fax: +64 9 373 7406; Email: [email protected]. 1 1. Introduction The financial crisis which began in August 2007 impaired the functioning of US dollar funding markets and disrupted a number of traditional money market spread relationships, of which the LIBOR-OIS spread is one of the more significant.1 Prior to August 2007, three- month US dollar LIBOR was typically 5 to 10 basis points above three-month OIS but at the height of the financial crisis this spread reached over 350 basis points before declining to more normal levels during 2009.2 In normal circumstances, arbitrage should ensure that the LIBOR-OIS spread does not reach these extreme levels. For example, when three-month US dollar LIBOR is well above the three-month OIS rate, arbitrageurs would make a three-month term loan in the interbank market, funding the loan by rolling over overnight borrowing in the federal funds market and hedging the interest rate risk by purchasing a three-month OIS contract (Gorton and Metrick, 2009). An excessive LIBOR-OIS spread is a sign that stress in 1 LIBOR (London Interbank Offer Rate) is an indicator of the average interbank borrowing rate in the offshore or eurocurrency market. The US dollar LIBOR fixing takes place daily in London for 15 different maturities ranging from overnight to 12 months. Fixings are a trimmed mean of the estimated borrowing rates submitted by a panel of sixteen banks comprising the largest and most active banks in the US dollar market. The sixteen banks on the US dollar LIBOR panel are listed in Table A1 in the Appendix. The OIS (overnight indexed swap) rate is the fixed rate on a fixed/floating interest rate swap where the floating rate is an overnight interest rate such as the federal funds rate. The OIS rate has emerged as the benchmark risk free rate in the money market. Although Treasury bills are acknowledged as risk free, they entail significant liquidity risk due to the “convenience yield” they offer investors (Feldhutter and Lando, 2008) OIS are not free of credit risk, but the credit risk is generally regarded as minor because the contracts do not involve the exchange of principal and the residual risk is mitigated by collateral and netting arrangements (Michaud and Upper, 2008). They are also considered to have minimal liquidity risk because the contracts do not involve any initial cash flow. 2 This paper focuses on the three-month spread since three-month LIBOR is the benchmark for many floating rate loans and is used in the settlement of derivative contracts such as short-term interest rates futures, forward rate agreements and interest rate and currency swaps. 2 interbank money markets is preventing the arbitrage process from working, either because the lender is unsure of the borrower’s creditworthiness or is uncertain whether it will continue to enjoy access to funds in the overnight interbank market for the full term of the loan. [insert Fig. 1 about here] From a theoretical perspective the LIBOR-OIS spread can be represented as the sum of credit risk and liquidity premia (Bank of England, 2007). Accordingly, the fluctuations in the LIBOR-OIS spread can be attributed to variations in credit risk and liquidity premia. This paper decomposes the LIBOR-OIS spread into credit risk and liquidity components using credit default swap (CDS) premia on LIBOR panel banks as a proxy for the credit risk component. The focus of this paper is on the behavior of the three-month US dollar LIBOR-OIS spread between July 2005 and June 2010. I am interested in two questions. First, what is the relative importance of credit risk versus liquidity premia and how have these components evolved over the course of the financial crisis. Second, and perhaps more importantly, is the behavior of these two components of the LIBOR-OIS spread consistent with the behavior of proxies for credit risk and liquidity. The decomposition of the spread must be meaningful if there is to be any merit to the subsequent analysis and discussion of the relative importance of credit risk and liquidity premia. Furthermore, it is also important that any divergence between LIBOR and the OIS rate can be explained by fundamental economic forces since a poorly functioning money market will impinge on the cost and availability of credit, with the potential to affect the real economy, and will likely jeopardize the effectiveness of monetary policy (Taylor and Williams, 2008). The unprecedented fluctuations in the LIBOR-OIS spread is a challenge for the existing theoretical literature on the functioning of interbank markets. This literature acknowledges 3 that the existence of an interbank market allows banks to access large volumes of short-term funds to manage liquidity shocks, thus avoiding the need to liquidate long-term assets (Bhattacharya and Gale, 1987). However one of the notable features of the global financial crisis has been the extreme difficulty banks have faced rolling over short-term funding in wholesale markets (Brunnermeier, 2009; Shin, 2009). It has become evident that one of the risks that banks face in tapping the interbank market is that suppliers of funds may withdraw funding based on noisy signals of bank solvency (Huang and Ratnovski, 2008). Several recent papers highlight the critical role played by asymmetric information in the functioning of the interbank market. In these models the credit losses suffered by a bank are private information and the lack of transparency over where credit losses reside gives rise to an adverse selection problem. Heider et al. (2008) develop a model that explains the phenomena of very high unsecured rates in interbank markets, liquidity hoarding by banks and the ineffectiveness of central banks liquidity injections in restoring interbank activity. In their model the type of interbank regime that arises depends on the level and distribution of credit risk. When the level and dispersion of credit risk is low, the adverse selection problem is minor, the interest rate penalty safe borrowers pay for the presence of riskier borrowers is low and the interbank market functions smoothly with full participation. If the level and dispersion of credit is significant, however, the penalty built into the interbank rate rises and safe borrowers drop out of the market due to higher adverse selection costs. When the level and dispersion of credit risk is high, the prohibitive adverse selection costs cause the complete breakdown of the interbank market: interest rates are not high enough to compensate lenders for lending to even riskier borrowers and banks with surplus funds abandon the market, leading to hoarding of liquidity. In addition, some riskier borrowers find interest rates too high and prefer to borrow elsewhere. 4 Baglioni (2009) presents a model that allows a more central role for liquidity shocks. Although there is no aggregate shortage of liquidity in this model, individual banks do not know whether their liquidity shock is transitory or permanent. A bank with excess liquidity can lend in the interbank market on either a short-term or a long-term basis. If the bank makes a long-term loan and the liquidity shock is permanent then this bank will be forced to borrow in the interbank market or sell illiquid assets (and possibly incur liquidation losses). The liquidity risk a bank faces will be more severe during a period of financial turmoil when liquidity shocks have greater volatility. The model also allows participants in the interbank market to be hit by a negative credit shock in the future. If this shock is large enough some banks may be pushed into insolvency. However the distribution of credit losses is private information giving rise to an adverse selection problem. In the Bagliono (2009) model the interplay of liquidity and credit risks can lead to gridlock in the interbank market during a period of financial turmoil when the volatility of liquidity shocks is high and adverse selection problems are severe. Banks short of liquidity will want to avoid being forced to sell illiquid assets at a heavy discount to their face value while banks long on liquidity will demand a premium on interbank term loans. This situation is likely to lead to the emergence of a spread between term and overnight interbank rates and to the cessation of lending in the term segment of the interbank market despite their being no aggregate shortage of liquidity. The unprecedented fluctuations in the LIBOR-OIS spread since August 2007 has prompted a number of researchers to examine the respective roles of credit risk and liquidity premia in the determination of the LIBOR-OIS spread.
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