El secreto empresarial: ¿Fomento o freno del progreso?

Recent research has shown that default risk accounts for only a part of the total yield spread on risky corporate bonds relative to their risk-less benchmarks. One candidate for the unexplained portion of the spread is a premium for liquidity. A few researchers have studied liquidity risk, or joint liquidity risk together with default risk.

CHAPTER 2. LITERATURE REVIEW 32

Liu, Longstaff, and Mandell (2006)[56] study how the market prices the default and liquidity risks incorporated into an interest rate swap spread. Trea- sury, repo and swap term structures are jointly modelled using a five-factor affine framework and estimate the model by maximum likelihood. In their pa- per, the credit spread is driven by a persistent liquidity process and a rapidly mean-reverting default intensity process. They found that the credit premium for all but the shortest maturities is primarily compensation for liquidity risk, and the term structure of liquidity premia increases steeply while that of default premia is almost flat. Both liquidity and default premia vary significantly over time.

As shown in Figure 2.1, they found that the credit spread in swaps consists of both a liquidity component and a default component. On average, the default component of the credit spread is larger, but the liquidity component is slightly more volatile. Both components vary significantly over time. The liquidity com- ponent display a high level of persistence. In contrast, the default component is rapidly mean reverting. In addition, the default component exhibits a number of large but temporary spikes in its level over time.

In order to explore the role of liquidity risk in the pricing of corporate bonds. De Jong and Driessen (2005)[18] employs bid-ask spread of long-term US trea- sury bonds to measure liquidity. They show that liquidity is a priced factor in a multifactor model for the expected returns on corporate bonds. The corpo- rate bond returns have significant exposures to fluctuations in treasury bond liquidity and equity market liquidity. Furthermore, the associated liquidity risk premia help to explain the credit spread puzzle. They discovered for the US market, the total estimated liquidity premium is around 45 basis points for long-maturity investment grade bonds; whereas for speculative grade bonds, which are exposured to higher liquidity risk, the liquidity premium is around 100 basis points. Similar evidence is found for the liquidity risk exposure of corporate bonds using a sample of European corporate bond prices.

Figure 2.1: Liquidity and Default Components of the Credit Spread The top panel plots the liquidity component of the spread. The middle panel plots the default component of the spread. The bottom panel plots the sum of the liquidity and default components which equals the credit spread. All time series are measured in basis point. The sample period is January 1988 to February 2002. Source: Liu, Longstaff, and Mandell (2006)

CHAPTER 2. LITERATURE REVIEW 34

with model prices is carried out by Houweling and Vorst (2005)[39]. They show that a simple reduced-form model gives more accurate estimates of default swap premiums than the bond’s yield spreads. Moreover, they shed light on the choice of the default-free term structure of interest rates. Their model yields unbiased premium estimates for default swaps on investment grade issuers, but only if swap or repo rates are used, as they state that swap and repo curves significantly outperform the government curve as proxy for default-free interest rates. Their paper confirms that financial markets no longer see Treasury bonds as the default-free benchmark empirically.

Feldhütter and Lando (2008)[31] also attempt to decompose the swap spreads through a joint pricing model for treasury securities, corporate bonds and swap rates using six latent factors, and decompose swap spreads into three compo- nents: a convenience yield (liquidity) from holding Treasury securities; a credit spread arising from the credit risk element in LIBOR rates, which define the floating-rate payments of interest rate swaps; and a factor specific to the swap market. The convenience yield, which separates the Treasury yield from the riskless rate, is by far the largest component of the swap spreads. The other two components separate the swap rate from the riskless rate. The credit risk component does not contribute much to the time variation of spreads.

A discernible contribution from credit risk exists as well as from a swap- specific factor with higher variability which in certain periods is related to hedg- ing activity in the MBS (mortgage-backed security) market. Their model also sheds lights on the relation between hazard rates and the spread between LI- BOR rates and General Collateral repo rates and on the level of the riskless rate compared to swap and treasury rates.

A more structural approach is adapted by Shin (2008)[70] to explore the pricing of debt in a financial system, where the assets that borrowers hold to meet their obligations include claims against other borrowers. Accessing finan- cial claims in a system context captures features that are missing in a partial equilibrium setting, such as liquidity spillovers across financial institutions re-

sulting from expansions and contractions of balance sheets. Aggregate liquidity can be seen as the rate of growth of a financial sector’s balance sheets. The fo- cus of Shin’s paper is on the liquidity of the financial system as a whole, where “liquidity” refers to the funding conditions for current and potential borrowers. For existing borrowers, rising asset prices strengthen their balance sheets and make them more credit worthy. For potential borrowers, the stronger balance sheets of financial intermediaries play to their advantage. His framework is eas- ily extended to deal with claims of differing seniority classes, and is well-suited to pricing complex debt instruments such as CDOs (collateralised debt obliga- tions), since CDOs are obligations that are backed by claims on others. His model is also well-suited to quantitative analysis of risks such as value-at-risk calculations that take account of endogenous changes in asset prices and the feedback effects that result.

In contrast to previous evidence from corporate bond data, Ericsson and Reneby (2007)[29] evaluate the price of default protection for a sample of US corporations using a set of structural models. They found that CDS premia are not systematically underestimated. They perform the same exercise for bond spreads by the same issuer on the same trading date for a robustness test, which shows that bond spreads relative to the Treasury curve are systematically un- derestimated, which is not the case when the swap curve is used as a benchmark, suggesting the previous documented underestimation results may be sensitive to the choice of risk free rate. They explain the reason why the swap curve outperforms the treasury curve is that the swap curve lies closer to the cost of funding for traders in the bond market.