The models presented in the previous chapters describe the price formation process in markets with different structures. As we saw in the previous article, among the markets with trade pricing rules, those governed by an order-driven execution system can be organized either as a continuous or as a call auction, while markets with a quote-driven system can be either a bilateral dealer market or a continuous auction that works as a limit order book.Within this outline, the Glosten and Milgrom (1985) model describes a bilateral quote-driven market in which dealers’ competition guarantees semi-strong efficiency; Kyle’s (1985) model proxies an order-driven call auction market where a specialist, or a number of market-makers, sets the market-clearing price after observing his, or their, customers’ aggregated order flow. Finally, the Grossman and Stiglitz (1980) model proxies an order-driven market where all participants can submit their demand schedules simultaneously.1 Since each demand function is a fairly accurate representation of a large number of small limit orders (Brown and Zhang, 1997), this market can be interpreted as a limit order book. As the next section shows, this interpretation has the advantage of considering all market participants as potential liquidity suppliers, i.e. of embodying the order-driven feature of a limit order book (LOB); it fails, however, to incorporate either the discriminatory pricing rule that characterizes an LOB or the agents’ strategic choices between limit orders and market orders. Section8.1 will introduce the reader to the discriminatory pricing rule and will sketch a basic model that embodies this rule; in this model, however, agents cannot choose the type of order to submit to the LOB, so section 8.2 presents models in which the choice between market and limit orders is endogenous.
A credit discriminatory pricing rule
Types of bank capital represent its own credit risk class
As a consequence each of the mentioned types of bank capital represents its own risk class. Investors clearly have to be compensated to carry the additional risks compared with senior bank bonds. Figure 4.3 shows that on average the spread differentials between senior bonds and Lower Tier 2, Lower Tier 2 and Upper Tier 2, and Upper Tier 2 and Tier 1 tend to be roughly equal. But one should note that spread volatility also increases significantly when moving to more subordinated types of bank debt. Again, this can be explained by the Merton model. Since Tier 1 and Upper Tier 2 bonds are designed to absorb losses before holders of senior bonds and Lower Tier 2 suffer a loss, the strike price of their embedded short put option is closer at the money than that of senior and Lower Tier 2 bonds. Hence, in absolute terms the delta of the short put is higher, causing larger changes of the value of the option and consequently spreads, when fundamentals change.
Different degrees of loans subordination
A second method to slice the corporate bond universe, especially the financial sector, is by different degrees of subordination. We discuss the characteristics of different types of bank debt in detail. In summary, Tier 1 preferred, Upper Tier 2 and Lower Tier 2 differ from senior bank debt in two major dimensions: with respect to loss absorption and interest deferral features. Both Tier 1 and Upper Tier 2 capital are able to absorb losses. But while missed interest payments are canceled immediately for Tier 1 issues they are repaid at a later date for Upper Tier 2 bonds. On the other hand, Lower Tier 2 debt contains no loss absorption features.
General fluctuations of credit spreads
BBB-rated corporate bonds obviously have a very high correlation to fluctuations of credit spreads in general. Although they made up on average only 25 percent of the Euro investment grade market, the influence of lower rated bonds on market spreads is substantial. Higher quality bonds, on the other hand, exhibit lower correlations to market spread changes. One reason is that their impact on the market direction is less pronounced because they are less volatile. But the second reason is probably more important. Euro corporate bonds are typically valued against swaps, that is the spread versus government bonds consists of two components: the swap spread and the spread over swaps. As a consequence changes of swap spreads have an influence on the spread of a corporate bond versus duration-matched treasuries. The higher the credit quality and the lower the spread of an issuer, the higher is the fraction of the benchmark spread that is due to the swap spread.
Investors require a premium for taking on credit risk
Investors require a premium for taking on credit risk. Not only does this premium, in other words the credit spread, have to increase with decreasing credit quality, but one also expects a higher sensitivity of spreads to changes of the fundamental environment for lower rated credits. As pointed out earlier, the assets of a company with a higher degree of leverage are nearer to the default threshold than those of a firm with a conservative balance sheet structure. In terms of the structural model the short put option on the assets of the issuer moves nearer at-the-money with decreasing credit quality, causing the delta to rise. Hence, a falling value of the assets, for example, in periods of a deteriorating economic environment and consequently declining equity markets, leads to a larger change in the credit spread the lower the credit quality of the issuer is.
Lagging indicators of credit quality
While in a single name context ratings are often criticized for being lagging indicators of credit quality, classifying bonds by rating is one widely used method to reflect the behavior of different risk classes in credit markets.
Many market participants argue that spreads themselves and spread volatilities are more timely indicators of an issuer’s credit risk than ratings. They consequently prefer to split the universe in spread class buckets. The disadvantage of this method is that it leads to relatively unstable compositions of the individual buckets and is less convenient, because the major index providers do not calculate indices based on spread classes. Since the different rating buckets constitute the corporate bond market as a whole, there is clearly a correlation between overall market fluctuations and the spread changes of the different rating subportfolios.
Selection of your credit spread class
The risk profile of a credit portfolio, in absolute terms as well as relative to a benchmark index, is largely determined by the weighting of different risk classes. Of course, the allocation of capital to riskier asset classes not only increases risk, but also offers ample opportunities for outperformance. From a top-down perspective there are various methods to split the corporate bond universe in different risk classes. Here the three most popular approaches are introduced: dividing the universe by rating classes, by degrees of subordination or by the degree of cyclicality of the different industries.
The tactical asset allocation in credit portfolios
The tactical asset allocation in credit portfolios combines top-down- and bottom-up analyses in order to arrive at medium- to short-term investment decisions. In this step of the investment process three major subjects are tackled:
- Spread class selection,
- Sector allocation, and
- Credit curve positioning.
When making a decision about the allocation of resources to different spread classes, elements of the top-down analysis clearly have a substantial impact, since the assessment of the fundamental and technical environment for credit and the valuation relative to other asset classes have significant influence on the positioning within the credit asset class. Conversely, credit curve decisions are usually implemented on a sector or, probably even more frequently, on a single issuer basis. Although elements of the bottomup analysis clearly influence the positioning on the credit curve, there are also some economy-wide indicators that have to be considered. Therefore, and with respect to the time horizon of investment decisions and their potential impact on active portfolio performance, the three abovementioned issues should constitute an own step in a structured investment process for credit portfolios.
The flow of your credit funds
The overall sentiment of investors towards the asset class corporate bonds is mirrored in mutual fund flows. Monthly and weekly statistics, for example, from Investment Company Institute, AIG and Trim Tabs, track the net flows into the major asset classes and their subcomponents. They also give an indication about the portion of cash held in mutual funds. The published numbers can help to explain movements in credit spreads that are not directly related to changes in the fundamental environment for credit. For example, they partly reflect risk appetite of investors. This is especially true, when looking at flows into high-yield bond funds. Major shifts in the asset allocation of institutional investors can also be observed from the data. Yet, published information on mutual fund flows tends to be behind the curve, in other words it is a lagging indicator for the activity of market participants and thus for credit spreads. But the analysis may help to spot long-term trends in the relative attractiveness of different asset classes.
Substituted equity by debt
In the last 20 years there were two periods, when US companies substituted equity by debt, especially by issuing corporate bonds. Consequently, between 1984 and 1990 and in the second half of the 1990s leverage rose dramatically. It also stands out that there were various periods when banks’ lending standards were extremely restrictive and one period, namely since 2000, when activity in the commercial paper market slowed down. Both events spurred corporate bond issuance in the past. If the usual pattern of the credit cycle holds, equity buybacks remain subdued until the economic expansion gains ground. As long as companies are willing to repair their balance sheets, net corporate bond issuance is also expected to be low. The analysis of the maturity structure of outstanding US and Euro corporate bonds shows a massive amount of redemptions for 2004 and 2005. On the other hand, while supply should remain weak during this period, demand for US financial assets by foreign residents is expected to remain strong. It is primarily driven by European investors and Asian central banks that pour huge amounts of money into the US capital market. A potential shift in the balance of supply and demand, however, is an important technical factor for the outlook for corporate bond spreads.
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Recent Posts
- A credit discriminatory pricing rule
- Types of bank capital represent its own credit risk class
- Different degrees of loans subordination
- General fluctuations of credit spreads
- Investors require a premium for taking on credit risk
- Lagging indicators of credit quality
- Selection of your credit spread class
- The tactical asset allocation in credit portfolios
- The flow of your credit funds
- Substituted equity by debt
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