So far we have described a rather intuitive way of combining individual views in a portfolio. Top-down and bottom-up analyses have determined the overall strategy for the portfolio, spread class and sector selection and finally issuer weightings. This qualitative methodology does not require estimates of returns, risks and correlations between the investments, and therefore is easy to implement. Yet, it is not able to capture the full benefits of diversification and to tailor the expected risk/return profile of the portfolio to the preferences of the investor. Since the seminal work of Markowitz (1952), diversification is a central tenet of modern investment theory. In the context of credit portfolios it plays a crucial role, because it helps to control downside risk arising from single issuer credit events. Since the mid-1990s debt-financed M&A activities, share buybacks, and the introduction of new technologies have fueled the new issue pipeline and broadened the corporate bond universe. Meanwhile, the European corporate bond market offers sufficient market breadth and depth for institutional investors to construct thoroughly diversified portfolios. If the portfolio manager is capable of quantifying the risk and return characteristics of his investment alternatives, portfolio optimization approaches present a formalized and thus objective way of deriving investment recommendations. This applies irrespective of the performance target of the investor. Portfolio optimization can be used with respect to portfolios that are managed in absolute risk/return terms as well as portfolios that are managed relative to a benchmark index. Various constraints can be included, for example a short sales restriction for real money investors, maximum concentration limits or esired duration ranges.

The following paragraph will deal with default rates because they are of central importance for high-yield investors. We compare the three major default peaks since 1920. Default rates have to be distinguished between “issuer-weighted” and “dollar-weighted”. The increasing amount of Fallen Angels in 2002 resulted in a sharp increase of the “dollar-weighted” default rate.

High-yield spreads tend to lead default rates, which means that a tightening will occur prior to a fall in the default rate because market participants will already anticipate the future development of the default rate. This relationship broke down in 2002 for a couple of months due to the large divergence of the “dollar-weighted” from the “issuer-weighted” default rate. As we can see cumulative default rates tend to increase progressively with a decreasing rating class.

Monetary policy, too, appears to be an important indicator for corporate credit spreads. Let us assume that the economy is at the brink of deflation. Generally, deflation tends to be accompanied by a rise in bankruptcies. When corporate revenues and earnings are weak, highly leveraged borrowers have difficulties to meet their obligations. In this situation central bank easing paves the way for future economic growth. The traditional channels by which a lowering of the federal funds rate tends to stimulate faster growth in real and nominal GDP are: (1) lower debt cost of capital, (2) higher stock prices, (3) dollar weakness, (4) consumer durables, including automobiles, and (5) housing. Hence, it lowers the equity cost of capital and bolsters consumer confidence through the wealth effect. We see that  Baa credit spreads usually reach their peak when the Fed has done approximately two-thirds of the interest rate cuts.