Archive for October, 2009

Credit and equity prices and volatility

Generally, equity-based models for credits have to be analyzed in the context of the leverage cycle. When the level of debt remains constant, equity as well as credit investors both benefit from rising equity prices, driven, for example, by increasing earnings estimates. When leverage is rising like, for instance, between 1997 and 2000, equities tend to perform well while credit spreads widen at the same time. Conversely, deleveraging through rights issues or asset disposals, cost cutting and dividend cuts provide a favorable environment for credit, but not for equities. As Figure 3.24 shows, there is undoubtedly a relationship between equity prices and credit spreads. Yet, this relationship varies over time, depending on the current and the expected fundamental environment in the future.

Models that only relate credit spreads to equity prices therefore need to be interpreted cautiously. Assume, for example that the management of a company signals its willingness to concentrate on the creation of shareholder value. Then the probability of leveraging increases substantially. If there has been no decoupling, credit investors should take that as a sign to be rather bearish.

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Learn how to value corporate credit

One of the most widely used indicators to value corporate credit is the equity market. The Merton model formalizes the relationship between leverage, equity prices, equity volatility and credit spreads. While the model permits an assessment of the relative valuation of equity and credit, it makes no explicit statement about which of the markets is currently priced correctly, or if both markets are in disequilibrium. In addition, focusing solely on equity prices and volatility neglects the effects of changes in leverage. However, equity-market performance contains information about the future state of the economy, the future cash flows and risk premium in the market. Stronger cash generation benefits corporate bonds since creditworthiness improves and the required risk premium is lower. Furthermore, as the equity cushion increases through rising equity prices and more IPOs and equity volatility decreases, default probabilities and spread levels tend to fall.

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The ratio of sales to loans and assets

The ratio of sales to assets is an asset turnover ratio that measures the sales-generating capacity of a given asset base. Taking the nominal GDP of the nonfinancial corporate sector as a measure for sales. The ratio has started to turn up at the beginning of 2001. This pattern is normally consistent with periods of recovery. However, it should be noted that this ratio is near its historical low. The z-score for the nonfinancial corporate sector has collapsed dramatically since 2000, resting well below the critical level of 1.8 since the second quarter of 2002. For an individual firm this signals that the company is likely to fail within 2 years. On the macro level it indicates a high probability of rising default rates and widening credit spreads. Three points stand out:

  • based on macroeconomic data the z-score has never been in the safe zone;
  • the average score since 1952 is about 2;
  • in the 1970s and 1980s, the z-score was permanently in the distress zone implying that corporate America should have gone bankrupt, but clearly it survived.

This leads to the conclusion that the weighting scheme is no longer appropriate to capture the vulnerability of the corporate sector. The relative importance of the individual factors changes over time. Therefore, it is necessary to adjust the weighting scheme on a regular basis, for example by using a regression methodology.

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The ratio of credit earnings before tax, interest depreciation

A second metric for profitability is the ratio of earnings before tax, interest depreciation and amortization (EBITDA) to total assets. Using data from the national accounts of the United States we define earnings before tax and interest as pre-tax profits with inventory valuation and capital consumption adjustment plus net interest. This metric follows a similar path as the ratio of retained earnings to total assets, although on a higher level and with a higher volatility.

Measuring the extent to which a firm’s value can decline before its book value becomes negative and a firm becomes insolvent, the ratio of market value of equity to total debt represents the inverse of leverage. We have defined the value of equity as the market value of outstanding equities, total debt is defined as total credit market instruments. The tremendous equity bubble of the late 1990s has collapsed, but nevertheless the equity-to-debt ratio stays above the level reached in the 1970s and 1980s. Because of its higher volatility, the ratio is largely driven by the equity performance. As a result the equity-to-debt ratio usually rises at the end of a recession because equity markets already
anticipate stronger economic growth while many companies still deleverage their balance sheets. Here again, the 2001 recession makes an exception.

About one-and-a-half years after the end of the recession in November 2001 equity markets finally marked their lows.

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Measure for mortgage profitability

A common measure for profitability is the ratio of retained earnings to total assets. We defined retained earnings as undistributed profits, that is, after-tax profits minus dividend payments. Like the working capital ratio, the profitability measure is on a downtrend in the longer term. During recessions the profitability of the companies usually declines. It is worth noting that the latest recession in 2001 marks an exception with respect to the ratio of internal funds to total assets. Whereas the profitability declined like in any other recession before, the cash flows of the companies on average improved in this period due to rigorous cost cutting in the corporate sector.

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Fundamental models for loans spreads

A popular approach to estimate the credit risk of an issuer is the use of z-scores. In this context, Altman’s five components framework has attracted particular interest. On the company level, it is based on the five metrics.

Replacing the company-specific metrics by macroeconomic factors yields a fundamental model for the credit market. Because of the required minimum history and data reliability we will focus on the US market. Data for this procedure is taken from the flow of funds statistics and the national accounts of the United States.

The ratio of working capital to total assets measures the net liquid assets of a firm relative to the sum of financial and tangible assets. We isolated net liquid assets for the US nonfinancial corporate sector from the flow of funds statistics by subtracting mortgages, consumer credit, trade receivables and miscellaneous assets from total assets and subsequently adding inventories, trade and tax receivables.

The large fall in 1974 is due to a significant decline in the value of trade payables. Usually, the ratio of working capital to total assets falls in a recession. But there also seems to be a secular downtrend in this ratio.

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The fundamentals of credit valuation

Besides market fundamentals valuation is the major driver of market performance for the longer term. The other two drivers that are commonly mentioned in investment literature, technicals and market sentiment, are more likely to explain short- to medium-term fluctuations of credit spreads.

The subject of valuation arises on every level of the investment process. Generally, it is a question of relative attractiveness of one investment vis-avis another one. In this chapter, we will outline four approaches that may support asset allocation decisions in fixed income portfolios with an aggregate benchmark as well as help to determine the beta of a pure credit portfolio.

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How to compensate for default payday risk

The spread needed to compensate for default risk depends upon future default rates, recovery rates and ratings transition probabilities. The rating agencies publish their forecasts of future default rates based on historical data. Usually required spreads come out significantly lower than current spreads for investment grade companies. For high yield, however, observed spreads tend to be too low, given the actual risk of default. While over the long term buy-and-hold strategies may earn an excess return over government bonds for pure investment grade portfolios, this strategy is not appropriate for high-yield portfolios. Here, investors need to focus much more on the process of selecting the right companies and avoiding the blowup names. A look at historical data shows that market spreads tend to overshoot at the end of credit cycles, especially in the wake of a recession.

For example, even if the historically high default rates of 1990/91 had persisted over the following years, investors should have required a BBB credit spread of only 115 bps for medium-term bonds. At that time the average market spread for BBB-rated issues, however, peaked at more than 180 bps.

Consequently, the market was much too bearish in 1991. Conversely, in 1997, at the beginning of the severe bear market for credit, spreads were too tight for the period of downgrades and credit blowups that followed. Note that these observations apply for bonds with a maturity of roughly 4 years.

While the cushion is not as comforting as for shorter maturities, even at the long end the spread levels reached in recessions provide sufficient protection, even when assuming that default rates stay high for a sustained period of time.

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Changes in credit quality

With regard to the above-mentioned problems, rating migrations seem to be a more reliable indicator of changes in credit quality than default rates. Given that the risks of downgrade as well as default vary over time, the question is whether credit spreads compensate investors adequately.

Since the sample for the calculation of rating transition matrices is much broader than for default rates, they are less likely to be biased by changes of the rating agencies’ universe. To measure changes of credit quality over time, the ratings drift, that is the number of upgrades minus the number of downgrades, as a proportion of the total number of entities rated, can be a valuable indicator. A sample of high-quality issuers, however, will tend to have more downgrades than upgrades, and vice versa. Hence, variations of the ratings drift partly reflect changes in average credit quality over time.

As one would expect, credit spreads tend to rise when the ratio of upgrades to downgrades becomes worse.

The question, however, is, whether the credit spreads widen enough to compensate investors sufficiently for the  deterioration of average credit quality that is reflected by a falling ratings drift. While predicting the direction of spread changes may help to make money on a mark-to-market basis, it is not adequate for buy-and-hold investors. They have to estimate the magnitude of the spread widening that corresponds to an observed deterioration of credit quality. Hence, the focus is purely on credit risk, while credit spreads also incorporate liquidity premia, and are influenced by technical factors and market sentiment.

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The correlation between credit spreads and the business cycle

Fama and Chen examine the correlation between credit spreads and the business cycle. They find empirical evidence that corporate bond spreads are good predictors of future economic growth. Based on empirical data from 1933 to 1997, a recent study by Koopman and Lucas (2003) reveals two different types of cycles. On the one hand, there is a cycle with a frequency of about 6 years, where a positive correlation between credit spreads and default rates, and a negative correlation between spreads and economic growth can be observed. On the other hand, a second cycle with a duration of about 11 years shows a positive link between spreads and business failures, and a negative correlation between GDP growth and both spreads and default rates. However, constraining the analysis on the post Second World War era no significant correlations between credit spreads, default rates and the business cycle could be found.

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