Analyzing credit is a lot like analyzing equity–at least the way equity has traditionally been analyzed. You look at a company’s balance sheet, its cash flow, its obligations, and make a rating based on that analysis on whether the company is very safe, a little safe, or risky. Those ratings are more codified and universal in the world of credit than equity, thanks in no small part to the big ratings agencies (Moody’s, Fitch, and S&P Global), which have a couple of A, B, C systems that are pretty widely used by credit analysts. But they still run by the same basic principles–to a point.
A big difference between credit and equity is the predefined nature of the earnings a credit gives the creditor. You buy a stock because you think it will go up, but there’s no predefined amount by which it will go up to that is agreed upon by the stock issuer and you. In credit, there is; a company will issue, say, $1 million in bonds paying a 2% coupon over 5 years, and if you buy that bond you’re agreeing that you will get $1 million in principle back in 5 years and $20,000 per year for the next five years.
This changes the calculus significantly, because all bonds pay a coupon, but they don’t all pay the same coupon. Thus one company that is equally as creditworthy as another company but pays a higher coupon is a more desirable buy, and the price of their bonds should rise to reflect that (which also would lower the effective yield of the bond to normalize with the other company). Furthermore, there are disagreements on companies’ creditworthiness, which makes this analysis more contentious and volatile over time.
Then there is the duration issue; a bond that pays principal back in 5 years is less risky than one paying it back in 10 years, so the yield should be lower. The relationship between yield and duration creates another data point for the credit analyst; she may decide that the company’s risk in being less creditworthy in 10 years is much more significant than in five, making the yield on the longer term bond significantly higher.
The relationship between a yield on two bonds issued by the same company (or government entity) over different durations is known as the curve, and the yield curve was very famous in 2018-2019 because the yield curve for U.S. Treasuries tightened and eventually inverted. Inverted yield curves have proceeded recessions every single time in history, and the fact that the pandemic-induced recession happened within that time frame is one of the spookiest events in financial history (since we cannot imagine that U.S. Treasuries started the pandemic!).
In addition to this curve, there is the spread. Like the curve, this is a measure of yields on two different bonds–but here we’re comparing bonds by different issuers, not of the same issuer but different duration. For instance, if we compare the yield on a 5-year bond from Amazon (AMZN) to one from the U.S. Treasury for 5 years, that is a bond spread. Bond spreads are important, because we often compare riskier bonds to less risky ones (Amazon doesn’t print their own money–at least not literally–so it is riskier than the U.S. government, which does) to determine the “risk premium” we get from buying a particular bond. If the premium is too high (or too low) for one bond compared to another similar bond, that’s a price inefficiency we can profit off of.
Understanding yields, curves, and spreads is the beginning to getting into credit analysis–and it’s the tip of the iceberg. But one can see that the world of credit analysis involves a lot more math and a lot more opportunities for mispricings than equities, which ultimately depend on three things: revenues, expenses, and earnings. This may be partly why so many more active investors beat the indexes in credit than they do in equity.