The Best Simple Measure for Evaluating Credit Risk of Publicly Traded Firms for a Stock Investor

Picture Credit: andrechinn || A cute idea stemming from contingent claims theory!

I was looking at conditions in the shipping industry today, and I thought back on a stock that I used to own — Tsakos Energy Navigation Limited [TNP]. I think I sold it in 2007 or so. I was shocked to see it selling for a tiny fraction of the price of where I sold it. And so I thought: Is it going to go broke?

I turned to my favorite measure of credit risk to try to answer this: (Long-term Debt + Short-term Debt) / Market Capitalization. Unless a company is in a very stable industry, I like that figure to be under one. For TNP, it is not a stable industry; it is in a highly cyclical business. The current value of that statistic is 11.

What’s the logic here? Debt claims are fixed as far as the debtor is concerned. For TNP, all of the debts are secured by their ships. But the best estimate of what the residual claimants (stockholders) have for the value of their holdings is market capitalization. Thus the ratio of debts to market value of equity can be a simple summary of how levered the company truly is. In this case, TNP sells at around 0.1x of its book value. Is it cheap? Yes, and particularly on a Price-to-sales basis. Is it safe? No. Will I buy some? No. Will I short it? I never short. Is it going broke? Who can tell? It doesn’t have a sufficient margin of safety for me.

If I were one of the banks lending against the TNP ships, I would look at different metrics — Value of the ship as a ratio of the loan, marginal earnings of the ship as a ratio of financing costs, etc. But if TNP decided to not pay on any ship loan in hard times, it would negatively affect their ability to finance new ships, and refinance existing ships. Not paying would be catastrophic.

The intuitive way to think about this ratio is like this: the value of a stock is the present value of the future free cash flows. The value of the debt is the present value of the future debt payments. So the higher the ratio goes, the thinner the margin is for making the debt payments. Also, equity has the optionality of “Heads I win, Tails you lose” to creditors. The most the creditors can do is get paid back, but they can lose it all (in this situation for TNP, the downside is capped by the collateral). But though the equity can lose it all, in the right situation they can multiply the value highly if the cycle turns favorably.

Anyway, I think this is the best quick take on credit risk as far as stockholders are concerned. If others have better ideas, please share them in the comments.

3 thoughts on “The Best Simple Measure for Evaluating Credit Risk of Publicly Traded Firms for a Stock Investor

  1. Since you insist on promoting Twitter, I am not going to write anything constructive on your blog.

    Censorship is a horrible thing. Twitter is a horrible thing.

    Please stop supporting censorship

  2. Indeed, cut off your nose to spite your face. Twitter censors very little. Freedom of speech is not absolute, especially in private forums, and generally moderation of comments makes for a better discussion. Twitter has a total right as a private entity to have a “house view” and bar comments that they don’t like. I occasionally delete comments and bar users because they don’t fit my commenting rules. It makes for a better internet, and a better Aleph Blog.

  3. This is a nice rule of thumb, but it’s intellectually unsatisfying, as the market capitalization of a company ultimately depends only upon the market sentiment about that company.

    Following your rule stringently just adds a constraint that binds you a bit to market consensus. That might be safe, but it doesn’t seem terribly insightful all on its own. And highly levered companies with narrow equity stubs can be quite profitable purchases for common shareholders if the company manages to avoid bankruptcy.

    I agree you’d probably avoid a lot of bad situations following your rule, but you’d also never look at a couple possibilities that end up working wonderfully. So how does this rule fit into some larger framework that helps you surface good opportunities?

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