Bill Rempel, a.k.a. NO DooDahs!

Value investors like to define risk in terms of company risk and not in terms of stock price risk. This makes sense for their particular trading style, since it focuses on long holding periods and stocks that already have significant negative price action over a recent period. To mitigate the company risk, value investors employ fundamental analysis of various company metrics. In order to minimize the risk of losing capital through adverse company-related events, there are a variety of financial metrics they can use, but this post will focus on solvency and earnings quality metrics.

Note that, in keeping with the earlier post titled Fundamental versus Technical Analysis, I confine discussion of fundamentals to include only those items which are independent of the statistics generated by market activity, such as past prices and volume.

Solvency Metrics

I’m familiar with the asset-based metrics of quick ratio and current ratio, but I almost never use those to make any decisions. I prefer metrics based on more dynamic methodologies. In evaluating solvency, I like to look at debt and debt servicing in relation to free cash flow.

Immediately I run into a definitional problem with free cash flow. There is a marked inconsistency in how free cash flow (FCF) is derived from the financial statements, but regardless of exactly how it’s derived, the concept of leftover cash once capital expenditure is accounted for determines if the company can generate cash to be used for business expansion. I found that I needed to pick, and apply consistently, a definition of FCF that is used to evaluate all companies. Investor Words has their definition, and Money Chimp has theirs, but the concept is the same. Here’s what the New York State Society of CPAs had to say about the issue.

… there is no real consensus on the definition of cash flow or free cash flow … This can lead to considerable misinterpretation when investors are relying on differing cash flow information provided by companies.

Their article is very informative and you really should read it, including the sidebars and exhibits. I think that applying a consistent definition of FCF is important when I’m evaluating potential investments.

Once I’ve chosen a definition that works for me, I can derive the FCF for companies I investigate from the MSN Money website, where their financial statements contain five years and five quarters of data in a more-or-less standardized format. Often a standardized or normalized FCF number over a five-year period makes more sense than a “trailing twelve months” number.

Debt in and of itself can be a thorny issue. Many value investors avoid companies with outstanding debt altogether, and I think that is a serious misapplication of Grahamian principles. Obviously a company with debt will be unlikely to fit the NCAV investor’s guidelines, and that’s where I think Graham was going when he spoke of avoiding companies with debt – they make lousy cigar butts. Personally, I like to screen for value stocks that have some debt! When a company has zero debt and first turns to financing cash from debt, they are unfairly punished (think “caning”) for it in the marketplace, whereas a company with a small amount of debt not only has taken its licks for it, but may get credit for reducing the amount of debt. In any event, I see a debt/equity ratio over 2.0 as problematic and a debt/equity ratio over 5.0 as “stay away or trade on technicals only.”

I like to track the debt/equity ratio over time. Ideally a well-managed company will have stability or improvement in this ratio over any considerable period, but occasionally a value stock will have a negative spike in this metric, followed by improvement in a recent time period. This could make a good setup screen for value investing.

Total debt as a ratio to FCF provides some insight into how long the company would take to pay off existing debt, if it wished to. When a company has no serious chance of ever paying off its existing debt, I wonder about that company’s solvency risk over the long term.

Another good solvency metric is debt service divided by the (pre-debt service) operating cash flow. See “The Power of Cash Flow Ratios” By John R. Mills and Jeanne H. Yamamura for some interesting case studies. They use the inverse as if it were interest coverage, but I find it more intuitive to express interest as a fraction of pre-debt service operating cash flow (OCF), because I can equate it to a personal situation. If a company has a large percentage of outflow to servicing debt, what is left over to further expansion, pay dividends, or make profits?

Earnings Quality Metrics

Several of the ratios I look at concerning “earnings quality” relate to the “accrual anomaly,” which, by the way, is international (PDF link).

The purpose of this paper is to investigate the existence of the accrual anomaly in international equity markets. I find significant abnormal returns to total accrual hedge portfolios in 15 of the 17 countries examined. Based on these results, I conclude that the accrual anomaly does exist in non-U.S. markets and it is a global phenomenon. I next examine whether the accrual anomaly appears to be driven by a common underlying factor(s) internationally. I find that the factors influencing the accrual anomaly differ substantially across markets due to (1) the effect of managerial discretion, (2) analyst following, and (3) ownership structure. All of these factors contribute to extremely low cross-country correlations in accrual returns, casting doubt on whether accrual-related returns are due to a global systematic risk factor or common information captured by accruals across countries.

© 2005 by Ryan LaFond.
All rights reserved. Short sections of text, not to exceed two paragraphs, may be quoted without explicit permission, provided that full credit including © notice is given to the source.

Accruals are a robust measure of earnings quality that can be used to segment the universe of stocks to produce abnormal returns.

I lifted the Earnings Quality metric that I like best from an accountant’s publication targeted for auditors, and it really loses some usefulness when the company is losing money. Sum net cash from operations, income taxes paid, and interest payments. Divide that total by the sum of net income, income taxes paid, and interest payments. In a company with income, where that income is generated by operations, this number should higher than 1.00. A company that generates net income with an Earnings Quality of lower than 1.00 is using their accruals creatively, booking financing cash as income, or channel stuffing, none of which is a good thing [except possibly for financing cash in some financial companies].

Cash Generating Power is the OCF divided by the sum of OCF and Net Cash from Financing Activities (minus “Other Financing Charges”). This is a useful check of the company’s ability to generate cash through operations, and part of its usefulness is that I only need to look up the Cash Flow Statement to calculate it. Again, I like numbers that are higher than 1.00 on a consistent basis, occasional dips are viewed differently than a constant low number. Delta Air Lines (DAL) had a number under 0.33 for three consecutive years as of year-end 2003.

Reliance on Financing Cash takes Net Cash from Financing Activities (minus “Other Financing Charges”) and divides it by Total Assets. This metric requires both the Balance Sheet and the Cash Flow Statement to calculate. I lifted it from a research paper [link lost, sorry!] that documented the “anomaly” that, when companies are segmented into deciles based on this statistic, those with high Reliance on Financing Cash under-performed and those with a low statistic over-performed. I’ve come to have a poor opinion of stock buybacks in recent months, so I’ve started to exclude cash outflow from stock buybacks when making this calculation.

Conclusion

I personally tend to think of these metrics as scorecards for management, my window into how well the company is run. Wearing my value hat, I want to buy companies that have good management as measured by objective results, and I want to buy them at a discounted price. Wearing my technical hat, I want to buy them when they’re no longer falling knives. But I digress. The point of fundamental analysis for solvency and earnings quality is to eliminate or mitigate company-specific risk from holding an equity position for a long term.