Michael Mauboussin and Dan Callahan recently shared a great paper, updating their work on ROIC.
"Companies that delivered high and sustained ROICs exceeded their peers in both net operating profit after taxes (NOPAT) margin and invested capital turnover".
Some highlights 🧵
1/ Making money is too modest a goal, says Mauboussin.
If that investment could have made superior returns elsewhere, the foregone profit from that alternative is an opportunity cost. As such, the opportunity should be the hurdle rate for an investment.
2/ This "dollar bill" test makes sense in theory but is not perfect because a company’s market value echoes both historic and future investments.
Due to differences in growth rates, spreads between ROIC and WACC can vary. But the market tends to reward these spreads.
3/ What is most important is ascertaining what is already priced in, and being able to anticipate revisions to those expectations.
"If you have a good estimate for ROIC and a forecast for growth, you have the ingredients to estimate free cash flows".
4/ Between 1990 and 2022, the majority of Rusell 3000 companies earned ROIC of between 5% to 10%.
The adjustments (light blue) for intangible investments tend to pull ROICs toward the average, with fewer extreme values.
5/ Over the same period, the average annual for traditional ROIC measurement is 9.5% vs 9.2% for the adjusted version.
6/ The importance of intangibles adjustment varies by industry. Some are more reliant on tangible investments, so adjusting for intangibles has a lower impact on ROIC.
Here is how ROIC differs across industries, over the period 1990 to 2022, using the traditional method.
7/ And here is the same group of industries, but with adjustment.
The adjustment once again demonstrates the degree of dispersion and displays fewer extreme values.
8/ Stocks with high ROIC will not deliver attractive returns if they fail to exceed expectations.
"The reason is that a stock price reflects the market’s expectations about a company’s future financial results. Excess returns are the result of revisions in expectations".
9/ Knowing how companies generate high ROIC can inform competitive analysis.
"A relatively high margin indicates a differentiation strategy. Relatively high capital turnover is consistent with a strategy of cost leadership".
10/ "ROIC provides a glimpse into the generic strategies that companies pursue to create value [and] companies that pursue a differentiation strategy have been more represented among companies delivering superior returns over time".
11/ Time horizon influences what is important to investors.
"Investors with a short-term horizon tend to focus on near-term financial metrics such as sales and earnings. Investors with a long-term horizon focus on competitive advantage and the size of the market opportunity".
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In 1991, Seth Klarman wrote a book, Margin of Safety, that is rumoured to have printed only a few thousand copies.
No longer in print, but packed with superb insights, Klarman once said he
“endeavoured to make the book timeless".
🧵 Our 9 favourite lessons:
1. The 80/20 rule:
"The first 80 percent of the available information is gathered in the first 20 percent of the time spent. The value of in-depth fundamental analysis is subject to diminishing marginal returns".
2. The down market test:
"A market downturn is the true test of an investment philosophy. Securities that have performed well in a strong market are usually those for which investors have had the highest expectations".
In several of Peter Lynch's old books, he shared a charting technique later dubbed the "Peter Lynch Chart".
"A quick way to tell if a stock is overpriced is to compare the price line to the earnings line".
A quick guide to producing these charts in Koyfin 👇
1) These charts are sometimes called 'Fair Value' chart lines, where you plot a range of constant valuation multiples to visualise where the company trades in relation to those bands.
Example: Apple trades at 27x earnings with a 10Y mean of 21.3x earnings.
2) To reproduce this, we use the multiplier transformation in Koyfin, allowing you to multiply or divide the underlying data of a multiple.
Open up the historical graph, add a ticker and decide which multiple you wish to plot (here, we use price/sales).
Mauboussin & Callahan just shared a paper on the psychology of expected value.
"How often you are right is not all that matters. What is vital is how much money you make when you are right versus how much you lose when you are wrong".
🧵 Our 8 favourite highlights:
1/ Most investors misprice extreme outcomes - markets often overpay for "lottery" stocks (low probability, high payoff) and underprice extreme downside risks.
"Many outcomes investors call black swans are really gray swans—known unknowns".
2/ Volatility kills compounding. Your long-term returns aren’t the average of your annual returns. Volatility drag means big drawdowns hurt wealth more than most realize.
Example: The GraniteShares 3x Long MicroStrategy ETF lost money in 2024 despite its underlying stock rising 358%.