Early value metrics were dependent on information that was easy to find. Price/Earnings and Price/Book came out of that era. Both did a decent job of capturing value’s outperformance.

But as financial statements became more widely available, it spawned other value metrics that performed even better. Cash flow-based value metrics are a good example of this.

The cash flow metrics tested below are built using market cap (enterprise value metrics will be next). All tests were run on the following assumptions:

• No OTC stocks or ADRs.
• No stocks trading below $1/share.
• No low-volume stocks.
• Market cap greater than $50 million.
• Deciles are equal-weighted, as is the Universe.
• Benchmarked against the Russel 3000 total return index (It’s a cap-weighted benchmark. The universe of qualifying stocks is included for a better comparison).
• Stocks are bought on January 1st of each year, held for one year, then sold. Rolling backtests are done at four-week intervals with a similar one-year holding period.
• Assume all metrics are based on trailing twelve months (TTM) unless indicated.
• Data are from 2000 to 2020, sourced from Portfolio123.

For the metrics below, higher is cheaper and lower is more expensive. Each one follows a similar pattern where the cheapest decile outperforms the most expensive by a wide margin. The cheapest decile also outperforms the universe and the benchmark. Though, some do a better job of it than others. Continue Reading…

Markets have a way of luring investors into doing things they shouldn’t. Be it innovative new products or promises of high returns, there’s always something to tempt an investor’s resolve. And it ends up being costly. As with many things in life, avoiding certain things often lead to the greatest results.

I was reminded of this while browsing Another Investor’s Anthology. Part of its collection is a chapter from an outdated book by Claude Rosenberg, Jr. It’s a list of investing rules that are more likely to cost you money than make it in the long run. So investing don’ts. His list pertains to stocks specifically but is true for most investments.

Here’s the thing. None of the rules are new. They’ve been repeated so many times that they should sound obvious. Which is the point.

Common investing mistakes are common because it’s so easy to fall back into the trap of making them. Sometimes we forget how it turned out the last time. Sometimes it’s a momentary lapse of judgment. Whatever the reason, hindsight reveals what we likely already knew — we never should have done it in the first place.

But that’s life. Mistakes will be made. The goal is to limit the damage. Timely reminders of the more obvious ones may save us from ourselves someday. Continue Reading…

Certain pockets of the market tend to outperform others. The classic value metrics like price-to-earnings or price-to-book were the first to be discovered back in Ben Graham’s era. Since then numerous value metrics have shown better results (we’ll get to those at later date).

Value metrics work in the long run mainly because of mean reversion and a side of behavioral bias. Investors tend to place bets based on popularity and recency bias. As Graham said, “In the short run, the market is a voting machine…”

The thinking goes like this. Companies doing well will continue to do well and companies doing poorly will continue to do poorly and nothing will change that. This works for a while until mean reversion steps in. Mean reversion is the tendency for fundamentals and stock prices to revert to a long-run average thanks to competition.

Excellent companies, with high-profit margins and growth rates, that make a ton of money, get priced with that mind but they also attract competition. That competition puts pressure on profit margins, growth rates, etc. which feeds into P/E ratios, stock prices, and more. In other words, the excellent company becomes an average company and markets eventually adjust its stock price to that reality. Continue Reading…

Wolf packs were absent from Yellowstone for 70 years. It completely changed the behavior of other animals. It removed fear from the system.

Survival for most animals means finding a balance between eating and watching for predators. Fear plays a vital role in keeping animals alive. But when you remove the top of the food chain, like wolves, the balance tilts to one side and upends the system.

Without wolves in Yellowstone, elk could eat without fear of predators. They could sit in one place and graze all day. More offspring also survived which did the same. Eventually, the number of elk grew beyond the capacity of the park. In other words, they ate and ate and ate until they ate at a faster rate than the trees and other vegetation could grow. After seven decades, they grazed the park clean of new saplings. That changed the landscape, forced other animals to change their habits (or leave for other habitats), and upended the ecosystem.

But that all changed in 1995. The reintroduction of wolves to the park forced the elk to change their behavior. They quickly learned they couldn’t sit around and eat all day. They had to move more often. They were more vigilant of predators. So they ate less and avoided higher-risk areas of the park. Things compounded from there. Continue Reading…