In a wide-ranging interview with Barry Ritholtz on Bloomberg View, quantitative investing guru James O’Shaughnessy recently talked about why human beings are such inferior prognosticators compared to computer models, what that means for investors, why stocks may well be safer than bonds over the long run, and why holding period duration is so critical.
You don’t need complicated strategies to beat the market. That’s what James O’Shaughnessy says in a recent column discussing shareholder yield (dividend yield plus buyback yield).
Investors are continually attracted tho “glamour stocks” — those popular, flashy picks that are always being talked about. But quantitative investing guru James O’Shaughnessy says history shows those exciting stocks usually lead to big trouble.
Which valuation metric is best? In his latest for Canada’s Globe and Mail, Validea CEO John Reese looks at just that question, weighing the pros and cons of several popular metrics.
Every other issue of the Validea Hot List newsletter examines in detail one of John Reese’s computerized Guru Strategies. This latest issue looks at the James O’Shaughnessy-inspired strategy, which has averaged annual returns of 9.8% since its July 2003 inception vs. 6.0% for the S&P 500. Below is an excerpt from the newsletter, along with several top-scoring stock ideas from the O’Shaughnessy-based investment strategy.
In his bi-weekly Hot List newsletter, Validea CEO John Reese offers his take on the markets and investment strategy. In the latest issue, John looks at new data from renowned researchers Kenneth French and Eugene Fama, and the implications that the data has for value investors.
Excerpted from the May 9, 2014 issue of the Validea Hot List newsletter
Over the long-term, small-cap value stocks have well outperformed larger growth stocks. For decades, that notion has been a pretty widely known one in the investing world, thanks in large part to the research of highly regarded finance professors Kenneth French and Eugene Fama. Fama and French’s research found, for example, that from 1927-2009, small value stocks beat large growth stocks by an average of more than five percentage points annually. In addition, large value stocks beat large growth stocks and small growth stocks by about two percentage points each annually.
That data would seem to indicate that simply buying stocks with low price/book ratios — the metric Fama and French used to assess value — should be a good investment strategy. And many analysts have supported the idea of such a strategy by contending that the market must reward investors who buy value stocks (which are often in some kind of distress) for taking on additional risk — that, at least, is what efficient market hypothesis supporters usually say.
But new data — from none other than Fama and French themselves — seems to turn that notion on its head. In a working paper that was released last year, Fama and French analyzed historical stock returns again, this time adding in two new factors: profitability and investment intensity (the level of capital investment a company makes). While the paper didn’t get a whole lot of attention, one of its initial findings appears to be quite significant: The profitability and investment factors made redundant the value factor. “In other words, value stocks — defined as those with low price/book — only beat growth stocks because they historically tended to be more profitable and less voracious users of capital,” wrote Morningstar’s Samuel Lee in a recent piece discussing Fama and French’s new paper.
The redundancy of the value factor might seem to be contrary to what many of the value-focused gurus I follow preach. In reality, the takeaways from French and Fama’s new data fit quite well in a several key ways with the gurus’ teachings, and I think they are well worth touching on.
First, it’s important to note that the value gauge French and Fama use is the price/book ratio, which is not one of the more used gauges by the gurus. In fact, in a research report earlier this year, James O’Shaughnessy’s firm wrote that “Despite its popularity, we do not use price-to-book in [the] OSAM Value [composite] because of several problems with the factor.” The price/book ratio “consistently has one of the lowest annualized returns of all value factors,” O’Shaughnessy Asset Management said in the paper. “Also, in half of the time periods shown, price-to-book underperforms the market.” While that particular paper was looking at the Canadian stock market, OSAM said the issue was not isolated to Canada. “In the U.S., price-to-book has been a very inconsistent value ratio with prolonged periods of underperformance,” the group said. “From 1927 to 1963 the cheapest ten percent of stocks by price-to-book underperformed the U.S. market by an annualized 205 bps; and over the next 36 years by more than 200 bps.” O’Shaughnessy, for the record, initially found the price/sales ratio to be the best value factor — that’s what I use in my O’Shaughnessy-based growth model, which has been one of my better performers over the long haul. (Today O’Shaughnessy actually uses a “value composite” that includes several value gauges, similar, in effect, to what the Hot List does.)
What I find interesting about OSAM’s work in relation to Fama and French’s work is that in almost all cases, the gurus upon whom I base my strategies used valuation metrics that focused on earnings, sales, or cash flow — in other words, the concept of profitability was at work within the value metrics. The price/book ratio, in contrast, is based on the value of the company’s assets, not its ability to generate profits — and Wall Street is less concerned with what a company already is than with what it could grow into in the future. It’s also worth noting that of the three guru-inspired models I run that do use the price/book ratio, two of them (the David Dreman and Benjamin Graham approaches) use other value metrics (the price/earnings, price/cash flow and price/dividend ratios for Dreman, and the P/E for Graham) as well. The one strategy that uses price/book (actually its inverse, the book/market ratio) as its sole valuation gauge — the Joseph Piotroski-based approach — includes among its other variables the return on assets rate and gross profit margin, both of which get at a firm’s profitability, as well as cash flow from operations, which is designed to eliminate firms that are burning through cash. Those three variables jive quite well with the profitability and investment factors that French and Fama added to their analysis in their paper.
Then there’s Warren Buffett. Of all of the guru-inspired strategies I use, the Buffett-based approach probably has the least stringent valuation measure — it simply requires that the company’s earnings yield be higher than the yield on long-term treasury bonds. It focuses a great deal on earnings persistence, return on equity, return on retained earnings, and return on capital — profitability. In addition, it looks for companies that have good free cash flows, the idea being that that will weed out firms that require a high amount of capital investment. High profitability, low investment requirements — that’s exactly what French and Fama’s study found made the value factor redundant.
So what does all this mean? Does it mean that value no longer matters? Most definitely not, in my opinion. Price is always important when you are buying anything, stocks included. As O’Shaughnessy’s research has shown, a number of non-price/book ratio valuation metrics have been great ways to identify winning stocks throughout history (metrics like the Price/sales and price/earnings ratios).
Just as importantly, I think French and Fama’s new research highlights the importance of using a well-rounded strategy that looks at a company and its shares from a number of different angles. Profitability, balance sheet, valuation — you should consider all of those factors when analyzing a stock. As Kenneth Fisher, another of the gurus I follow, wrote, “Never assume you have found the one silver bullet.” My Guru Strategies do not look for a silver bullet. Most of the strategies use between seven and 10 different variables; the Motley Fool-based approach uses no fewer than 17. And those are just individual models. With a consensus approach like the Hot List, which gets input from all 12 of my models, you’re talking about putting a stock through dozens and dozens of financial and fundamental tests. Those that make the grade are thus some of the most fundamentally sound stocks in the market, showing strength across a number of different levels. Take Hot List newcomer NetEase, which is being added to the portfolio today. The $9-billion-market-cap tech firm has grown earnings at a 24% pace over the long term, and much more rapidly in the most recent quarter. It has no long-term debt and a 5.4 current ratio, indicating a very strong balance sheet, and it has been extremely profitable, averaging a 10-year return on equity north of 28% and a return on retained earnings over that period of more than 20%. All of that, and it trades for about 12 times earnings and has a free cash flow yield of close to 8%.
Of course that’s no guarantee that the stock will be a huge winner for the portfolio. But over the long term, stocks with those kind of well-rounded fundamentals and financials tend to perform quite well. By investing in baskets of stocks like those, we stack the odds greatly in our favor over the long haul. The proof is in the pudding — the Hot List’s stellar long-term track record is in large part due to its deep, thorough fundamental analysis of companies and their shares. Moving forward, I’m confident that this approach will continue to pay off with returns well ahead of the market average.
Often times, investors overlook a key part of portfolio management when buying and selling stocks: tax impact. But in a recent research report, quantitative investing guru James O’Shaughnessy’s firm offers some tips for how to minimize Uncle Sam’s impact on your portfolio.