James O’Shaughnessy (Chairman and CEO of O’Shaughnessy Asset Management) introduces his 2011 book, What Works on Wall Street (Fourth Edition): the Classic Guide to the Best-Performing Investment Strategies of All Time, by stating: “…investors seem programmed by nature to fail at investing, forever chasing the asset class that has turned in the best performance recently and heavily discounting anything that occurred more than three to five years ago. The whole purpose of What Works on Wall Street is to dissuade investors from that course of action. Only the fullness of time shows which investment strategies are the best long-term performers, and this is doubly true after the last decade’s sorry performance. …We will make the case that equities–particularly those selected using the best long-term strategies–will go on to be the best performing assets over the next 10 and 20 years. …The fourth edition of What Works on Wall Street continues to offer readers access to long-term studies of Wall Street’s most effective investment strategies.” He uses overlapping portfolios formed monthly and rebalanced annually for all tests. Using broad sets of data on U.S. firms/stocks from either 1963 or 1926 through 2009 to extend and expand his prior quantitative analyses, he concludes that:
From Chapter 1, “Stock Investment Strategies: Different Methods, Similar Goals” (Page 4): “…all strategies have performance cycles in which they over- and underperform their relevant benchmarks. The key to outstanding long-term performance is to find strategies that have the highest base rate [frequency with which they beat their benchmark]…and then stick with that strategy, even when it’s underperforming other strategies and benchmarks.”
From Chapter 2, “The Unreliable Experts: Getting in the Way of Outstanding Performance” (Page 21): “The most ironclad rule I have been able to find studying masses of data on the stock market…is the idea of reversion to the mean. …The same holds true at the strategy level.”
From Chapter 3, “The Persistence of Irrationality: How Common Mistakes Create Tremendous Opportunity” (Page 40): “To break from our all too human tendencies to avoid losses even when it is disadvantageous to do so, chase performance, and perceive patterns where there are none, we must find an investment strategy that removes subjective, human decision making from the process and relies instead on smart, empirically proven systematic strategies. …we can become wise by realizing just how unwise we truly are.”
From Chapter 4, “Rules of the Game” (Pages 45, 59): “My goal in this book is to bring a more methodical, scientific method to stock market decisions and portfolio construction. To do this, I have tried to stay true to those scientific rules that distinguish a method from a less rigorous model. …Transaction costs and bid/ask spreads are not included. Each reader faces different transaction costs. …you should subtract as much as 1 percent of gains [to account for bid/ask spreads]…for the data from the 1960s through the 1980s… Currently, our traders at O’Shaughnessy Capital Management have found that bid/ask spreads on small-cap trades average 0.50 percent and 0.15 percent on large-cap trades.”
Chapters 5 through 15 and 17 through 20 examine the historical performance of 16 firm characteristics: market capitalization, price-to-earnings ratio, EBITDA to enterprise value, price-to-cash flow ratio, price-to-sales ratio, price-to-book value, dividend yield, buyback yield, shareholder yield (dividend plus buyback), accounting ratios, composite value factor, one-year earnings per share percentage change, profit margin, return on equity, and relative price strength (momentum).
From Chapter 16, “The Value of Value Factors” (Page 355): “Value strategies work, rewarding patient investors who stick with them through bull and bear markets and through bubble and burst.”
From Chapter 21, “Using Multifactor Models to Improve Performance” (Page 470): “…you can do vastly better than a passive investment…by using more than one factor to select a portfolio of stocks. …Investors are best served by buying stocks that have jumped a series of hurdles rather than just one.”
From Chapter 22, “Dissecting the Market Leaders Universe: The Ratios That Add the Most Value” (Page 484): “…focusing on the most expensive popular stocks delivers the worst overall returns, while concentrating on the cheapest stocks delivers the best returns. In addition, the strategies that provided the best overall compound returns also did so with the highest degree of consistency.”
From Chapter 23, “Dissecting the Small Stocks Universe: The Ratios That Add the Most Value” (Page 499): “…many of the commonly successful strategies like buying stocks with the lowest price-to-earnings, price-to-cash flow or price-to-sales ratios significantly enhanced the returns of a small capitalization strategy. The value composites proved to be excellent measures of the health of small-cap stocks… The best-performing strategies also perform consistently… There is a red flag here, however. Even the best strategies suffered declines of 50 percent or more…”
From Chapter 24, “Sector Analysis” (Page 545): “…what works in the All Stocks universe also works quite well at the sector level. …what we should avoid investing in at the All Stocks universe level should also be avoided at the sector level.”
From Chapter 25, “Searching for the Ideal Growth Strategy” (Page 567): “One of the very best ways to use price momentum is to marry it to a value constraint [composited value factors]. …six-month price appreciation is a more effective final momentum filter than 12-month price appreciation.”
From Chapter 26, “Searching for the Ideal Value Stock Investment Strategy” (Page 578): “While I have added the growth requirement that three- and six-month price appreciation be greater than average, …the return differences are very small between the [value] strategy with that price momentum and without it.”
From Chapter 27, “Uniting the Best from Growth and Value” (Page 581): “One of the consistent themes of my research is the efficacy of uniting value and growth factors. Doing so allows you to smooth out the jags of a pure momentum strategy by tempering it with the best of value.”
From Chapter 28, “Ranking the Strategies” (Pages 595-596): “Each of the ten best-performing strategies…includes relative strength criteria. Yet they are always tied to another factor, usually one requiring the stocks to be modestly priced in terms of how much you are paying for every dollar of sales, earnings, book value, or a combination of value factors. Most of the 10 worst-performing strategies buy stocks that investors have bid to unsustainable prices, giving them astronomical price-to-earnings, price-to-book, price-to-sales, or price-to cash flow ratios, or are last year’s biggest losers.”
In summary, investors will likely find What Works on Wall Street useful as a broad survey of the long-term historical performance of a large number of U.S. stock portfolios formed based on single and composite/combined indicators, converging to a few value-momentum strategies that work best on a gross basis.
The book presents detailed results via a large number of figures and tables. It cites a reasonably wide range of supporting research, but citations concentrate in the late 1980s and early 1990s.
Cautions regarding findings include:
- The author focuses on portfolios of U.S.-listed equities (for which long-term data is most robust). It does not address diversification across global markets or different asset classes.
- While the author takes steps to mitigate data snooping bias, there are so many characteristics/combinations tested on the same data sets in search of best portfolio strategies that discrimination among strategies/variations may derive materially from luck.
- As acknowledged by the author, return calculations are gross of trading frictions for initial portfolio formation and annual rebalancing. The discussion in Chapter 4 on how the reader should correct for trading frictions (reference “Trading Frictions Over the Long Run”) seems unsatisfying, as follows:
- There may be interactions between level of trading frictions and return anomalies, such that anomaly existence depends materially on excluding frictions. For example, small-capitalization stocks generally carry higher trading frictions than large-capitalization stocks.
- Because different strategies may have different levels of portfolio turnover, including trading frictions may affect the performance ranking of the strategies. For example, momentum strategies generally involve higher portfolio turnover than value strategies.
- For individuals forming their own portfolios, holding enough stocks to exploit historical statistics reliably means relatively small positions with attendant high trading frictions.
