By Joseph Hogue, CFA
This is the first of twenty articles written exploring the myths in popular investing as exposed in Michael Dever’s new book, “Jackass Investing.” In the book, Dever uses experience from three decades of hedge fund management to explore how the conventional wisdom in investing and portfolio management preaches little more than gambling.
Having poured over the Chartered Financial Analyst curriculum for the last three years, combined with experience in real estate development and finance, I felt pretty confident in my understanding of how investments work and best practices in portfolio construction. As I started reading through the introduction and first chapters of Jackass Investing, I found myself pushing back against the author’s rejection of the conventional wisdom. Then I thought back to how well the conventional wisdom had helped my portfolio over the last ten years and decided to open my mind a little. While I don’t agree with all the ideas in the book, it has helped to clarify what are actually sound practices and those ideas that I have clung to simply because it was ‘common’ knowledge. Over the course of this series, you will surely not agree with every concept as well, but hopefully it will help you develop your own strategy and not be dependent on what everyone else is doing.
The book is built around a few key ideas. Each chapter is written around a common ‘myth’ in investment management supported by the conventional wisdom. The author shows how these myths destroy portfolio value and how investors can adopt strategies that will increase returns and create true portfolio diversification. These strategies are based on knowledge of ‘return drivers’, a central concept in the book. The return for all investments is influenced by their respective return driver, or the dominant force behind its value. These return drivers can be fundamental or technical influences, but investors must understand the dominant return driver underlying each of their investments.
Once the dominant return drivers are understood, the investor can develop a trading strategy around it and the baseline conditions within the market. When multiple trading strategies, developed around different return drivers, are combined in a portfolio the resulting portfolio is much more highly diversified relative to what the conventional wisdom holds as diversification. Available with the book and on the author’s website, www.jackassinvesting.com, are 13 action strategies to help the investor apply the concepts in their own portfolio. Through this series, we’ll look at some of the action strategies as well as develop a few of our own, but because of time and length constraints, we won’t be able to cover every concept or action strategy from the book.
The book begins with myth #1, “Stocks Provide an Intrinsic Return,” and some sobering historical references to the collapse of financial markets. We are reminded of Germany, Russia, Argentina, and Peru and how the norm across time has been for the destruction of wealth through financial market disintegration rather than the coincidental experience in the United States’ financial system. The author is not warning of the collapse of the American system, but showing how in each of these systems a single event or condition acted to destroy wealth within investors’ portfolios. The idea creates the need for a portfolio of distinct strategies that each benefit from different return drivers, so that when conditions change, no one return driver will dominate portfolio value.
Using regression analysis to determine the drivers of returns in the S&P500 Total Return Index over various periods, the author shows that two primary return drivers explain 93% of the variance in the index over each holding period. These drivers are the aggregate earnings growth of companies and the multiple that investors are willing to pay for these earnings, referred to as the price-to-earnings multiple. This shouldn’t be anything shocking to investors, but what will surprise you is the holding period at which each driver is dominant. The chart below shows the S&P500 Total Return Index source of returns by each driver and by holding periods. The analysis shows that in any period of less than ten years, the P/E multiple accounted for more than 75% of price changes while earnings growth accounted for a much smaller influence on returns. So not only is the market driven by just two return drivers, even in the longest holding periods the influence on returns is largely a factor of investor enthusiasm for buying stocks. This shows that, as stated in the book, “what appears to be an ‘intrinsic’ return of the ‘market’ is simply the aggregate result of corporate earnings coupled with the enthusiasm people have for buying stocks,” and that investor sentiment is a dominant factor in all but the longest holding periods.
There are two important ideas within the chapter. The most obvious is the result of analyzing the returns on the market index, as shown in the chart. If earnings growth only significantly affects returns over periods of longer than ten years, is it complete folly to analyze fundamentals? I wouldn’t think so. Remember, the author is promoting the development of a series of trading strategies around several return drivers. As a return driver, earnings growth could be the basis for one strategy; in fact it is the foundation for momentum strategies. Trying to forecast the earnings growth of a company over the long-term (+10 years) however would be difficult at best and not as practical a strategy. In the example below, we will use the action step from the author’s website to implement a shorter-term strategy using the Piotroski score.
The other important idea nested within the chapter, and really the basis behind the book, is the investor’s need not only to understand the underlying return drivers to an investment but that all return drivers have an accompanying time period for which they are relevant. Even if the investor had realized earnings as a return driver to equity prices, if they failed to understand the time component, any trading strategy built off the driver would probably not perform well.
The strategy outlined in the book’s Action Section for this chapter is built around the fact that investor sentiment, or the P/E multiple, is the dominant return driver for stocks within most holding periods. The strategy analyzes companies that have been rejected in the market and consequently have seen their stock prices fall precipitously. If this sounds familiar, it is the premise behind value investing. What the strategy brings to the table is the methodology to distinguish the stocks that are truly value plays and not merely value traps. Value trap stocks are cheap for a reason, their financial stability and future performance is tenuous. Value stocks, on the other hand, are cheap because of that oft-fickle investor sentiment.
The strategy is based on the Piotroski scoring method, named after the University of Chicago Professor, Joseph Piotroski. Piotroski argued that because value stocks are often distressed companies, investors needed a way to distinguish between companies with good future potential and those more likely to be value traps. The scoring is built on a series of nine criteria for evaluating a firm’s financial strength. Over a 20-year test period, those stocks scoring highest outperformed a portfolio of all value stocks by about 7.5% annually. Additionally, those stocks scoring lowest were up to five times more likely to file bankruptcy or de-list their shares. The strategy limits the universe of possible investments to those in the bottom 20% on a price-to-book basis. These are often the stocks that have been beaten down by company events and investor sentiment. The strategy then includes only those stocks that score nine points, satisfying all criteria. This can be expanded to those scoring across eight criteria, but would change the results of the strategy by bringing in potentially weaker companies.
The criteria used in the method and scoring system are fairly straight-forward. One point is assigned for each of the criteria met by the company’s financials.
- Positive prior year net income.
- Positive prior year operating cash flow: This is a better gauge of income and less susceptible to management manipulation.
- Current year return-on-assets is greater than prior year: A good measure of profitability.
- Prior year operating cash flow exceeds net income: A warning sign of income statement manipulation by management is net income that significantly exceeds operating cash flow. Managers can manipulate accounts to show higher net income, but it is much harder to manipulate actual cash flows.
- Ratio of long-term debt to assets is lower than prior year: Lower liabilities relative to assets is a sign of improving financial stability.
- Increasing current ratio (current assets divided by current liabilities): This is a signal of improving access to working capital and solvency.
- Number of shares outstanding is equal or lower than prior year: An increasing number of shares outstanding means that prior investments are being diluted.
- Current year gross margin exceeds prior year: Margins measure the company’s competitive position.
- Percentage increase in sales exceeds percentage increase in total assets: An improving asset turnover means the company is improving productivity.
I can’t help but feel some sense of self-satisfaction at seeing the Piotroski system included in the book’s trading strategies. Two weeks ago, in an article using the movie “Moneyball” as an analogy, I posted an article outlining the method. In it I highlighted DR Horton (NYSE:DHI) and Dell (NASDAQ:DELL) as companies scoring well with Big Lots (NYSE:BIG) and Eastman Kodak (EK) as potential short plays. In fact, I noted that Eastman Kodak had a negative book value when goodwill is backed out and scored a zero on the Piotroski scale. Over the last two weeks, to Tuesday’s market, the long/short strategy in the four stocks has returned 42.5%! The long in Dell has outperformed the general market, while the long in DR Horton has lagged. The short in Big Lots has lagged the performance in the general market by about 3% while the short in Eastman Kodak has paid off big time with a 53% return due to bankruptcy concerns. These results would not be typical of a two week performance and the expansion to more than four stocks would smooth results from any one investment, but it is nice when a call turns out to be a big winner (so I am exercising my right to gloat over this one).
Using the strategy, an investor would normally want to select about ten stocks for long or short positions. The author launched a market neutral fund in 2001 and incorporated the strategy into the portfolio. The tested results of the Piotroski strategy alone produced returns on an annualized basis of 29% to 2009 and an average annual return of 48% by the end of 2010. The returns include a cost of 4% each year to account for transaction costs in trading.
This is certainly not the only trading strategy an investor could build around investor sentiment. The field of behavioral finance offers insight into a range of emotions that investors use to erroneously guide their investment choices. Additionally, the market offers just as many indicators that can be used to monitor sentiment as a return driver. We’ll explore some of these indicators in future articles within the series. Future articles in the series will also explore the myth that you cannot time the market, and that by staying invested to take advantage of the best ten days of market returns will lose your money.
Until then, I welcome your comments.
Disclosure: I have no positions in any stocks mentioned, and no plans to initiate any positions within the next 72 hours.
Additional disclosure: This series has been written on a contracted basis with the book's author. The opinions expressed in the article are those of Efficient Alpha and not necessarily those of the book's author. Efficient Alpha has been contracted to describe strategies and concepts used within the book but not to promote or recommend any strategies, the author, or the author's services.