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Using Public Information to Find a Trading System Edge

(Guest Commentary By Bill Rempel - January 3, 2008)

Dear Subscribers and Readers,

I will be back in “full force” for this weekend's commentary, as we cover Part II of our two-part series where we attempt to identify the short and long-term trends for 2008 (Part I can be found here).

For those who had wanted to learn more about individual stocks, the art of stock selection, and model-based trading/investing, it is again time to see what one of our regular guest commentators, Bill Rempel, has to say.  Bill is a prolific writing on the stock market and individual stocks and is the author of a very active market blog at: http://billrempel.com

In this commentary, Bill is going to discuss many ways that one could obtain a trading edge – simply by utilizing public-available and documented research and anomalies and by adopting a mechanical system of trading.  Bill also argues that, contrary to what many believe, a system that is available in the public domain does not necessarily make it less likely to.  This commentary is a again fascinating read, but should only act as a starting point for one to do further research.  Without further ado, following is biography of Bill:

Bill Rempel (aka nodoodahs) is an active poster on the MarketThoughts forum as well as a few others around the web. Bill is a regular, monthly guest commentator on our website (see “A Dozen Questions to Make You a Better Trader” for his last guest commentary). Bill graduated from Caddo Magnet High School (a high school for nerds) back in 1985 and proceeded to learn the hard way when he drank his way out of a scholarship to Tulane later that year. After a few years of sweating for a living, he decided to go back to school, and graduated from LSU-Shreveport in 1995 with a Bachelors in Mathematics - all the while working the overnight shift stocking shelves in a grocery store.

Post-college, Bill has been in the P&C insurance industry as an actuary, product manager, and pricing manager. Bill and his wife Millie are amateur investors with a variety of holdings, but they prefer to buy and hold value investments. In typical "value" style, they live cheap, driving old cars and preferring to save or invest instead of buying fancy "stuff."

Disclaimer: This commentary is solely meant for education purposes and is not intended as investment advice.  Please note that the opinions expressed in this commentary are those of the individual author and do not necessarily represent the opinion of MarketThoughts LLC or its management.


Regular readers know by now that I'm a big fan of living an examined trading life, asking the questions about personal goals, tolerance for volatility, and methodology that many other traders don't seem willing to ask.  I'm also a big fan of rules-based trading, up to and including mechanical and semi-mechanical systems.  My last MarketThoughts column was aimed squarely at performing an all-around self-examination of my trading; this column is about finding trading edges to use in building a system.

From last month's column, this was question (7) what is my trading "edge?"

The objective of finding an edge demands that I find and use information that directly relates to the future movements of a company's stock price, and whose relationship is empirically documented.  Amazingly, most of the information I need is readily and publicly available!

Inside the "Accrual Anomaly is a good example paper for examining several different factors.

Accrual accounting simply means that a company is trying to match revenue and expenses to when they happen, rather than when the money is received.  A manufacturer may book revenues based on the completion percentage of a large order, rather than having all the cash come in two or three lumps, based on order placement and start/finish of production; an insurer may book a loss for a natural disaster before all payments are completed; etc.  This gives a company great latitude in the ability to smooth earnings.

The "anomaly" is that companies using accrual accounting to the benefit of higher earnings in the present quarter(s) tend to have underperforming stock prices over the next year, and vice versa.  I have typically been using the ratio of operating cash flow to net income (found on the cash flow statement) to check for this, although there are a variety of methods.

Other research includes this paper on accruals and earnings quality, and the work of John R. Mills and Jeanne H. Yamamura on various cash flow metrics.  Note that Mills & Yamamura were more focused on solvency than on stock price, but solvency risk is an important metric for longer-term traders.

These are all purely Fundamental factors mentioned thus far.  Inside the "Accrual Anomaly" also touched on the "book to market ratio" (known to most of us as Price/Book or PB) as an anomaly (a FundaTechnical factor), small cap size and listing on the Nasdaq as predictors of outperformance (both Technical factors), and various observations related to mergers and divestitures (I would call these Fundamentals).

The point I'm making here is that, if carefully read, much academic literature can provide clues to the edge that I am seeking when designing a trading system.

For example, hidden in the appendix of a paper supposedly about 130/30 funds' advantages over long-only funds was a six-factor model that, on a long-only model, significantly outperformed the Russell 1000 or the EAFE if applied internationally.  They used earnings estimates revisions (Fundamental), long-term price momentum (Technical), ratios of Price to Cash Flow, Book, and Sales (all FundaTechnical), and Share Decrease (?!?) in their model.  Returns for the long-only model were 18% annualized versus 11% annualized in domestic U.S. stocks, over the period of 1994 through 2006.  Note that this is basically just a "value" model with a momentum overlay!  I find the use of Share Decrease (representative of buybacks) more than a tad interesting.  Is it only a Technical item?  Or is it Fundamental, or related to a Fundamental?  I could make the argument that a company which can afford to buy back its own shares is probably a company that isn't relying on accrual accounting to "juice" its earnings, and certainly isn't a company reliant on cash from selling shares in order to "book" a profit.  Now, whether the buyback is internally financed or debt-financed may be a matter that needs looking into, but in aggregate, it appears to be a valid factor.

Tweedy, Browne has assembled a list of things that "work" in investing, given their "value" perspective and longer holding time.  Here is some return data for one of Tweedy's funds.

Joseph Piotroski has documented several fundamental factors that influence future stock prices, including improvements in Current Ratio and improvements in Return on Assets.

The Magic Formula, used by Joel Greenblatt, is the combination of a Fundamental (Return on Invested Capital) with a FundaTechnical (Earnings Yield, or the inverse of the Price/Earnings ratio).  You can buy his book from his site.

The MarketThoughts Forums have a multitude of links on finding methodologies that produce an edge.  Here is one thread with a collection of links, and there is an entire section of the forum devoted to research papers, articles, and speeches, many of which are related to stock market anomalies.

This is nowhere near a comprehensive list of research, and it's not intended to be.  I am simply trying to get the point across, that there are – and have been for many years – documented empirical methodologies that lead to outperformance when applied to stock trading.  Not only is the research available free (!) in many cases, even when it needs to be purchased, it is still OUT THERE waiting for me to use it!

Every once in a while, I put for the argument for using publicly documented "anomalies" to find a trading edge, and hear the myth of efficient markets writ large by those who respond,  "if a system works, then everyone will use it, and then it will stop working."  People who say that are not serious students of the market.  Indeed, Joel Greenblatt exposed the real reason why good systems will always work when he disclosed his own system - basically, good systems will always work in the long term because they can't always work in the short term, and thus never get the market inefficiencies they rely on arbitraged away. Another way of saying this is that "folks are folks," and all successful systems are dependent upon human nature, which never changes.

Ben Graham's methods have been in backtest by the AAII for several years – here's a chart of their performance.  It seems to me as if a system that was publicly disclosed in the first half of the last century is still working today; and if you read "The Intelligent Investor" you'll see that the systems described by Graham are very mechanistic in nature.

The best way to find an edge to build a system around is to start with publicly available research!

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