Price, The Conscious Investor

John Price, author of The Conscious Investor: Profiting from the Timeless Value Approach (Wiley, 2011), began his career as a research mathematician and for thirty-five years taught math, physics, and finance at universities around the world. He then morphed into an entrepreneur, developing stock screening software that emulates Warren Buffett’s investing strategies. And, as is evident from this book, he didn’t neglect his writing skills. He proceeds with the analytical precision of a mathematician but with the facility and clarity of a careful wordsmith.

Price describes over twenty methods of valuation. He explains the circumstances in which each method is most appropriate. He also evaluates each method’s strengths and weaknesses.

Here I am going to confine myself to describing the screen that underlies Price’s own investing system. He focuses on earnings forecasts, offering objective methods in place of the strategies of analysts, which are tainted with behavioral biases. Critically, he screens to find companies that are actually amenable to growth forecasts. They share three characteristics. “The first two, stable growth in earnings and stable return on equity, are based on histories of financial data taken from the financial statements. The third one, strong economic moat, is based on the ability of the company to protect itself from competitors.” (p. 292) Since many readers will be familiar with Warren Buffett’s notion of moats, I will discuss only the first two characteristics and how to measure them.

Price developed a proprietary function called STAEGR which “measures the stability or consistency of the growth of historical earnings per share from year to year, expressed as a percentage in the range of 0 to 100 percent. … STAEGR of 100 percent signifies complete stability, meaning that the data is changing by exactly the same percentage each year. The function has the feature of adjusting for data that could overly distort the result, such as one-off extreme data points, negative data, and data near zero. It also puts more emphasis on recent data.” This function is “independent of the actual growth. This means that whether a company has high or low stability of earnings is independent of whether the earnings are growing or contracting. In this way the two measures, stability and growth, complement each other in describing qualities of historical earnings.” (p. 294) (more…)

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