The philosophy underlying the work at Napali Research is a combination of traditional value investing, the unprecedented availability of data and computational power, and psychology.

Stock is Ownership

We start with the axiom that a share of stock represents partial ownership of a business, as espoused by history’s most successful investors such as Benjamin Graham, Warren Buffett, Joel Greenblatt, Walter Schloss, and many others. A share has a value that can often be estimated to a rough degree by conservatively analyzing the business.

At the same time, many factors, frequently psychological in nature, affect the current price of that share. When there is a wide mismatch between value and price, there is an opportunity. This philosophy works equally for buying and selling, long or short.

Therefore our work concentrates on finding ways to assess the value of a share in the context of screening thousands of companies. Many valuation methods are used in the financial industry for different purposes and for different types of companies. How do we pick an appropriate valuation method?


We are big fans of an evolutionary model of the economy and business (an outstanding resource is The Origin of Wealth by Eric D. Beinhocker). This model suggests three useful categories of companies for our investment screening purposes:

  • Stalwarts: Only a tiny handful of businesses shows long-term competitive advantages and business predictability. These are companies such as GE, Johnson & Johnson, Berkshire Hathaway as a few examples. Limiting ourselves only to these can lead to good but unexceptional investment returns unless these companies can be bought at unusually low prices. However, risk is generally low.
  • Shooting Star: By far most companies come and go as a few good ideas propel them to success, but the inability to follow up with more successful products eventually leads to failure.
  • Scrappy Survivors: There is a small but significant group of companies that continues on a bumpy road over the years, doing well for some time, slipping up or being caught by a change in their economic environment, but later recovering with new products, in cycles on the order of 5 years. According to work by Wiggins and Ruefli as cited by Beinhocker, about 1% of companies are in this category, or about 100 in the current SI Pro database, and this fraction appears to be increasing slowly over time.

We would like to be able to identify companies in all three of these categories and be able to value them and assess their risk to a reasonable degree. Under the right circumstances, a company in any of these categories can be a successful investment. (Of course, there is probably a fourth category which contains companies that never really create any value at all. We will try to avoid those entirely.)

Categorizing a company is the first thing to do. Fundamentals over the longest available time period sets a background, and against that background, recent fundamentals may help us find cases where a company is currently moving up or down the “food chain.” Assessing the company’s history of value creation, share dilution, debt management, etc., should help us assess risk.

The Role of Psychology

Finally, when we decide to buy or sell has a large impact on total annualized returns. Some companies are, for whatever reason, simply permanently underpriced, and buying cheaply if we can’t sell at a higher price later does us no good. We want stocks that are currently underappreciated, but not permanently thrown out with the bath water either. A little bit of technical analysis helps us focus on companies that are being noticed by other investors. Many studies have shown, for example, that simple momentum, whose roots lie in human psychology, is a very strong predictive factor.

No In-Depth Analysis

While any of us may (and should) do further in-depth and detailed analysis of a company, generally we do not publish such analysis here. The variation among investors in their interest, abilities, specific knowledge areas, time, access to data, and much more, makes it difficult to provide useful in-depth analysis.

Our focus is on screening large numbers of companies for specific characteristics, and our measures of success generally revolve around how well our approaches do on average, not for any one specific screen result. This distinction is key.

How Do We Measure Success?

Virtually all traditional methods of evaluating investment performance such as Sharpe Ratio, Alpha, Beta, etc., are based on Modern Portfolio Theory and its offshoots. We take the healthy stance of thinking that just about all of that is silly, and has been proven many times over not to work (this is based on both faulty assumptions underlying the mathematics, and the inability of the theories to predict new events correctly; in any scientific field MPT would have been rejected out of hand decades ago). In addition, quantifying something as complex as an investment strategy by one or two numbers is certainly folly.

Instead, we develop or use other existing methods to evaluate the results of data or strategies we present that are more sound for the purposes we want to achieve. Most of the time these will take the form of charts which are a bit more complex to understand at first, but convey greatly more useful information.

Is This Buy and Hold? Trading? Active Investing?

We don’t try to adhere to any labels at all. An investment makes sense when price and value diverge, and it stops making sense when that is no longer true. Sometimes divergences narrow over very short periods, and sometimes they take years. In our opinion, there is little point in putting a specific label or time frame on the approaches we favor. We will use solid analysis of the data to determine what we believe are good investment approaches. We provide a great deal of data to readers of this site so they can make up their own minds what works.

Macro Economic Factors

We do not attempt to link macro economic factors to stock selection or other decisions. However, in many cases our focus on business fundamentals implicitly incorporates macro economic factors. For example, very high interest rates may affect a company’s ability to service its debt, which appears as a growing interest expense. Or a sudden industry slowdown may balloon receivables or inventory, causing low or negative cash from operations.

While macro economic news has dominated headlines for much of 2008 and 2009 so far, we believe that following these factors into specific stock selection serves little useful purpose in our approach. Some companies in the most badly affected industries will suddenly shine because they have more cash on hand, or low debt, or a product line with unusually good value against competitors’ offerings, or any of dozens of other factors. In other words, we are industry agnostic at all times.

This is not to say that macro economic factors are not useful, just not useful to us. Others who are more talented at understanding them can very likely make good use of the information.

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