False knowledge fields: A definition
George Bernard Shaw once wrote "Beware of false knowledge; it is more dangerous than ignorance." Rather than write about Warren Buffett and Charlie Munger's concept of staying within your circle of competence, we thought we'd change the lens and discuss areas where we might have gobs of data but are simply terrible at correctly estimating trends or outcomes. At Nintai we call these False Knowledge Fields (FKFs) and make sure they play no role in our valuations, investing calculations or investment decisions. We believe FKFs have three major characteristics. These include high amounts of historical data, a proliferation of ever increasingly complex analytical models (with associated acronyms), and an extremely low success rate in predictive calls or recommendations. On Wall Street, there has developed an entire industry around FKFs with trillions of dollars traded on their recommendations and insights. One great example is the use of analyst recommendations in equity selection.
Buy/Sell/Hold recommendations
In a previous article titled “People We Rarely See And Never Meet: Analysts, Research, And Recommendations” (which can be found here) we discussed how actual performance has little to do with analyst pay and perception. It’s probably a good thing. With roughly 5% of all analyst recommendations being a “sell,” you don’t have to be a remarkable statistician to know their overall performance is unlikely to be very stellar. Seen below is a chart of analyst recommendations during the calendar year of 2011 created by Cullen Roche for FactSet Research[1]:
So does the field of analyst recommendations qualify as a false knowledge field? We think the numbers confirm this. First, by utilizing Bloomberg machines and FactSet data alone, there is an extraordinary amount of data available to analysts. Second, each analyst and research organization has a proprietary research and rating system. Last, there is a preponderance of data showing that analyst recommendations woefully underperform the general markets. When less than 5% of stocks are publicly recommended as “sells,” it doesn't take long before your numbers lag. In this instance, analyst recommendations meet each FKF criterion extraordinarily well.
Why this matters
As individual investors (or investment managers in our case), we cannot stress enough the importance of not operating and making decisions in your own false knowledge fields. At Nintai, we have found a considerable amount of our readers’ questions lead us into our own personal FKF danger zones. The challenge is to continually push back and admit we either don't have the ability or the confidence to answer these questions. It’s not easy, but it is most certainly necessary if you intend to carry out your fiduciary responsibility to your clients. As an example, the following two questions should seemingly be easy to answer but are clear examples of FKFs.
Will the market go up (or down) in the next 12-24 months?
There is an extraordinary amount of data that shows us the historical performance of the markets. Combined with thousands of analyst tools ranging from the Schrodinger Equation to the Binary Options Robot, there is no end to the models available to predict whether the markets should be going up or down. The only problem with this is that they are rarely correct. As a bottom-up and individual equity investor, we see no value in these and clearly place this area in a brightly outlined FKF box. We never have and never will be able to make market predictions with any accuracy. An answer to this question given with certainty would be a grave disservice to our investors – and most likely wrong.
How will the world economy impact your portfolio recommendations?
Similar to the last question, there is an enormous amount of data and models that would seemingly help us make informed decisions. Unfortunately, the ability to calculate and estimate world GDP growth and possible recessions is beyond most analysts’ capabilities. The phrase “economists have predicted 9 of the last 5 recessions” is a nifty and succinct way of commenting on the steady failure of individuals to acknowledge their own FKFs. We concede there is both an inordinate amount of data and models out in the real world. We also recognize there are a lot of systems utilizing these data and systems to produce entirely incorrect predictions. Why would we think Nintai could be any different?
Conclusions
Just as it is critical to identify your own circle of competence (“know what you know”), it is equally vital to identify what is clearly outside your knowledge even when it seems the numbers and processes can get you to a well reasoned answer. The abundance of data and the definitive quality of multiple models gives us an entirely false sense of security that we are operating well within our competency. Nothing could be further from the truth. By answering our three questions it is possible to ascertain whether we should move forward or simply walk away from the problem and admit our ignorance. At Nintai, we believe the identification of our personal and professional False Knowledge Fields is as important as identifying our Circle of Competence. When put together we believe investors and money managers will have a significant advantage over Wall Street.
As always we look forward to your thoughts and comments.
[1] “Buy or Hold, But Never Sell!”, Pragmatic Capitalism, February 14th, 2012