Wolfgang Pauli, a theoretical physicist of the 20th century and creator of the Pauli exclusion principle, once remarked famously of an unfortunate colleague's paper: "This isn't right, this isn't even wrong." This wonderfully describes the absurdity of certain research points, and the fact that--no matter how much time or effort was spent researching factors and making connections--some things simply are not important to know and do not apply to an over all thesis or general principle.
This fact is also true when it comes to investment research. One can often find a thousand different reasons why an investment might go up, a thousand different reasons why it might go down, a thousand different reasons why it might do nothing, and another thousand that are otherwise irrelevant except through an obfuscating fusillade of second or third derivative reasoning or very minor relationships. At the end of the day, perhaps only a dozen of these factors really matter, and the rest of these thousands have little or no relevance during the investment period.
In our age of information where data is virtually everywhere to be accessed, knowledge is surprisingly still lacking. Much of the data we process turn out to be “noise”, which is like static on a television screen while watching your favorite show—it’s there but it serves to distort the picture. Knowing certain information might hurt more than help if interpreted the wrong way. One would understand very poorly the storyline of an episode of Law and Order if all one focused on were the static floating around the screen, or just simply portions of the show that are not important to solving the case (what color dress Detective Olivia Benson is wearing, Ice-T’s acting skills, to name a few).
That’s not to say that having certain data in front of you isn’t important. On the contrary, one should always spent time sifting through even the most mundane of places to find data. The difficult part is the interpretation of this data, and an often personal judgment on whether certain factors are important, or whether it is rubbish. Upon seeing an editorial, for example, two people might interpret the information presented in the piece in completely different ways. Can we really say one perspective is wrong while another is right? In the world of investment research, at least, we are bombarded by sell-side research and investment opinion (editorial in nature), but often times it is not the right vs. wrong that throw many thinkers off, it’s relevancy vs. irrelevancy. The right and wrong can only be weighed once the latter is determined. One can hear an investment banker pitch a deal all day long (as it is the banker’s job to pitch positive noise all day long), but at the end of the day, one invariably finds it necessary to simply discard certain things that were said during a pitch presentation or a conversation if it has little or no relevance—at least not to the proportions the banker might be proposing (i.e. “this is the deal of the century, everyone knows biopharmaceuticals will drive the future, this company makes biopharmaceuticals”)
In my short and humble career as an investor, some of my personal favorite examples of noise that I’ve come across in my own investment research have been cases where: (1) Generalizations have overweighed the specifics. Examples include hated sectors and negative trends that preclude people from wanting to look at an investment that may only marginally relate to the trend, or optimistic business trends that make people jump on the bandwagon no matter how fundamentally unsound the business might be. (2) Valuation metrics that does little to measure and compare a specific underlying business but are considered in an investment thesis anyway. Examples include cyclical stocks that are touted to be trading at all time low multiples (or cyclical stocks trading at low multiples that nobody wants to look at but are nevertheless good investments even given its cyclicality), or pharmaceuticals and other intellectual-property driven businesses compared on meaningless metrics such as P/E. (3) Wall Street estimates from analysts that are lured by noise (meta-noise).
Many more instances of noise exist, and to list them all is beyond the purpose of this short editorial. Noise is often case-specific, and when it creeps up it invariably makes the astute investor want to tear out his/her hair. The best acid-test is the funny feeling in your stomach, or a feeling of gut-wrenching flabbergast, or a temporary suspension of belief in the upward drive of mankind. The kind of feeling you get when watching CNBC reporters rabidly promoting a certain trend or going crazy over the psychological Dow 12,000 mark. It’s exciting, sure, but it’s also distracting from the crux of certain matters. That’s noise, and it’s an ongoing process for all investors to experience and learn to avoid these pits and holes on the highway of data and information.