Some if not most of us are familiar with the Laffer curve -- a fairly simple concept that represents the optimal point of government revenue generation vis a vis the going tax rate.
The most basic observation of the curve is that, at the extreme points of 0% taxation and 100% taxation, government revenue is effectively nonexistent. At one end of the scale nothing is collected; at the other end all incentive for productivity is removed.
From a cash flow standpoint, the government's goal is to find that optimal point X on the Laffer curve --somewhere between 0% and 100% -- where revenue is maximized.
Obviously there are all kinds of philosophical and political rabbit trails here. Rather than go down any of those trails, I'm interested in discussing how the Laffer curve as a concept can shed light on the effective use of information in trading. The concept of optimal balance between two extremes is what's important.
With that background, imagine that the Laffer curve is now applied to your information intake for trading decisions instead of tax rates.
Once again, you are looking to find point X, and once again 0% and 100% represent unacceptable extremes. A 0% information intake would mean trading at random (no information processed); at the other extreme, a 100% information intake is impossible. To pursue it would mean trying to swallow the ocean -- i.e. parsing an infinite stream of data -- and never trading at all.
The first question is, in terms of optimal information intake, where is point X for you? Where is the point at which you receive maximum value for the flow rate of information processed, before rate of return slips into decline?
Consider two hypothetical traders, similar in all respects but one. Trader A has an average information threshold, while trader B has a modestly higher one. Does this translate to significant advantage?
In the short run, not necessarily; in the long run, almost certainly. Why? Because increasing your optimal information threshold is a big step on the road to increasing performance capabilities.
Say Trader A and Trader B both routinely analyze the same stacks of data in various forms: technical, fundamental, situational, etcetera. With a higher information threshold, Trader B is able to consistently extract more value from the data. This advantage persists and compounds, like an always-on water faucet with a higher flow rate. The information curve advantage shows up in bottom-line performance as either 1) a track record of consistently higher quality decisions, or 2) a greater number of equivalent quality decisions, spread across more markets / timeframes / etc. Better results, more turnover. Ceteris paribus, with a higher information threshold, Trader B is likely to outperform Trader A.
One of the popular pitfalls of the discretionary trader is "information overload" or "analysis paralysis." Both of those are real conditions that discretionary traders must wrestle with. (Mechanical traders too, during the tweaking and building process.)
If we frame the analysis paralysis problem in terms of the information curve, we can see that it is generally a result of trying to handle a higher-than-optimal information intake; a trader experiencing analysis paralysis has exceeded his (or her) personal threshold of data flow. The paralyzed trader needs to cut back on information intake overall, or elevate the threshold through innovation and efficiency gains, or ideally both over time. (If that doesn't work, another alternative is to cut back on activity levels in general; cutting back to zero would equate giving up active management entirely.)
Again, going back to the performance edge: if your optimal information threshold is high, it implies that you can expose yourself to a larger volume of information profitably, i.e., you aren't just doing extra reading / following extra data points for no reason. The decision making constraint is you; not just how much information is useful, but how much you can use.
It's been said of many great traders and investors that they can look at a hundred data points and immediately pick out the handful of factors most relevant to the situation. The faster they can do this (without sacrificing quality), the more decisions they can make, or the less time they can take, or both. A trader with a high optimal information threshold has a built-in sifting mechanism that is constantly evaluating and discarding; the more you effectively you can sift, the more quality you can produce.
Key point: raising your optimal threshold does not necessarily mean wading through superhuman amounts of data. If anything it is the opposite. It means learning what to ignore as much as what to pay attention to; having a strong sense of what you can't know and what you don't really need to know.
Remember the Where's Waldo books? The funny little guy in the striped sweater and stocking cap, hiding in complicated scenes? To find Waldo fast, you have to be able to discard irrelevant data fast; the same is true in regard to efficient decision making. The skilled trader is not reading bloated research reports until two am every morning. The goal is to absorb data quickly and efficiently, without losing one's bearings or experiencing analysis paralysis.
There are a number of ways to elevate the information curve, and potentially elevate performance as a result. Going about it requires taking a structured approach to markets overall; learning to think about markets in a certain way.
