# My New Energy Algorithm Will Find Us New Trades

For today’s *Oil & Energy Investor *piece, I’ll need you to bear with me as I outline my latest project. It is shaping up as one of the more exciting ones I have designed in years.

Allow me to apologize up front; in what follows, the professorial part of my background may well sneak through.

(But don’t worry – there’s something big in this for you.)

This approach is also the most recent example of what my wife Marina refers to as one of my primary maladies: “not leaving the damn thing well enough alone.”

Apparently, that means I also have other “maladies” (the list seems longer now than when we married thirty years ago).

But I digress.

I have always loved posing and solving problems. It is the process used that I often find more intriguing than the answer obtained. Even if the exercise does upon occasion leave some “collateral damage.”

Consider it a model building exercise.

### The Parallel Rule in One’s Life

It is intriguing how ways in which you practice one part of your life can affect how you move in others. Often, it makes little difference where a way of solving problems arises; there are usually ways to apply it elsewhere.

This is one of the more important lessons I have learned over the years. There is an important difference between *invention *and *innovation. *

The former is coming up with something absolutely new. This is very rare. The latter is taking something that already exists and using it in a new way. It is innovation that fuels most of human advancement.

As veteran readers of *Oil & Energy Investor *are aware, I have had three interlocking careers: academe, energy, and service as an intelligence actor and analyst.

These for some time would operate in parallel (though not always pulling in the same direction). My existence sort of evolved much like a living, breathing Venn diagram. The “grey area” where the three circles intersected defined who I was.

A student of mine, who is now quite well-known in his own right, once asked what got me out of bed in the morning.

The answer was easy. How do we push the envelope today? What anomaly can be uncovered that demands a solution?

### Why Humans Defeat Math

For much of my life, I have applied things in ways different from others.

At a young age, I was found to be gifted with an analytical ability. As is usually the case with young kids with this “malady,” this was first evidenced in mathematics. That led to my first degree at sixteen in theoretical physics.

Yet I always had an interest in and curiosity about the human applications of reasoning, those exercises that often cannot simply be rendered by numbers. These were what a mentor of mine would refer to as the “squishy” part of being human.

He often also called it the “shoving a round peg into a square hole” syndrome.

After all, numbers can tell you how many people believe something. They can even tell you how many act in a certain way. But numbers alone cannot tell you why people have those beliefs or act as they do. Numbers simply exist.

Humans, on the other hand, need to provide an understanding about their existence. The direction implicit in numerical exercises result follow rules impressed from the outside.

However, human action introduces another vital element – intentionality.

That means any pure mathematical way of explaining things must always be tempered by assumptions not part of the equation itself.

All mathematical systems, for example, are based on assumptions (or postulates) that are accepted as given but cannot be proved. Each formulaic proof begins with: “Assume that X equals (whatever), from which it follows that…”

Change the assumption, you change the proof, direction, or even result.

### Euclid’s Postulates

A clear illustration of this is found in Euclidian geometry, that oft-dreaded downer from high school. Euclid initially used four postulates for the first 28 propositions in his *Elements. *These are referred to as *absolute geometry. *The fifth was required once #29 required a consistent proof.

That fifth postulate is usually rendered as follows: given any straight line and a point not on it (i.e., perpendicular), there exists one, and only one, straight line which passes through that point and never intersects the first line, no matter how far the two lines are extended.

This is often called the “parallel postulate,” and given the above noted parallel nature of my careers, I have often been attracted to it.

Well, here’s the kicker.

The fifth, like the previous four postulates, is based on assumptions that must be accepted without proof. The main assumption is this: Euclid is dealing only with a two-dimensional world. It is why we call his system “plane geometry.” Yet, as mathematicians demonstrated some two centuries ago, add a third dimension – depth – and the result fundamentally changes.

With this third dimension added and the definition of parallelism remaining unchanged, you now can draw any number of lines through a point external to a given line that do not intersect.

Change the basic assumption, change the result.

And that finally leads me to the use of algorithms and how they are being misused in energy analysis…

### A Roadmap vs. Contrived Problems

An algorithm is a procedural roadmap, a set of rules or ways of proceeding that streamlines calculating exercises intent on solving problems. Usually, the algorithmic process is expressed mathematically, particularly in computer applications intended for higher order number crunching.

But this is not magic, and the way in which the approach is used currently in large-block energy investment strategies has become suspect.

Initially, there is a way that the algorithm as a process is identified in psychology, and it says a great deal about how to understand their impact on the energy market. In applications to a wide variety of mental exercises, a psychologist will often make the distinction between *algorithm* and *heuristics*.

The difference, essentially, is this.

An algorithm is basically a set of “how to” guidelines used to solve a known problem. A heuristic is a learning mechanism employed when there is no readily available path to solve a problem.

The deficiency in current mainstream applications to determine oil prices or other matters related to the energy sector results from confusing these two.

Most practitioners who are intent on inventing a new, fanciful way of generating artificial profits are essentially trying to reinvent the wheel. Rather than innovating, they insist on treating their algorithms as heuristic and inventing a new (and contrived) problem.

This is compounded by such algorithms being applied to multivariate computer programs in which the new “alchemists” attempt to read human “squishy” factors as if they were governed by the same assumptions as a system of mathematics.

Morgan Stanley just hired an Ivy League computer scientist to head up their new Artificial Intelligence efforts. Goldman Sachs brought in an AI expert from Amazon, and JPMorgan is getting into it as well. But try as they might, they are likely still years – even decades behind Alpha-9. It’s an unprecedented combination of raw computing power, blazing processing speed, and other-worldly intelligence… and now, you can become a millionaire in 12 months. |

Here is the danger that results…

### When Emotion and Energy Collide

The math solutions end up justifying the arbitrary assumptions upon which they are based. A drive to generate ways that result in very short-term profits, becomes largely a self-fulfilling prophecy.

They are often wrong, but nonetheless manage to distort what is occurring in the underlying market fundamentals. Much results from an irritating penchant to hurry what economic indicators are telling us; the genuine yardsticks need a fiscal quarter or two to play out.

Unfortunately, these guys crunch arbitrary values into speculative algorithms in search of a roadmap to making money before each daily trading session is done. If they can get a Chicken Little on TV to stoke emotions while the computer continues spewing out lines of 0s and 1s, so much the better.

Progressively, the “market price” published – largely from those cutting crude oil futures contracts (paper barrels) – becomes less indicative of the real price carried by physical oil in trade (wet barrels).

This usually plays out better for these guys if the price is artificially pushed down. A range of short plays, derivatives, arbitrage moves, credit swaps, and the like are introduced to extend what is often a manufactured result.

Don’t get me wrong. I have nothing against making profit. After all, that is what my investment services are all about. But the mathematical sleight of hand increasingly being used is holding up a carnival mirror to the market. That has unsavory consequences.

Nonetheless, there is something interesting that can be gleaned from what they do after the fact. The questionable assumptions leave a mathematical imprint, much as a trail of bread crumbs through a maze of numbers.

Strip these from the equation, and there emerges better lenses through which to view market dynamics.

### Applying Algorithms to Energy

About two years ago, I developed a diagnostic algorithm to do just that. The result is a proprietary tool I call the Effective Crude Price (ECP). This is a better read on what the price of oil *should* be, once the exogenous games are stripped from the process.

The closer the published price approaches my ECP, the closer the market price reflects the genuine value of the underlying oil.

There is one distinct drawback to the ECP exercise: it is always retrospective. The calculations tell us where the market has been, not necessarily where it is going. As such, it has a limited use in determining where we should put our money next.

Until now, however (drum roll, if you please).

I have run hundreds of ECP permutations, providing what is opening up as an adequate data base from which to do projections.

This is what has resulted.

### Not Leaving Anything Well Enough Alone

A new algorithmic path is emerging that would allow me to identify preferable investment directions *moving forward*. It is still in the testing (beta) stage, however, and requires greater access to a bigger global set of project intentions, public and private investor preferences, and government policy directions.

But I have great confidence in this method to provide knowledge about the market that we simply didn’t have before.

Against such a more extensive intelligence set, my developing new algorithmic method may be able to cherry pick projects, companies, regional markets, and trends against which a “layering” strategy can be employed to maximize return.

In a number of recent international presentations and briefings, I have termed it *layering* because it cuts across what are usually considered quite distinct investment targets.

For convenience, I have often used this diagram to illustrate the approach.

The essential key to all of this is an initiative now well underway to bring together some of my network of international experts to analyze and structure the data flow on energy investment preferences, trends, and projections.

A sort of centralized handicapping of market players, if you will – institutional, public, and private.

Meanwhile, while I haven’t yet titled the new algorithm, the data flow from a fluid group of global analysts has already begun.

In a bit over two weeks, when our next Windsor Energy Consultation convenes at the castle of the same name outside London, I intend to unveil the initiative before one of the heaviest hitting audiences around.

We may be on to a major new way of selecting investments. And with apologies to “she who must be obeyed,” there may be a lesson here.

Sometimes it just may be better “not leaving the damn thing well enough alone.”

Sincerely,

Kent

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