Wednesday, July 8, 2020

This Week's Message: Never Share Your "Secrets", and Thoughts on Systems (economics and markets specifically) and on Galileo

Every Wednesday I, in "This Week's Message", attempt to offer up content that's a bit more pithy on present happenings than perhaps you'll find in our daily messaging. 

Sitting here this afternoon I'm honestly feeling a bit numb after spending much of the morning working on a study I've assigned to myself on the rate-of-change dynamics in the price of a certain asset class and what they possibly say about future price movements in the stock market. I actually have about a century's worth of data to score, so it's a bit monotonous, and time consuming, but so far intriguing. Upon conclusion I'll likely highlight my findings herein. If they're indeed telling, well, then I won't be telling much about the study itself. For, if, say, you happen to discover a legitimate market signal beneath all of the noise, you never ever share it, as it'll only "work" as long as the crowd isn't using it.

By the way, that last line should serve as advice to never spend a penny on anybody's published penny-stock strategy (as one example). I.e., as long as the system works, I assure you, it won't be available for public consumption. Such schemes only hit the circuit once they've run their course. Actually, I suspect that more often than not they were simply some back-tested mirage that could be sold in a pamphlet, a book or a $50 a seat seminar, that was never profitably put into practice.

So, this afternoon I'm giving my brain a bit of a break and sharing some of what I believe to be pertinent highlights from my latest readings.

Recently read Albert Rutherford's Learn to Think in Systems, and while -- save for a passing reference here and there -- it wasn't a book on the economy or markets, well, it said a lot to me about the economy and markets.

Here are a few of my many highlights that I haven't already shared herein:  emphasis mine...
Systems thinking consists of three things: elements, interconnections, and a function (for non-living systems) or purpose (living systems). thinking involves the ability to represent and assess dynamic complexity (e.g., behavior that arises from the interaction of a system’s agents over time), both textually and graphically.”
...specific skills of systems thinking:
  • Understand how the behavior of a system arises from the interaction of its agents over time (i.e., dynamic complexity);
  • Discover and represent feedback processes (both positive and negative) hypothesized to underlie observed patterns of system behavior;
  • Identify stock and flow relationships;
  • Recognize delays and understand their impact;
  • Identify nonlinearities;
  • Recognize and challenge the boundaries of mental (and formal) models.
Defining human systems is a challenge because of their myriad elements and the above “cause and effect” interrelations. In such systems, change can root in the interaction of many various, and seemingly unrelated, actors and events.
This one speaks volumes about the risk of the extreme and seeming knee-jerk "stimulus" efforts by the Fed and the politician. 
How can one possibly predict an accurate vision for future changes, let alone future achievements? How can an individual, group, or country be sure their well-intentioned intervention or proposal will improve things and not elicit negative unintended consequences?
These speak to how I spent my morning:
...while the outcome of the future can’t be accurately assessed, there are some highly repetitive and foreseeable patterns in human systems. Every event is unique, but the human mind’s management of these events is predictably irrational. Thanks to this predictable irrationality and the research of systems thinking experts, some commonly occurring combinations of events emerged from systems case studies.
Identifying the variables and the links between them leads to the discovery of a feedback loop (or causal loop – both names are used interchangeably).
...every variable provokes a change in the next variable due to the change of the previous variable.
Reinforcing processes lead to growth or decay. They are often referred to as vicious or virtuous cycles.
A loop can’t be reinforcing and balancing at the same time. If you can’t decide which case applies, it means the story is not yet finished. Add more variables and links to the loop story until you can determine the nature of the loop (balancing or reinforcing).
Reinforcing feedback loops can be virtuous or vicious. 
Keep these last three in mind as the next few months unfold:
Reinforcing processes can generally be defined as self-perpetuating and can show a runaway tendency, especially in the later stages of a situation.

In reinforcing feedback, trends are always rising or falling. They are never flat. If the reinforcing loop has two variables, one is the performance variable that gets reinforced and the other is the action that creates the reinforcement.

  • Reinforcing feedbacks are unstable. Outside influence can easily shift the quality of the cycle from virtuous to vicious or vice versa.
  • There is always a limit to growth in reinforcing feedback as nothing grows or shrinks forever.
  • Change created by a reinforcing process can happen swiftly and unexpectedly. Think about the 2008 stock market crash.
  • The slow growth or decline these loops produce can be sneaky and easy to overlook. By the time we realize the reinforcing feedback at force, the process is well established, the stock has grown large, and even an immediate intervention will take a long time to make changes.
  • Reinforcing loops are prone to what systems thinking language calls runaway changes (sudden changes with a large impact that are triggered by a small input). Imagine this as an avalanche. Even a small noise or motion is capable of releasing thousands of pounds of untamed snowfall.
And from what I'm currently reading, Mario Livio's Galileo: And the Science Deniers:
The young Galileo probably helped his father in the experiments with the strings, and in the process, he might have started to realize the importance of the evidence-based approach to science. This could have been the first step in Galileo becoming a firm believer in the concept that in trying to find descriptions of natural phenomena, one needs, as he later expressed it: “to seek out and clarify the definition that best agrees with that which nature employs.”

Practically every individual who has made a novel contribution to a domain remembers feeling awe about the mysteries of life and has rich anecdotes to tell about efforts to solve them.” Indeed, creativity often means the ability to borrow ideas from one field and transpose them into another.
When a person has discovered the truth about something and has established it with great effort, then, on viewing his discoveries more carefully, he often realizes that what he has taken such pains to find might have been perceived with the greatest ease. For truth has the property that it is not so deeply concealed as many have thought; indeed, its traces shine brightly in various places, and there are many paths by which it is approached.
To Aristotle, the only possible way to understand phenomena was to know their purpose. Galileo, on the other hand, employed a clever combination of experimentation and reasoning. He realized relatively early that progress is often achieved through correct decisions as to which questions should be asked, and also via studying artificial circumstances (as in the case of balls rolling down inclined planes) instead of examining only natural motions. 
Thanks for reading!

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