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Hackernoon logoThinking in Systems is Hard But It Can Be Done [A How To Guide] by@CryptoLema

Thinking in Systems is Hard But It Can Be Done [A How To Guide]

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@CryptoLemaPablo Lema

Thinking in systems is hard, particularly because humans are best at linear reasoning, “if this, then that.” Systems are much more complex, made up of intermingled relationships with varying feedback loops, “if this,” may not necessarily lead to “that,” and even if it does, it might not happen for quite a while.

That is what I want to talk about today.

The crypto market (any market really), is nothing but a huge system, composed of many internal sub-systems and interdependent with many external systems.

Thus, there are a few things we can discern from systems in general which can be applied to crypto investing as a whole.

Before we delve into this more deeply, let’s illustrate what we mean by a “system” with an example: Let us imagine a simplified winery composed of grape fields which need to be harvested, mashed, and aged into wine, this is a system which will input grapes and output wine. 

Imagine that our wine in storage (what is being aged in casks) is our “reservoir” (by this I mean our stock or supply). New grapes from harvesting are our input and bottled wine is our output.

Logically our goal is to maintain a balanced reservoir; but this is tricky because our reservoir will adjust only slowly over time as it becomes engorged or depleted, depending on our yearly harvests and sales.

This is similar in our model of crypto investing. What we want is there to be a sustainable level of “work” inputs into any cryptocurrency we are thinking of investing in.

Notice that this is tricky to gauge because both if there is a lot of work going into a crypto asset, or too little, the change will not be immediately obvious.

Why do we want a constant reservoir of work instead of a flurry? When there are large input changes in the reservoir, the system adjusts. If flooded, the system will demand a higher level of inputs to maintain its level, even after the unsustainable rate of input has ended; because end users, or even the product itself (the cryptocurrency) have come to rely on this level of work.

In a sense, the “pipes” maintaining the inputs and outputs of our reservoir grow and shrink under sustained and depleted loads, but only slowly over time.

A low quantity of work inputs will deplete the reservoir of work capital in a crypto asset, and price collapse can not be far away. Depending on severity, this signals a stagnant or abandoned cryptocurrency. 

This is lesson one: we want constant reservoir of work capital in our investable crypto assets.

It is key to understanding our argument, to realize that a human operator running the winery, is unlikely to be able to foresee any large effects in our reservoir that a glitch in any sub-system may cause down the road.

Imagine that global warming declined grape yields by 5% every year hence. This will be catastrophic ten or fifteen years down the road, when we bring new yields to market; but is barely noticeable in production for the first few years.

Even if our operator may intuit the coming consequences, intervening in the system is unlikely to yield the results we would like.

What would happen if the operator can foresee the consequences and adjusts production accordingly? He develops a ten year plan to purchase more land, plant more grapes and protect his harvest; now we’re good right? The system is correcting.

Well, no. What will likely happen, if our harvester can foresee the coming collapse, is that most other regional wineries will as well, and will similarly adjust, creating an overproduction of wine and collapsing prices below production cost. 

This is lesson two: Intervention in the system, much like the devil’s bargain, is likely to turn against you.

Did you notice recently, the fact that Dash was added on Coinbase, but that Dash price plummeted in the months following? Shouldn’t a large new trading onramp lead to more demand and higher price? Well yes, but remember that the market pricing of an asset is an indirect consequence of the action of multiple subsystems.

It is hard to predict what will happen if we are not able to view the entire market system underlying an asset. 

Lesson three: This is impossible to execute, there are simply too many moving parts. Short term pricing is inherently unpredictable.

Consider your investment approach. Day traders have a hard time of it, they are both trying to see the entire market system (and its many external interactions with other systems) and simultaneously predict where all this will take one very small product of this interaction (price).

Our trading approach is superior because it only requires thinking in terms of inputs and outputs.

Finally, let us briefly consider feedback loops. Feedback loops tend to be triggered by input or output signals, but once triggered they become independent forces within the system. 

For example, in the Dash ecosystem, masternodes are meant to create positive feedback loops by requiring the lock up of large amounts of cryptocurrency, thus leading to price increase by reducing sell pressure. However there are limits to the elasticity of the system. 

Both radical up or down movements in price, caused by other forces, will create a self perpetuating loop leading to masternode liquidation, to either secure a large gain or cut a large loss. The trigger is outside the masternode sub-system, but affects it directly. 

This is lesson four: elasticity of the pricing sub-system is limited in financial investing, and certain feedback loops will regularly trigger marginal behaviour.

Feedback loops that trigger a large influx or outflow of new users, for example, affect our ability to adjust work inputs and product, so as to keep our reservoir stable. This is critical.

Our model works because it allows us to focus on the stability of the reservoir, without requiring us to fully grasp the state of the system beyond that point.

Our method of using systems gives us laser focus and greatly simplifies our analysis. 

We have used a highly simplified example, you need to build your own mental model by considering both inputs, outputs, and feedback loops and their effects on work capital.

You must be able to weave a system in your own mind that will make sense for a given cryptocurrency in terms of multi-year price appreciation.

A stable reservoir of work inputs, one resilient against feedback loop triggers, as well as input and output variance, will signal the cryptocurrencies with the greatest potential for mass adoption, and real use as a cash equivalent.


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