Radix Economics and Extremistan


#1

After reading Antifragile, I got a bit concerned about the economics model. So this just a first attempt to explain why.

While I’m not proposing any changes right now, I think we should thoroughly discuss the subject and make sure everything in the stability model takes into account the proper domain.

These concepts were made by NassimTaleb who divides the world of randomness in mediocristan and extremistan.

Mediocristan

Is a place where everything is close to the average, subject to gravity for instance, the bell curve works perfectly here.

Example:

Assume that you round up a thousand people randomly selected from the general population and have them stand next to one another in a stadium. You can even include Frenchmen (but please, not too many out of consideration for the others in the group), Mafia members, non-Mafia members, and vegetarians.

Imagine the heaviest person you can think of and add him to that sample. Assuming he weighs three times the average, between four hundred and five hundred pounds, he will rarely represent more than a very small fraction of the weight of the entire population (in this case, about a half of a percent).

You can get even more aggressive. If you picked the heaviest biologically possible human on the planet (who yet can still be called a human), he would not represent more than, say, 0.6 percent of the total, a very negligible increase. And if you had ten thousand persons, his contribution would be vanishingly small.

In the utopian province of Mediocristan, particular events don’t contribute much individually—only collectively. I can state the supreme law of Mediocristan as follows: When your sample is large, no single instance will significantly change the aggregate or the total. The largest observation will remain impressive, but eventually insignificant, to the sum.


Extremistan

This is the domain of information (book sales, stock markets etc…), where even if you increase your sample size you won’t be able to know it’s true statistical properties, that doesn’t mean the past is irrelevant but it is insufficient to make any useful prediction.

Fat tails might be disguised as normal distribution for a long time until a single event changes everything.

In Extremistan, inequalities are such that one single observation can disproportionately impact the aggregate, or the total.

Another way to say it is that social quantities are informational, not physical: you cannot touch them. Money in a bank account is something important, but certainly not physical. As such it can take any value without necessitating the expenditure of energy. It is just a number!

Example:

Consider by comparison the net worth of the thousand people you lined up in the stadium. Add to them the wealthiest person to be found on the planet—say, Bill Gates, the founder of Microsoft. Assume his net worth to be close to $80 billion—with the total capital of the others around a few million. How much of the total wealth would he represent? 99.9 percent? Indeed, all the others would represent no more than a rounding error for his net worth, the variation of his personal portfolio over the past second. For someone’s weight to represent such a share, he would need to weigh fifty million pounds!

If you are dealing with quantities from Extremistan, you will have trouble figuring out the average from any sample since it can depend so much on one single observation. The idea is not more difficult than that. In Extremistan, one unit can easily affect the total in a disproportionate way. In this world, you should always be suspicious of the knowledge you derive from data.


Here is graph showing how an increase in sample size works great in mediocristan but terribly in extremistan.

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You can still have more erratic variations on larger samples.


#2

@Angad the economics section was locked, could you open and move this topic? Thanks


#3

Thanks for the post @ryan


#4

I do not understand what is your concern about economic model @ryan?


#5

My concern is that the model mistakes extremistan for mediocristan.


#6

I think quite opposite . Previous model did not took extreme events under concern. New model can resolve issues even in absolute extreme cases. Interesting why you think not?


#7

When it comes to extreme events there is nothing fundamentally different from the previous model.
These extremes events are not present in historical data (the definition of a black swan) and one of the basis of the economic stability is precisely historical data.

From what I understand about this, you can’t just have a prediction model based on historical data, you also need a lot of redundancy and optionality to deal with unexpected events that will never be a part of your sample. Remember they are unpredictable due to non-linearity and complexity in the system, aka extremistan.

There are some related issues with the specifics of the economics model, but that should be mentioned here only after the econ white paper is made public. So it’s better to focus on the general aspects for now.


#8

I will gladly continue this discussion because i think that current model is much more ready to extreme events. But it has its downsides in few aspects


#9

Then please show some evidence to support your affirmation, I would also like to know what are the downsides for you.


#10

Lets fragment it into smaller pieces: software, currency, interaction with external economies.

  1. Software. I can not comment about how well code is written and how good architecture is made so lets assume it works fine. If it does not then it is Black Swan no.1. If it works fine it will exist in the wilderness of Internet and nobody will be able to harm it. It is impossible that Radix protocol will be banned worldwide.
  2. Currency. all cryptocurrencies has same danger that governments can ban them. That is not impossible in general but world has never been united before and if you look at today’s landscape everything is going better for crypto in general and Radix will not be excluded somehow. If people will find utility in Radix currency nobody will be able to ban it because it will be same as to ban the internet.
  3. Interaction with external economies. By this i mean AMs, relationship with banks, public interest and etc. Radix will be fragil in the beginning and that fragility will be smaller with growth. First step is general interest in Radix from public and companies, when we will reach significant portion of investors and users we will get pace and will not stop. More countries, more AMs ,more partners, more users will mean less fragility.

#11

1 and 2 are not relevant to this discussion because I’m concerned specifically with the economic model’s ability to maintain a stable value during extreme events. But I generally agree with those points. Open source after launch should cover 1, as for 2 even if governments try to ban Radix that would only make people more interested in it. Look at BTC growth in Venezuela, that’s the antifragility of information!

On 3 you are right about the fragility in early stages and that’s fine. As the system grows it will incorporate new information which will lead to more resilience overall.
The problem is in the stability mechanism (after it’s implemented ofc) because it relies on trends and historical data. Again: that is insufficient because extreme events are not present in the historical data so you cannot make any kind of predictions about them.

Take a look at this chart, another extremistan simulation to make it clear
2

That single spike is responsible for almost all the statistical properties of the system, but the historical data up to that point would not help you prepare for it.
It shows that black swans matter not because of their frequency, but because of the impact they can have.

I’ll make a proposal to mitigate the impact of those extreme events, don’t think they can be completely avoided, but if the price is not wildly deteriorated we should be ok. I just want to learn more about the economics behind it to avoid presenting half baked ideas.