[Economic Model Suggestion] Soft thresholding through probabilistic matching

  1. Failed transactions do not have a fee on Radix (related to the double spend problem). We can look at adding a cancelation fee, but that would have to be no more than the cost of a normal transaction because if it was bigger I would likely use the double spend consensus prevention to cancel the order instead. That fee size means that inserting and removing a significant trade a few hundred or thousand times is not likely to be much of a cost. I know there are a few different methods you could use here, but the underlying issue here is that with anything deterministically random related to money adds an inherently gameable aspect of the system, and while you can go down the anti-game rabbit hole, you will always be doing that at the expense of ease of use, low friction, and adding system complexity.

  2. Depends if I want to use the Rad, or I am just playing the market. If I want to use the Rad, it isn’t at a loss, just the best possible price. It just pushes the surplus to be essentially negligible.

  3. Oh - in that case, it doesn’t really solve the problem? It just means the value of the Rad can periodically push higher than Pmax. I thought the issue that was being looked at here was market makers sitting between Pmin and Pmax and thus reducing the likelihood of the ECA entering the market?

I’m no longer clear which issue is being solved by this proposal.



The goal is for XRD to be stable w.r.t. the XRI basket while not placing a hard ceiling limit. Hard ceiling limit without intervention inbetween means that the value is relatively stable as it can freely move between Pmin and Pmax which in turn may incur a 20% loss. In addition, this means that while XRD is switching hands a lot, there is no incentive to hold over day trade as the value doesn’t hit Pmax.

My proposal means the system provides increasing market pressure on the price and pushes it towards Pmin. The real value w.r.t. XRI is Pmin. Any value above is speculative. The system merely attempts to match buy/sell orders which are above Pmin and redistribute the surplus to bag holders during which the price is pushed towards Pmin.
Eventually, the price can’t hold for long above Pmin and it will be very stable w.r.t. the XRI.



Sorry Piers, I am unclear on your answer. Have companies you surveyed said they would be fine buying at 1.1 to avoid “unclean” Rads (or for other reasons)? Or are you speculating that they will be fine paying a premium? For instance there is legitimate reasons to assume price to be well below $1 during stage 2. Far below $1. How much are you speculating and how much have you addressed this possibility with interested businesses? Right now, to get to Pmin of .9 we need billions of Rads bought at 1.1. Billions. So I am very interested on what businesses have told you specifically.



There is nothing stopping you from placing orders above pmin or below pmax in the current model. That is the inherent issue of creating hard bounderies when the system is so new. You show your cards, you make the system a trader and other traders will control the market, because it will be easier to profit on trading the range than waiting around for the hopes of interest through redistribution. Additionally having redistribution associated with only buying the “ceiling” de-incentivizes people to do so pyschologically.

But this model proposed hides what the pmin and pmax are, because there is a randomness in the buying or selling. Therefore how would people know what to “game.”? If the price goes up to $10 early in stage 2, who cares? Isnt the goal stability by stage 3?

Also if businesses are going to buy direct (like you suggest above) then if the price is $5, why can’t you still sell it to them for $1.1? They are still paying more than those at stage 1, they are creating redistribution and contributing to the pmin.



Sure - in this case you are gaming the randomness, simply by placing and removing orders. You are trying to force the system to behave in the way you want it to by repeatedly triggering the randomisation algorithm. Theoretically, do it enough times, it will fulfil your order at the price you want. That is the gameability. It may be random, but play enough times it still gives you a predictable outcome because the randomness is still bounded by a probability function.



I disagree. In this scenario there is no incentive to trigger the algorithm. These incentives go away as soon as price doesn’t have a ceiling. I don’t know at that point why anyone would want to “trick” algorithm as there would no longer be a manufactured range to trade.



To get clean Rads, not to avoid them.

No - we haven’t yet asked if they are willing to pay above market price for tokens if it meant they did not have to interact with other users. The Economics was not yet sufficiently defined, so asking such a specific question wasn’t possible.

Our market research has instead been asking as many projects as possible about the issues they have with deploying on existing platforms. Predictability of cost of using the platform (e.g. it not suddenly costing you 5x to use the platform next month as it does this month) has been one of the biggest pain points we have seen (outside of scalability).

A strong guarantee of supply, at a predictable cost is verified to be desirable. To also know that none of the tokens you receive are tainted in any way as they are freshly minted by the system - that has not been properly surveyed yet.



We’ll then I think we should direct the focus on figuring out a system that allows businesses to buy at fixed price, while not gutting the incentives for everyone else and crushing stage one investors. In this specific proposal thread, the system would allow price to travel upwards creating much better incentives. So one obvious option I mentioned is allowing businesses to buy direct at 1.1 even if market price is higher. Basically doing businesses deals OTC at fixed price. I think there might be even more options especially if the goal is .9-1.1 by stage 3 and not stage 2. If we have a 5 year window to get this stability on the top end as well as the low end then this can be solved with an algorithm as proposed above.



This is how I assume the system is defined to work here - please let me know if I am off:

Pmin = R/M
Pmax = f(random P)>Pmin

Meaning that the ECA could step in and fulfil any XRD buy order at any price greater than Pmin, but will only buy back XRD at Pmin.

As a trader:

Place and cancel random buy orders (XRI for XRD) just above Pmin. Put enough in, the ECA will print me new Rads at some price just above Pmin.

Next, I would then place those XRD for sale at just above where I am exercising my cancel and replace buy order system, say at Pmin + 10%

The system cannot buy back the Rads off me because it is above Pmin. Any user who doesn’t want to wait for their order to be fulfilled (either by the system, or by another user), will just buy my Rads for sale at Pmin + 10%.

I know this is a similar shape of problem to the static Pmax problem, but the foreseeable issue here is that you will get people gaming Pmax down as low as possible here, meaning the Pmax-Pmin margin becomes much much lower, and so to (likely) the market price of the Rad.



I am sure some enterprising business would arb the crap out of that, and you would just have the practical market peak price tend towards 1.1, even if it wasn’t directly enforced by the ECA.

Even if that didn’t happen, that sounds like giving favourable rights to one group over another. It also sounds like every business that wanted to use the Radix network would need to form a relationship with the foundation, which doesn’t seem scalable, practical, fair or fail safe.



Apologies @tesslerc - re-reading your post, the Pmin is also a random function related to volume.

So; probably a good idea to outline why Pmin is an important feature for the network (outside of holders) - it’s a helps guarantee a minimum level of service from the Node Runners themselves - e.g. as a organisation thinking about providing computing resource to the network, I would like to know what the minimum revenue I can expect from providing that computing resource.

Pmin helps create the other side of this equation. Thus:

Pmax = gives people predictable cost of using the network
Pmin = gives people predictable revenue from providing service to the network

Now, obviously the price can move between those two boundaries, but at least Node Runners always know what the worse off they can be, given a certain earning potential of Rads into the future, and developers/companies know what the most expensive the Rad network will be for them to use.

I don’t think that using a random function for Pmin is as bad for Node Runners; so this is not so much a criticism of that, just an extra reason why Pmin is important.

On a wider discussion of a random function Pmin, you have a similar issue of gameability issue:

As a trader, I will;

  1. Buy up anything 10% below Pmin and lower
  2. Repeatedly put a sell order for XRD just below Pmin until the system fulfils me + take the 10%

Of course, this is assuming that Pmin converges on R/M (which I assume it does, such that when M=0, R=0)


  1. I wrote that Pmin can either be random or fixed. Regarding gameability of Pmin, you want to sell at Pmin but people are trying to sell at $0.01 so it won’t get matched - see explanation below.
  2. The system doesn’t intercept any order above Pmin. It intercepts any buy order at or above the maximal buy order. You can’t set buy order at Pmin if people are trying to buy at $5 and expect the system to fulfill it. Exactly as any trader selling XRD for Fiat tokens can’t fulfil an order at Pmin when there are orders at $5 - you first handle the highest gains then start going down.

Bottom line, the system should be treated as any other trader. It can’t match trades which are illogical to batch, e.g., a buy order below the maximal value someone is currently willing to pay.



The bottom line is that pmax is the real issue here. With a hard 1.1 top there simply is too much risk vs too little potential reward to use the system. We simply cannot sell Rad at $1 and create a ceiling only 10% higher, with a bottom 90% lower.

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@Piers @tesslerc @windjc,

One of the primary goals in stages 1 and 2 is to increase Pmin up to 0.9. Tesslerc’s approach will work toward this goal by having the ECA always sell above Pmin, and always buy at Pmin (sell high, buy low). Each sale is guaranteed to put upward pressure on Pmin.

@Piers, if you’re concerned about traders gaming the system to drive the market price down, then have the ECA always sell for at least Pmin + N (maybe 10% above Pmin for example). This will ensure that even the traders who are gaming the system are actually pushing Pmin up over time. The more they trade, the faster Pmin increases.

In addition, as we’ve said, the ECA can place its sell order at or above the current highest bid order and below the lowest ask. It will act a bit like a market maker, keeping the market liquid.

To address businesses who want a ‘new’ coin, if an order comes in at a certain level above Pmin (e.g. Pmin + 0.2), then the ECA could always fill that order. This will allow businesses, or someone who just wants Radix now, to buy as much as they want at a reasonable price above Pmin without having to wait for a seller.

I do agree that Pmin should always be fixed at R/M to provide a stable floor.

I believe that this approach will increase Pmin much more quickly than only having the ECA sell at Pmax because it takes advantage of the trading while it’s at levels between Pmin and Pmax. It even works if the trading stays between Pmin and Pmax all of the time.



I think this idea, and this thread are converging:

I think the idea of a soft Pmax might be workable, but not as probabilistic function; would need to be volume/price driven so that Pmax is known and can be used by businesses, but does not prevent the price itself from moving according to the market needs over time.

Have a look at the other thread and jump in if you want.



The only issue you are describing is an illiquid market in which there are no sellers.
So long as there are sellers the businesses can buy at the minimal sale price regardless of the existence of an economic model.

Bottom line is - you can’t have a “known” Pmax value and allow it to move these two facts are negating one another. And if it is known, it can/will be gamed.



I feel like we are pushing together micro and macro economics here. Yes, on a day view, it is possible that a known Pmax will mean that a local maxima just below the Pmax is reached but never exceeded. However, if the net demand for Rads is positive then that threshold will be broken as the sellers do not have an infinite supply.

This then comes back to the velocity of Rads within the system, and if people are being encouraged to hold Rads as a predictable SoV or not. Making something into a SoV is really the only reliable way to assure long term holding and decreased velocity within the system.



As I mentioned in another thread, we need to distinguish our terminology to avoid confusion.

Pmax should be a “hard” limit and in any given period its exact value is known. Perhaps it is always 1.1 * XRI. Or if we do allow it to move, then it should still be easily calculated. For example, in any given period it could be Pmin + 0.2. As @Piers pointed out, this allows businesses to easily calculate their maximum costs of buying XRD.

Psell – But for these kinds of discussions, we also need a term that describes a more volatile price at which the ECA can make sales. I’m suggesting “Psell”. This value can change within a given period based on the algorithm we choose. Perhaps it’s based on volume/price, or a probabilistic function as Tesslerc suggested, or some other approach.

Psell will never exceed Pmax.

Having the two terms will avoid confusion and allow us to clearly discuss the best approach for the ECA to be successful.



You know what also enables business to easily calculate the buy value? Fiat tokens :confused:
It feels like the current model is one compromise after another, all in order to provide assurances for businesses, while ignoring all other users in the system.

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“If net demand for Rads is positive…as sellers do not have an infinite supply.” I keep seeing this reiterated over and over. The demand you are describing to get to stage 3 is businesses or individuals buying over $1,000,000,000 Rad at $1.1.

If that does not happen, the current system asks people to buy Rads at $1 in stage one, with a 10% max upside and 90-99% potential downside beginning in stage 2.

How is this a justifiable risk/reward scenario? The fact that people who buy at $1 may make 10-20% of stage 1 interest before stage 2 launches if literally tens of millions get invested AFTER they invest? Does that really lower the risk/reward to justifiable levels?

Would you in good faith recommend such an investment to your friends and family?