Cryptocurrencies – Is it a Ponzi scheme?I had been spending the last couple of days breaking down Ponzi schemes by attributes, translating it to a mathematical model, in hopes of finding provable similarities with cryptocurrencies. After all, it looks like cryptocurrencies are fueled on the necessity of new purchases for price increases, hence the association of it in likeness with Ponzi schemes.
First of all, definition just for entirety’s sake: an “investment” generating returns for (older) investors using the revenue intake from new investors. Apart from fresh intake of funds from new investors, the “investment” may or may not have a business activity for revenue stream. Usually comes with an abnormally high promised return paid in a controlled manner over an agreed time period.
From this, we could make a very simple model of a Ponzi scheme as such, optimistically assuming there is a business activity providing a revenue stream to maintain the scheme for as long as possible:
Intake of new funds = F
rPayout of funds = F
pTime starting from 0 (
t >= 0), so at any point of time we’d expect both intake and payout
Business revenue = F
bTotal liquidity = C
L, where C
L = F
r + F
bFrom here we could already very quickly deduce if
t(F
b) >
t(F
p), then the business is making a profit hence sustainable and legitimate. If payouts from C
L results in a negative
t(C
L - F
p) < 0, where F
b < F
p then this fully is a Ponzi scheme relying on new fund intake to survive.
From this model, if we could fit in the attributes of cryptocurrencies exchange-of-hands we could determine at what stage it would be a Ponzi scheme. However:
1. Intake of new funds. When new funds of a Ponzi scheme is being taken in, this adds to a pool of liquidity such that C
L = F
r + F
b. On the other hand buy orders does not add to any pool and instead provides a difference which indicates the increase (or decrease) between previous price and new price.
2. Payout of funds. When a payout of a Ponzi scheme is initiated, this deducts on liquidity C
L with F
p. Again, the same problem arises, sell orders does not add to any pool and this is derived as a difference instead.
3. Time is consistent between both models.
4. No liquidity of the same sense for cryptocurrencies – It’s a market supply-demand curve.
From here we can clearly make the differentiation that – As the attribute C
L does not exist in a cryptocurrency market, it is not possible for it to fail the same way as a Ponzi scheme in which t(C
L – F
p) < 0. There could be a huge negative difference between the previous and new price, but never to a point where the price is below 0. On the other hand price increases are fueled by speculative worth where the “greater fool theory” applies, so we could look objectively from this perspective to see if this could result in a crash/bubble, and what happens to the “last greatest fool”.
In summary, instead of showing attributes akin to a Ponzi scheme, cryptocurrencies show attributes closer to the stock market/penny stocks, driven by fundamentals (equivalent to investigating the industry, NAV, P/B of a company) and crowd speculations. I may expand more about bubbles and the greater fool theory in relation to the cryptocurrency market on a later date, but not now.
You've managed to put a convincing argument with a mathematical model, what I have been trying to explain using mere words.