I am sure many of you are wondering about the individual parameters of Shelly, when it comes online later this year. All else equal, one particular parameter–the reserve reduction rate–is of high importance as it affects the total health of the Cardano ecosystem. We should all keep in mind that Cardano depends on the effort of developers to build useful applications on it.
In the early years, and until ADA establishes itself as an economically viable ecosystem, a significant portion of developers will ask to be compensated in hard currency (because, well this is what they spend to sustain themselves). This is an unavoidable problem.
I have analyzed the Cardano reward scheme with a view of setting this parameter to increase the economic resilience of the system under adverse conditions.
Here are my thoughts on the subject along with my findings:
a. Cardano and the developers who support the protocol should set the reserve reduction rate at a level that guarantees sustainable level of annual treasury flows (in USD) to support the protocol under extreme price conditions (i.e. 1ct/ADA).
b. Assuming that transaction fees are not going to be a significant source of cash flows, treasury funding will depend largely on the reward reduction rate.
c. Assuming the minimum protocol maintenance budget of $3M per year (this is my best guestimate), the appropriate reserve reduction rate should be set at around 10% per year. This rate gives us the annual cash flow to sustain the protocol even if the USD price of ADA falls to 1.6c per ADA. See the sensitivity analysis below.
d. This translates into an annual stakeholder reward rate of 3.94% in ADA for the first year, assuming a near-complete network participation rate.
e. Growth in adoption will be key in driving the price of ADA and in lowering network participation rates for investors with price increase likely to have an outsized effect on investor ROI.
NOTE: I had to fix some of the parameters to get to the above conclusions. I have tried to do my best to set them at the most reasonable level, but obviously the real world parameters could differ based on a number of factors that don’t necessarily only consider the economic incentives. Regardless of where the remaining parameters land, we still need to address the economic viability of the network under adverse conditions. Analyzing economic viability as a reward distribution problem has been the most obvious way to tackle it.
Let me know what you think or if you have any questions.