Matched Funding
Overview
This wiki page describes the ‘Matched Funding’ scheme, in which the contribution of the Neurons’ Fund to SNS swaps scales in line with direct participation, allowing for a more accurate reflection of market signals.
In addition, the page also outlines the separation of contributions from direct participants and the Neurons’ Fund. In the Matched Funding framework, the minimum and maximum funding targets of an SNS swap are specifically set for direct participation. This means that the success of a swap only depends on the level of direct participation, not the contributions from the Neurons’ Fund.
The Matching function, f
The scheme is implemented through a matching function f, where the input x represents the amount of direct participation, and the output f(x) denotes the corresponding contribution from the Neurons' Fund (NF).
The function f is designed to have three distinct phases and will be a continuous function to ensure a smooth transition between these phases. Importantly, the rules for these phases will be globally consistent, applicable to all SNS launches.
- Initial Lag Phase (I): The function starts at 0, and grows slowly until it reaches a set threshold. This design encourages projects to accumulate enough direct participation before receiving substantial contributions from the NF.
- Growth Phase (II): After crossing the threshold, the NF's contribution increases at a faster rate, signifying more significant support for projects that have demonstrated viability through direct participation.
- Saturation Phase (III): Beyond a certain point, f(x) will level off and will not surpass 10% of the NF's total maturity, which ensures that no single SNS will excessively deplete the NF's resources.
- Bounding Condition: The matching function f(x) is bounded by g(x)=x, meaning that it will never exceed a 1:1 ratio with x. In practical terms, the NF's contribution will always be less than or equal to the amount of direct participation.
- Audability: The shape of f (which can change over time due to varying NF size) should be audible.
These design principles aim to create a fair and sustainable system for allocating NF contributions to various SNS initiatives.
Benefits of matched funding
Better Reflection of Market Signals
The matched funding system is designed to closely align with market sentiment. Specifically, a project that successfully raises more direct contributions will correspondingly receive a greater contribution from the Neurons' Fund (NF), up to a predetermined threshold.
Simpler Decision-making for NF NNS Neurons
The automated adjustment feature in the NF's contributions lessens the decision-making burden on NF NNS neurons. As a result, these neurons have fewer instances where they need to opt out, making the process more efficient.
Improved Incentives for Projects
The matching system provides a more compelling incentive structure for projects. Knowing that increased direct funding will be matched (up to a point) by the NF, encourages projects to be more proactive in their fundraising efforts.
Detailed specification of the matching function
Cap
The contribution should be capped by 10% of the NF maturity at proposal execution time and also by a global NF contribution cap being equivalent to 0.75M XDR. In other words we have cap = min (10% of NF maturity, global NF contribution cap)
The global NF contribution cap is a configurable parameter of the NNS.
Thresholds
For specifying the shape of the matching function f, we define the following thresholds
- t_1: Up to this point, a project receives no contribution from the NF.
- t_2: Projects get a 2:1 contribution from the NF.
- t_3: Projects receive a 1:1 contribution from the NF.
- t_4 = 2 * cap: Projects get a 2:1 contribution from the NF. (and afterwards the contribution of the NF remains flat).
The thresholds should be configurable parameters of the NNS. For example they could be part of the NetworkEconomics record.
These thresholds are specified in XDR and then converted to ICP thresholds at the execution of the SNS swap proposal using the 30-day average ICP/XDR conversion rate.
- t_1: 75k XDR
- t_2: 225k XDR
- t_3: 375k XDR
Matching function polynomials
The matching should be realized by set of polynomials
- f_1: for function values between t_1 and t_2
- f_2: for function values between t_2 and t_3
- f_3: for function values between t_3 and t_4.
Formulas for the polynomials can be derived from constraints listed above on the functions f and f’.
Clearer separation of contributions
Feedback from both SNS projects and users has highlighted the need for a clearer separation between contributions from direct participants and those from the NF. This is now realized in two areas:
- Proposal Structure: Instead of specifying the overall minimum and maximum funding target, projects have the ability to set distinct minimum and maximum funding targets specifically for direct participation, which is the only factor determining whether the swap succeeds. The contribution from the NF is then added to this base amount, determined by a well-defined model (as per the matching function discussed above).
- User Transparency in the SNS Launchpad: During the swap, contributions from direct participants and the NF are displayed separately for transparency, within the NNS dapp’s SNS launchpad.
Benefits of the clearer separation
- Transparency in Success Metrics: The success of the swap is directly and transparently linked to the amount raised through direct participation.
- More freedom to define funding target range: Projects can set a more flexible range for minimum and maximum funding targets without having to factor in the NF contribution, offering more leeway than in the current system where the NF contribution affects these limit (e.g. because the fixed NF contribution should exceed more than 66% of the minimum funding target).
- User Clarity: Users will be able to easily see the amount of direct participation already collected during the swap, as well as the anticipated NF contribution.