Meta-DAO Report for Marinade

Introduction

Today, 40% of Marinade's stake is directed by the votes of MNDE and mSOL holders. Originally, the Meta-DAO intended to build a vote market that allowed MNDE and mSOL holders to trade their voting power for money. However, once we learned about Marinade's internal plans, we realized that our energy was better spent supporting Marinade instead of building a separate system. This report is the culmination of that.

Specifically, we set out to accomplish the following:

• Clarify the system: lay out the system very clearly in its entirety to understand its market structure and to discover any edge-cases.
• Analyze allocation: determine how the marginal revenue earned by the system should be distributed between the Marinade treasury, the MNDE holders, and the mSOL holders.
• Analyze adoption incentives: determine whether Marinade should incentivize adoption of this system, and if so, how. Specifically, we set out to determine whether Marinade should do liquidity mining, and if so, what size and length would be most effective.
• Help validators understand their benefit: provide a calculator program that allows validators to estimate how much they stand to benefit, in dollar terms, by lowering their commission.

These goals were decided upon with Marinade as an appropriate scope of work.

We will now go through each of these topics in order.

Clarify the system

It's helpful to think about Marinade as a SOL-denominated fund. Users deposit SOL in exchange for fund shares (mSOL), and Marinade generates yield with that SOL by staking it to validators. The yield, minus Marinade's performance fee, increases Marinade's NAV (net asset value) and thus the value of the fund shares.

Much as a fund has bargaining power that an individual investor doesn't have, Marinade has bargaining power that an individual staker doesn't have. From an economic standpoint, we can describe Marinade's plans as using its bargaining power to create value for its mSOL holders and the Marinade DAO. Specifically, Marinade will use its bargaining power to:

• get validators to provide insurance on their own yield
• induce lower prices (comission rates) from validators

Further, Marinade intends to introduce a delegation strategy that allows users to benefit from these lower prices by delegating to the normal algorithmic strategy.

Protected staking rewards (PSR)

Validators can go down or set their comission rate to 100%. In the past, this would have lowered Marinade's yield.

In the future, Marinade will be requiring validators to submit 'protection bonds' which hold an amount of SOL equal to the maximum staking yield that Marinade would lose before it could re-delegate to another validator.

We were unable to find any edge-cases in protected staking rewards.

Marinade-specific commission rates

Piggybacking on this bond system, Marinade will be introducing a way for validators to set Marinade-specific commission rate. So if the validator generally uses a comission rate of 6%, they could set a Marinade-specific rate of 4% and have the difference (2%) taken from their bond.

The only thing we found worth pointing out about the Marinade-specific commission rates is that it may be worth allowing for negative commission rates. This is because Solana Foundation matching stake will likely lead to validators being willing to pay Marinade for their stake. For example, if a validator normally charges 10% commissions, they may be willing to pay Marinade up to 9% given that they can profit the difference (1%).

The market structure impact of both

Today, users who don't care about DeFi have a weak incentive to liquid stake. A benefit of liquid staking is diversifying yield, but that can also be achieved by Marinade Native. We believe that protected staking rewards and Marinade-specific commission rates substantially change these incentives and the resulting market structure.

For one, PSR provides an obvious incentive to liquid stake. But less obviously, we also expect it to lead to lower validator commissions. The reason why is simple: previously, the act of staking required a certain amount of trust. You needed to trust that the validator wouldn't go offline or set its commission rate to 100%. The consequence of this is that validators with good brands / reputations were able to attract more stake and to be included in LST pools. But PSR removes that trust assumption, both increasing the homogeneity of the service that validators provide and increasing the threat of new entrants. Industrial organization (IO) economics predicts that both drive down excess returns. So PSR will decrease validator commissions, especially for those validators who depend substantially on the stake of Marinade and other LSTs that add PSR.

The Marinade-specific commission rates also creates a positive feedback loop between its amount of stake, its bargaining power, and its ability to get lower commissions. The more stake Marinade has, the more bargaining power it has. The more bargaining power it has, the more it can get validators to lower their Marinade-specific commissions. The more it can get validators to lower their Marinade-specific commissions, the stronger the incentive to stake in Marinade.

Both of these relationships are depicted below.

Importantly, both also affect the structure of the LST market.

Today, it is relatively easy to spin up a new LST pool and attract stake. This is evidenced by MarginFi's LST attracting $48m in TVL, Jito's JitoSOL attracting $630m in TVL, and BlazeStake's bSOL attracting $215m in TVL. This is a collective $893m in TVL, compared to mSOL's $659m. Much of this can be attributed to the current weak defensabilities in the LST market, which left unchecked could force Marinade to decrease its performance fee.

But once protected staking rewards and Marinade-specific commissions are implemented, it becomes much harder to set up a stake pool that has feature parity with Marinade. For example, if you want to launch with 200 validators in your pool, how do you convince 200 validators to put up protection bonds before you have any stake? And because you will have less bargaining power, validators will be less likely to lower their commissions for you.

In summary, we believe that PSR and Marinade-specific commissions will have three main impacts on the LST and validator market structure:

• PSR will increase the homogeneity of validators and raise the threat of new entrants, forcing them to reduce commissions. It will also increase Marinade's defensability in the LST market.
• Marinade-specific commissions will encourage commission-based competition among validators, also forcing them to reduce commissions and increasing Marinade's defensability.
• Both will increase the incentive to use LSTs instead of staking natively.

New delegation strategy

There is one more component to the system: the new delegation strategy. Today, users can use their MNDE and mSOL to direct stake to individual validators. The new delegation strategy would allow users to direct stake back to the algorithmic strategy.

In exchange for doing this, these delegators would receive a percentage of the marginal revenue generated. How much they should receive is the subject of the next section of this report.

We don't believe that this delegation strategy would change the market structure much. It is simply changing a constant factor (% of stake directed algorithmically) from 60% to something higher like 70% or 80%.

We were also unable to find any edge-cases.

Analyze allocation

How much should the mSOL and MNDE delegators receive? We came to the conclusion that they should receive a similar amount as if there were a bribe platform / vote market. This is because if they don't receive a similar amount, this opens up the opportunity for someone (like us

We can create a general equation for calculating how much delegators should earn by first looking at a specific instance. Suppose that 25% of the MNDE and the mSOL that's directing stake is directing it to the algorithmic strategy. Then 70% of Marinade's SOL would be directed algorithmically, with 60% set as a constant and 10% coming from the new delegation strategy.

Now suppose that Marinade has received 1000 SOL in fee rebates. How should it be distributed? Well, the new delegation strategy was responsible for generating 14.3% of those fee rebates (10 / 70), equivalent to 143 SOL. Any vote market would also have a take rate, and Marinade could also have one if it wished. If the take rate was 5%, this would be equivalent to 135.85 SOL that goes to directors and 7.15 SOL that goes to the DAO treasury. We can generalize this:

directors_receive = fee_rebates * ((directed_algorithmic_pct / (60 + directed_algorithmic_pct)) / 100) * ((100 - take_rate_pct) / 100)

dao_receives = fee_rebates * ((directed_algorithmic_pct / (60 + directed_algorithmic_pct)) / 100) * (take_rate_pct / 100)

Note that take_rate_pct can be 0. We can also generate equations for determining how much the MNDE directors will receive versus the mSOL directors.

mnde_directors_receive = fee_rebates * (((mnde_directed_algorithmically / total_mnde_directed) * 0.2) / (((mnde_directed_algorithmically / total_mnde_directed) * 0.2) + ((msol_directed_algorithmically / total_msol_directed) * 0.2) + 0.6)) * ((100 - take_rate_pct) / 100)

msol_directors_receive = fee_rebates * (((msol_directed_algorithmically / total_msol_directed) * 0.2) / (((mnde_directed_algorithmically / total_mnde_directed) * 0.2) + ((msol_directed_algorithmically / total_msol_directed) * 0.2) + 0.6)) * ((100 - take_rate_pct) / 100)

Figuring out how much SOL rewards an individual director should receive is trivial; it just requires dividing their directed amount by the total amount of that asset (either mSOL or MNDE) directed to the algorithmic strategy.

Analyze adoption incentives

Next, we set out to uncover if and how Marinade should incentivize adoption of this system, such as through liquidity mining. It is our determination that Marinade does not need to use liquidity mining to incentivize validator participation, but that it may be useful to incentivize end-user adoption. If Marinade decides to pursue liquidity mining, the evidence suggests that it should pursue longer small emissions instead of shorter big emissions.

Liquidity mining for validator participation

We believe that Marinade does not need to use liquidity mining to incentivize validator participation. The reason why is that validation is already a fairly commoditized service, and as mentioned above PSR makes it even more commoditized. Validation has all the hallmarks of a competitive market:

• Many competitors: hundreds in Marinade and thousands on Solana
• Homogeneous product: yield is fairly homogenous, and PSR will make it more homogenous by making protection uniform
• Low barriers to entry: the barriers to entry of setting up a new validator are much lower than in most markets

While it's true that Marinade's focus on geographic decentralization makes the product slightly less homogenous, we believe that this is outweighed by the above three. So if validators are incentivized to participate, especially if they have a calculator that shows them at what level they should set fees to maximize their yield, they will participate.

Liquidity mining for users

End-users, on the other hand, are a different story. Marinade's typical user may not be super active in DeFi, and many of them have not even heard about directed stake. But them directing to the algorithimic strategy would be beneficial to Marinade for a few reasons:

• It would likely raise the mSOL APR
• If Marinade does take a take rate, it would increase the funds available to the DAO
• It could boost the geographic decentralization of Marinade and Solana, one of Marinade's stated aims

So it would be good for end-users to direct algorithmically and liquidity mining has been demonstrated to be effective for Marinade in the acquisition of users.

Long and small instead of short and big

Given an amount of MNDE to be used for liquidity mining, Marinade can either distribute that MNDE over a short period ('short and big') or a long period ('long and small').

We did some empirical research on previous liquidity mining programs, displayed in the appdendix, and it's evident that long and small beats short and big. This comes back to the key driver of Marinade's long-term profitability and sustainability: stickiness of stake. With liquidity mining, we want to help push prospective users over the hump of initial adoption, not attract mercenary farmers who will leave the second the rewards are done. We found that long and small is better at attracting sticky TVL than short and big.

This makes sense intuitively as well. The users who are constantly monitoring for the best yields and show up to your short liquidity mining program are also likely going to be the first to leave once the program is done. The most ideal stakers are those who only return to Marinade's website once a year, and a month-long liquidity mining program is going to be filled disproportionately with active rather than sticky stakers. The most successful programs have been those that are run for multiple years. We recommend planning as if Marinade will need one year or more of liquidity mining to attract significant directors, and not spending lots of MNDE early on.

Calculator

TODO, waiting on LJ

Conclusion

The Meta-DAO set out to clarify the system, analyze allocation, analyze adoption incentives, and help validators understand their benefit. To summarize the insights:

• It may be worth allowing negative commission rates to allow validators to pay for stake given the Solana Foundation's stake matching program.
• Protected staking rewards (PSR) and Marinade-specific commission rates could both substantially change the structure of the LST market.
  • While today's LST market doesn't have many structural defensabilities, as evidenced by new entrants like BlazeStake gaining adoption, both would make it harder for upstart LST providers to compete with Marinade.
  • PSR makes validation a commodity, which will likely lower commission rates.
  • Marinade-specific commissions will likely increase flows from native staking (not necessarily Marinade Native) into mSOL because Marinade can exercise bargaining power to lower commissions while individual stakers cannot.
• We don't expect the new delegation strategy to have any structural impacts on the LST market.
• mSOL and MNDE delegators to the new strategy should receive a similar amount to what they would earn if a bribe platform exists. The equations for calculating this are detailed above.
• We don't believe it makes sense to run a liquidity mining program for validators, but it could make sense to run one for delegators to this new strategy. If so, we recommend that the mining rewards be spread out over a long period of time, possibly multiple years.

Once we receive an updated delegation algorithm, we should be able to create a calculator program that allows validators to estimate their benefit from setting a Marinade-specific commission.

Appendix - Liquidity Mining Research

As a part of the Meta-DAO's report to Marinade, we recommend that Marinade use liquidity mining to attract stake to the new delegation strategy. We also recommend that Marinade opt to spread the incentives over a long period of time, even if that means lower APR. This is the research that we used to come to the latter conclusion.

Methodology

Simply, we wanted to ascertain whether it was better to have smaller incentives over a longer period of time ('long and small') or bigger incentives over a shorter period of time ('short and big').

To do so, we used two main strategies:

• First principles reasoning: determine exactly what would make for a 'good' liquidity mining program and form hypotheses on which length is better.
• Empirical evidence: use data from past liquidity mining programs, both on Ethereum and Solana, to test these hypotheses.

Unfortunately, the empirical evidence wasn't as robust as we'd like. For example, some of the longest DeFi LM programs have been run by early protocols. It's unclear whether their growth was due to their liquidity mining or simply being early. The other challenge was collecting good data: although protocols generally announce when they start liquidity mining programs, they scarcely announce when they end them.

Still, some data is better than no data! But we will contextualize it, using metrics like overall DeFi growth over the period of the LM program to determine how much of the sticky capital the LM program was responsible for.

First principles reasoning

Traditional liquidity mining has been criticized as encouraging mercenary capital that flees the moment rewards dry up.

Balancer Labs

A successful “Trade Mining” program requires the two following statements to hold true:

• Sybil Resistance - The incentives program must be difficult or impossible to exploit
• Inelastic Users - Users tend to be “sticky” and continue using the product after incentives are removed

Gauntlet

When done correctly, a liquidity mining program attracts sticky users. When done incorrectly, a liquidity mining program attracts mercenary users who leave the second the program is done. While the latter group may improve a protocol's metrics (e.g., TVL) in the short-term, the protocol is by definition a net-loser to them because those users wouldn't have shown up unless the LM (and thus the dilution) was greater than any required fees. So we want to attract future sticky users.

So let us ask: what does a sticky user look like? We think that these traits are correlated with stickiness:

• Low engagement in DeFi: highly-engaged users tend to always know which farms are the most profitable and to exploit those opportunities. Users without the time or a strong enough interest will not know about as many of these opportunities and will be more inclined to 'set it and forget it.'
• Relatively low sophistication: while any interaction with DeFi requires a basic level of sophistication, highly-sophisticated users are less likely to stick with a given brand based on trust alone.
• Price-insensitive: those who are less price sensitive are by definition okay paying more fees in order to gain convenience.

From this archetype, we can hypothesize that 'long and small' would be better for this type of user. Since they are price-insensitive, they will be okay receiving less rewards. And since they have low engagement in DeFi, they may not even see a 'short and big' program.

On the other hand, we can also see how a 'short and big' strategy would be perfect for attracting the type of mercenary capital that we don't want. Since the mercenaries are highly-engaged, they will be likely to see the announcement. Since they are price-sensitive, the big APR boost would significantly impact their behavior.

Gauntlet agrees that short-term programs are likely to attract less sticky TVL:

One possible theory for a sustained lift from a liquidity mining program is through forgetful LPs. If liquidity is supplied to capture incentives and left unmonitored, it may remain unmoved for some time after the program ends.

This may be observable in some long-lasting liquidity mining programs but is unlikely to be observed in such a short-term (several weeks) program where the end date of the program was known from the start.

Gauntlet

Empirical data

We were able to collect data on 8 protocols. Here is that data:

This data seems to confirm our hypothesis.

Both of the short LM programs (Uniswap Optimism and Yearn) were able to attract significant TVL while the program lasted, but the TVL didn't stick. Since the end of Yearn's program, its TVL has increased 41% while all of DeFi grew 900%.

On the other hand, the multi-year programs appear to be successful. Although it's hard to determine how successful the Compound and Balancer programs are at attracting sticky liquidity given that the programs are currently ongoing, both have tracked overall DeFi growth - slightly underperforming it in Compound's case and outperforming it by 4x in Balancer's case. Synthetix is a better datum because they finished their LM program. Since then, only 1% of TVL has left, albeit in a time that DeFi TVL grew 8%.

And when we look at the medium-term liquidity mining programs, it's a mixed bag. It looks like Solend and Aave's programs were moderately successful at attracting sticky TVL. Convex, on the other hand, has performed exceptionally poorly, with their current TVL at only 8% of their post-LM TVL (DeFi TVL is currently 35% of what it was when they finished their program).

Essentially:

• Both short-term programs were unsuccessful at attracting sticky TVL.
• The three multi-year programs were successful at attracting sticky TVL.
• The three medium-term programs were moderately successful to completely unsuccessful at attracting sticky TVL.

So there appears to be a positive relationship between the length of the program and the stickiness of attracted TVL.

Conclusion

We set out to determine whether it would be better for Marinade to have a longer LM program with proportionately smaller rewards or a shorter LM program with proportionately larger rewards. Having reasoned through this question and analyzed empirical data, it is our determination that a longer LM program with proportionately smaller rewards would be better for Marinade.

References

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