SummerFi Lazy Summer Protocol - Initial Fleet and Ark Parameters by Block Analitica

[BlockAnalitica]

SummerFi Lazy Summer Protocol - Initial Fleet and Ark Parameters by Block Analitica

Block Analitica has developed a risk curation framework to optimize risk-adjusted yields across Arks, Lazy Vaults, and ultimately the Lazy Summer Protocol as a whole. The goal is to achieve balanced risk management, liquidity optimization, and scalable deployment. Our approach is intended to evolve over time based on market conditions and new data.

Risk Measures

For the risk assessment of each ark, we primarily implemented financial risk metrics along with security audit scores to compute a risk premium for each ark. The key variables considered are compound collateral volatility, compound collateral tier (based on security), existing depth liquidity in DEXs, and rehypothecation risk. The collateral tier risk evaluates the reliability of assets backing the debt on each lending protocol. Below, we explain how these metrics are aggregated to compute the final risk score.

Ark Compound Volatility

This metric accounts for the debt-weighted total volatility of the collateral, providing an estimate of how secure the loans are in case of high price volatility.

Compound Collateral Tier

We define a tier system where assets are ranked based on security audits from Certik and CyberScope. Similar to volatility, we debt-weight the tier for each protocol/ark and determine the compound collateral tier.

Liquidity Depth & Rehypothecation

Liquidity depth is associated with the potential lack of liquidity in DEXs, particularly in cases where liquidations occur and markets fail to absorb the losses.

Rehypothecation is a more complex variable to assess accurately. For now, we flag protocols that allow rehypothecation by assigning a value of 1 and 0 for those that do not. We weigh this factor when computing the total risk to ensure it contributes up to 10% of the overall risk score.

Final Risk Score Calculation

We combine the described risk metrics to reflect the ark’s overall risk. The risk metrics are aggregated and normalized. For example, if an ark’s collateral is at least tier 2 and exhibits a price volatility of over 40%, its risk score is already ~55%. Rehypothecation can add up to 10%, and if all assets are illiquid, the total score may exceed 90%.

It’s important to note that additional metrics will be incorporated to improve our risk assessment. We will make forum posts when new parameters need to be updated.

Available Liquidity and Utilization

We have gathered key metrics from lending protocols, including total supply, liquidity before the kink, utilization ratios, and overall health, to set each ark’s maxDepositCap. These caps are risk-adjusted based on the risk metrics discussed earlier.

The rebalanceMaxInFlow and rebalanceMaxOutFlow parameters are set to ensure that capital flows gradually into riskier arks, while allowing faster inflows to safer ones. Initially, rebalanceMaxOutFlow is set so that keepers can withdraw all capital from an ark if they deem it necessary.

Percentage of Vault TVL & Adjusted max Deposit Cap

The percentage of vault TVL is designed to encourage diversification, rather than capping assets purely based on market risk, which is handled by maxDepositCap. However, the two parameters remain correlated. The initial calculation considers current APY trends, adjusted for risk, and a correlation factor (~80%) to ensure deposit caps reflect risk exposure.

Scaling Down - New Deployment

With all above in taken into account, we are proposing starting with lower fleet caps and will gradually increase them over time as the protocol matures.

Watchdog Automated System

We are developing an automated monitoring system to track the collateral backing the debt in each market used by the fleets. If any collateral depegs or experiences significant price changes, the system will automatically set the maxCap for that ark to 0. This will immediately trigger Keepers to withdraw all capital from the ark, ensuring rapid risk mitigation.

Parameters

The parameters based on our risk models and market metrics are the following:

Fleet Mainnet - ETH

chain	fleetAsset	fleetCap	FleetMinimumBuffer
ethereum	ETH	5,600	0.37

With arks:

Ark	Symbol/Vault	maxCap	Max. %TVL	maxInflow	maxOutflow
morpho	morpho_gauntlet_weth_prime	6,000	37.0%	290	2,100
morpho	morpho_flagship_weth	0	0.0%	0	0
morpho	morpho_re7_weth	0	0.0%	0	0
morpho	morpho_steakhouse_weth	2,100	35.0%	110	2,000
aave_v3	WETH	190,000	100.0%	9,100	5,600
compound_v3	WETH	14,000	41.0%	470	2,300
fluid	WETH	28,000	47.0%	580	2,700
gearbox	WETH	2,800	36.0%	59	2,000
euler	euler_prime_weth	0	0.0%	0	0
spark	WETH	52,000	58.0%	2,100	3,300

Fleet Mainnet - USDC

chain	fleetAsset	fleetCap	FleetMinimumBuffer
ethereum	USDC	15,000,000	1,000

With arks:

Ark	Symbol/Vault	maxCap	Max. %TVL	maxInflow	maxOutflow
morpho	morpho_gauntlet_usdc_core	36,000,000	33.0%	1,044,000	5,000,000
morpho	morpho_flagship_usdc	0	0.0%	0	0
morpho	morpho_steakhouse_usdc	28,300,000	33.0%	684,000	4,900,000
morpho	morpho_gauntlet_usdc_prime	9,500,000	32.0%	297,000	4,800,000
morpho	morpho_smokehouse_usdc	12,700,000	33.0%	648,000	4,900,000
morpho	morpho_usual_boosted_usdc	0	0.0%	0	0
morpho	morpho_re7_usdc	0	0.0%	0	0
aave_v3	USDC	1,020,000,000	77.0%	7,920,000	11,500,000
compound_v3	USDC	87,000,000	35.0%	3,438,000	5,300,000
fluid	USDC	94,000,000	35.0%	1,116,000	5,300,000
gearbox	USDC	5,400,000	32.0%	136,800	4,800,000
euler	stablecoin_maxi_usdc	0	0.0%	0	0
euler	euler_prime_usdc	3,700,000	32.0%	97,200	3,700,000
euler	euler_yield_usdc	0	0.0%	0	0
spark	USDC	440,000	32.0%	14,580	440,000
sky	sUSDS	1,430,000,000	95.0%	23,220,000	14,300,000

Fleet Mainnet - USDT

chain	fleetAsset	fleetCap	FleetMinimumBuffer
ethereum	USDT	15,000,000	1,000

With arks:

Ark	Symbol/Vault	maxCap	Max. %TVL	maxInflow	maxOutflow
morpho	morpho_flagship_usdt	194,000	33.0%	15,120	194,000
morpho	morpho_steakhouse_usdt	25,100,000	36.0%	565,200	5,400,000
morpho	morpho_gauntlet_usdt_prime	1,820,000	33.0%	47,160	1,820,000
morpho	morpho_re7_usdt	0	0.0%	0	0
morpho	morpho_smokehouse_usdt	1,400,000	33.0%	33,300	1,400,000
aave_v3	USDT	610,000,000	100.0%	8,640,000	15,000,000
compound_v3	USDT	24,300,000	36.0%	1,278,000	5,400,000
fluid	USDT	87,000,000	47.0%	1,782,000	7,000,000
gearbox	USDT	1,780,000	32.0%	33,840	1,780,000
euler	euler_prime_usdt	7,800	34.0%	558	7,800
euler	euler_yield_usdt	0	0.0%	0	0
spark	USDT	490,000	32.0%	11,700	490,000

Fleet Base - USDC

chain	fleetAsset	fleetCap	FleetMinimumBuffer
Base	USDC	7,500,000	100

With arks:

Ark	Symbol/Vault	maxCap	Max. %TVL	maxInflow	maxOutflow
morpho	morpho_gauntlet_usdc_core	1,670,000	36.0%	2,230	1,670,000
morpho	morpho_steakhouse_usdc	900,000	35.0%	1,570	900,000
morpho	morpho_gauntlet_usdc_prime	1,640,000	36.0%	2,740	1,640,000
morpho	morpho_re7_usdc	0	0.0%	0	0
morpho	morpho_moonwell_usdc	0	0.0%	0	0
morpho	morpho_spark_usdc	17,300,000	58.0%	22,900	4,300,000
aave_v3	USDC	54,000,000	100.0%	42,000	7,500,000
compound_v3	USDC	2,770,000	37.0%	5,400	2,770,000
fluid	USDC	6,800,000	43.0%	5,700	3,200,000
sky	sUSDS	8,000,000	46.0%	47,000	3,400,000

Fleet Arbitrum - USDT

chain	fleetAsset	fleetCap	FleetMinimumBuffer
Arbitrum	USDT	7,500,000	100

With arks:

Ark	Symbol/Vault	maxCap	Max. %TVL	maxInflow	maxOutflow
aave_v3	USDT	27,300,000	100.0%	36,000	7,500,000
compound_v3	USDT	4,500,000	53.0%	11,900	4,000,000
fluid	USDT	5,300,000	55.0%	4,000	4,200,000

[Javier]

Welcome @BlockAnalitica

[FBrinkkemper]

Hey @BlockAnalitica thanks for the initial parameters and high level explanation.

Understand it’s early days, but would it be possible to provide more transparency to the exact metrics and formulas used?

Looking forward to engaging in making lazy yields sustainable for all.

[BlockAnalitica]

Hey @fbrinkkemper, thanks for raising awareness about the transparency of the model. We’re sharing additional information around the initially proposed framework below.

Risk Assessment Metrics

Ark Compound Volatility:

where is the volatility of each asset backing the protocol’s debt, and is the collateral amount on the respective asset, and is the total collateral.

Compound Collateral Tier

A weighted average of the collateral quality (tier):

We define a tier system where assets are ranked according to their security audits, using CertiK and CyberScope as references. A score of 0 indicates a safe asset, while 5 means it is unsafe. Similar to volatility, we weight the tier by debt on the specific protocol/ark to determine the compound collateral tier.

Liquidity Risk & Rehypothecation

Liquidity risk arises when DEXs lack sufficient liquidity, particularly during liquidations, causing markets to be unable to absorb losses. To quantify this, we introduce a scaled variable . Aggregating across all collaterals, we obtain:

We define the liquidity risk metric as:

The factor 3 ensures that if all collaterals fail to meet liquidity requirements, the risk metric approaches 90%. This factor can be fine-tuned to align with the target risk profile. The square function approximates the effects of concentrated liquidity in DEXs like Uniswap, where slippage increases non-linearly with swap size.

Rehypothecation is more complex to assess accurately. For now, it is flagged with a value of 1, otherwise 0. We introduce later a ⅙ factor in the total risk formula to ensure rehypothecation contributes a maximum of 10% to overall risk. Future iterations will refine this metric for improved accuracy.

Risk Score

The overall risk score aggregates the described risk metrics as follows:

It is then normalized:

For example, if the backing assets have at least tier 2 security and exhibit 40%+ volatility, the ark already presents a risk score of 55%. Rehypothecation can add up to 10%, and if all assets are illiquid, the score can exceed 90%.

Additional metrics can always be incorporated into the r formula. The normalization of R ensures compatibility with the rest of the model when determining ark and fleet parameters.

Liquidity and Utilization

We have also gathered key metrics from the lending protocols associated with current liquidity and overall health:

1. totalSupply, totalBorrow
2. liquidityBeforeKink: The available liquidity before utilization reaches the kink.

Ark-Level Parameters

At the ark level, we compute parameters as follows:

Where R is the risk score, and U is the utilization. This means we do not recommend providing significantly more liquidity than is currently available in the market, as this could adversely affect supply rewards, and in case of liquidations, more capital could be at risk.

In the relations above, t is associated with the rebalance cooldown period. Note that this initial set of parameters is individual for each ark and does not take into consideration that multiple arks are present in the same fleet.

Percentage of Vault TVL & Adjusted max Deposit Cap

We now adjust previously computed values based on fleet composition. The percentage of vault TVL represents diversification rather than a strict liquidity cap but should correlate with the max deposit cap. First, we adjust the maximum deposit cap per ark:

Since no historical data exists for the new system, we set default values: $1,000 for all mainnet fleets, and $100 for the L2’s.

With adjusted deposit caps, we compute the final vault deposit cap:

To compute vault TVL percentages, we define a risk-adjusted reward mechanism and a capping mechanism:

Thus, after determining the individual , we aggregate, normalize, and introduce an adjustable parameter for fleet-level optimization:

The factor gamma in the square root is an added parameter to adjust depending on the keepers risk profile, for now being set to 2. Narks denotes the number of arks in each respective fleet.

Scaling Down - Safe Initial Conditions

Based on current market conditions, the vault caps can be higher, but for safety reasons, we limit the total of all vaults capital to $60M, $15M for each mainnet fleet, and $7.5M for the L2’s. These limits are expected to increase over time.

Please keep in mind that the risk assessment and liquidity framework is an iterative model that will evolve over time. As new market conditions emerge, additional data becomes available, and more advanced methodologies are developed, we will refine these parameters to enhance accuracy and efficiency. Future iterations may introduce more precise rehypothecation metrics, dynamic liquidity adjustments, and adaptive weighting mechanisms to optimize risk management across arks and fleets.

[0xtucks]

Hey BlockAnalytica team, thanks for the detailed breakdown.

One observation: the current max in flows and cooldown periods might be a bit too restrictive. If they’re set too low or the cooldowns are too short, it means that our rebalancing mechanics aren’t nimble enough to react to fast-moving market conditions.

Also, to help fleets bootstrap more effectively and chase competitive yields, maybe we could look at temporarily increasing the max in limits or adjusting the cooldown periods.

I feel like the max in and out flows should be more closely aligned than currently.

Curious to hear your thoughts on this tweak!

[BlockAnalitica]

Hey @0xtucks,

thanks for bringing this up. We are trying to balance flexibility in reallocations and risk mitigation.

We are currently making adjustments to both the cooldown period and the maxInFlow caps.

[BlockAnalitica]

Hey @0xtucks, arkMaxInFlow and reallocInterval parameters have been adjusted as the following:

arkMaxInfow: either equal to the arkMaxOutFlow, or max 20% of the fleet cap
reallocInterval: 10min