Risk Parameter Updates 2022-06-15

Simple Summary

A proposal to adjust two (2) parameters for two (2) Compound assets.


Gauntlet’s simulation engine has ingested the latest market and liquidity data following the recent market crash. This proposal is a batch update of risk parameters to align with the Moderate risk level chosen by the Compound community. These parameter updates are the thirteenth of Gauntlet’s regular parameter recommendations as part of Dynamic Risk Parameters.


This set of parameter updates seeks to maintain the overall risk tolerance of the protocol while making risk trade-offs between specific assets. Gauntlet recently published a blog post on our parameter recommendation methodology to provide more context to the community.

Our parameter recommendations are driven by an optimization function that balances 3 core metrics: insolvencies, liquidations, and borrow usage. Our parameter recommendations seek to optimize for this objective function. Gauntlet’s agent-based simulations use a wide array of varied input data that changes on a daily basis (including but not limited to user positions, asset volatility, asset correlation, asset collateral usage, DEX/CEX liquidity, trading volume, expected market impact of trades, liquidator behavior). Our simulations tease out complex relationships between these inputs that cannot be simply expressed as heuristics. As such, the charts and tables shown below may help understand why some of the param recs have been made but should not be taken as the only reason for recommendation. Our individual collateral pages on the dashboard cover other key statistics and outputs from our simulations that can help with understanding other interesting inputs and results related to our simulations.

Top 30 non-recursive and partially-recursive aggregate positions

Top 30 non-recursive and partially-recursive borrowers’ entire supply

Top 30 non-recursive and partially-recursive borrowers’ entire borrows

Top USDC non-recursive supplies and collateralization ratios:

Note that the above top 3 non-recursive USDC suppliers entirely borrow either USDT or TUSD, and thus pose low liquidation and insolvency risk given their collateralization ratios.

Top DAI non-recursive supplies and collateralization ratios:

Note that the above symbol-specific charts show the positions that are entirely non-recursive (i.e., don’t supply and borrow the same assets) and have collateralization ratios less than 10. The recursive and partially recursive positions, and more highly collateralized positions, are still incorporated into our simulations.


Our recent market downturn report showed that many collaterals are resilient to insolvencies, as our simulation models have predicted. We will continue to adjust risk parameters to drive increases in capital efficiency while maintaining protocol risk at safe levels. Parameter recommendations are ordered by descending cToken collateral locked.

Parameter Current Value Recommended Value
USDC Collateral Factor 84% 85.5%
DAI Collateral Factor 82.5% 83.5%


The community should use Gauntlet’s Risk Dashboard to understand better the updated parameter suggestions and general market risk in Compound.

When making recommendations, Gauntlet takes into account the entire distribution of insolvencies and liquidations from our simulations and weighs them against increases in borrows. The below metrics give the community insight into some of the insolvency and liquidation tail risks the protocol could face and Capital Efficiency improvements the protocol stands to gain. Click the collateral-specific pages linked in the Collateral Risk section for more detailed simulation metrics.

Value at Risk represents the 95th percentile insolvency value that occurs from simulations we run over a range of volatilities to approximate a tail event.

Liquidations at Risk represents the 95th percentile liquidation volume that occurs from simulations we run over a range of volatilities to approximate a tail event.

These parameter changes increase borrow usage by 11 basis points with no change in Value at Risk or Liquidations at Risk.

Next Steps

While Gauntlet expects to initiate a governance proposal for this set of parameter recommendations on Sunday, 6/19 (voting to begin 2 days later), we will cancel the vote should changes in our daily simulations dictate it necessary.

By approving this proposal, you agree that any services provided by Gauntlet shall be governed by the terms of service available at gauntlet.network/tos.


For awareness @blockchaincolumbia @pennblockchain @getty @hayesgm @monet-supply @JacobPPhillips @rleshner @blck @Sirokko

This proposal will go live by end of day tomorrow. Please raise objections in advance.

My concerns are generally the same. I believe that in current market conditions it might be reasonable to put a hold on increase on CF as it in general allows users to take more risk. Even while i don’t expect any dire consequences from proposed increase i think protocol should be at more conservative side ATM. Given that we are now in massively different situation and quite a lot of time passed from initial polling. I think it’s reasonable to ask Gauntlet to run simulations for all markets and present full table, similar as you did in October for Conservative, Moderate and Agressive strategies prior to moving further forward in pursue of current Moderate risk strategy. Maybe that’s time to slowdown a bit.

Thanks, @Sirokko - we run simulations on the entire market and find opportunities on an asset-specific level to make risk/capital efficiency tradeoffs to optimize the protocol. On our dashboard, you can click on each asset and see the impact of these parameter changes on VaR, LaR, and capital efficiency for each Compound collateral asset. We appreciate your feedback on conservative/moderate/aggressive strategies and will consider how to provide more color moving forward. For context, our simulations recommended increasing USDC to 87%. Given the historic friction of a risk-off approach we are recommending a smaller increase to 85.5% and then analyzing how market conditions evolve afterward.

To give people more time, we will be publishing the on-chain vote on Sunday 6/26 @blockchaincolumbia @pennblockchain @getty @hayesgm @monet-supply @JacobPPhillips @rleshner @blck

Maybe i wasn’t explicit enough. I was referring to octoder 21 poll. When Gauntlet initially asked community to chose risk profile Moderate risk level And at that time, mind you, community was presented with that:

Current Collateral Factor (Current CF) Conservative CF Moderate CF Aggressive CF
AAVE (50%) 55% 60% 70%
BAT (65%) 60% 65% 65%
COMP (60%) 55% 60% 60%
DAI (75%) 75% 75% 80%
ETH (75%) 75% 75% 80%
LINK (50%) 50% 60% 65%
MKR (35%) 40% 50% 65%
SUSHI (40%) 40% 50% 65%
UNI (60%) 60% 60% 65%
USDC (75%) 70% 80% 80%
WBTC (65%) 60% 65% 70%
YFI (35%) 45% 50% 60%
ZRX (65%) 60% 65% 65%

As you see, at that time Moderate Risk And Agressive Risk for USDC was 80 CF. Now, over 6 month later, with rate hiking, QT on the way, inflation at the highs of the decades, and war in europe you saying that your model show Moderate risk will be CF 87. Well, let’s take it does. What will be the numbers for Agressive then and for Conservative approach? The point here is: It might be time for community to switch the gear for the lower speed. And for that it would be good to see alternative numbers your model could provide with different risk parameters.

Personally i don’t think increasing CF will increase borrow at all in current market conditions, and thus, your point of increasing efficiency is moot. What it will do, it will increase risk for users, who now going to be liquidated at lower price levels, likely loosing more money in process. I see that it might have some benefits for particular borrowers as increased CF might give them more breathing room in case of further downfall of crypto markets.

I’m still open in general to possibility of further CF increases, but we are now living in totally different world than 6 month ago which no doubt is translating on crypto markets too. I believe it deserves whole picture, rather than just following your mandate recieved on very different circumstances. Hope that cleared what i was asking you enough. Cause as for now it really just looks like Gauntlet is pushing CF only up according to model. And even if Compound house isn’t on fire currently, the whole neighboorhood arount that house is already burning. And i just can’t stop wondering, shouldn’t we be more conservative here, even if it translates in lower efficiency. You know, just in case.

Thanks, @Sirokko . Regarding your point on capital efficiency: at its core, these parameter changes enable users to take on more leverage. How users actually use the protocol is not in Gauntlet’s control. One could make the point that by making capital efficiency more competitive, more users could create new positions, but that is heavily dependent on other factors (i.e., what assets are listed, how much liquidity there is, what is the utilization of asset, rewards, etc.). If you have predictions on usage, we’d be interested in hearing the supporting data. As for the macroeconomic events, we do not speculate on their impact on Compound usage. Simply, we ingest the current data and current usage of the platform. Our models observe a relatively low amount of market risk on Compound even in an adverse market shock. If risk levels were to spike, we would turn down collateral factors accordingly. Again, given the historic friction of a risk-off approach, we are recommending smaller increases in CF than the results of our simulations and then analyze how market conditions evolve afterward.

We appreciate your thoughts on the community’s risk tolerance preference. We’d love to hear the community chime in on this and whether people prefer to be more conservative.