1/ Today, we take a deep dive into our Morpho vault curation strategy. 🔎

Since mid-March, we’ve launched a dozen Gauntlet-curated Morpho vaults that generate risk-adjusted yield by providing exposure to lending markets with varying risk profiles.

In this thread, we'll cover:

🔹 Morpho Vault Structure
🔹 Market Allocation Strategy
🔹 Strategic Adjustments

🧵👇 2/ First, let's cover how we categorize our vaults:

Prime vaults primarily allocate liquidity to blue-chip markets and maximize risk-adjusted yield while targeting a minimal risk of insolvent debt.

Core vaults offer exposure to markets with higher yields that may come with incrementally more risk.

Explore all Gauntlet-curated vaults here: app.gauntlet.xyz/protocols/meta…

1/ A few weeks ago, we published a thread on AVS allocation research we've been doing for @ether_fi. Today, we publish the full report!

The report covers:

1️⃣ AVS commitments
2️⃣ Impacts of adding AVSs
3️⃣ Optimal allocations to ensure $eETH maximizes risk-adjusted yield

👇🧵 @ether_fi 2/ Given payments and slashing are not live, this framework remains theoretical.

We start off by determining an initial restake per operator given @ether_fi's existing commitments and operator set.

1/ We added additional LRT and LST markets to the Gauntlet LRT Core MetaMorpho vault on @MorphoLabs to diversify collateral risk and optimize for yield.

Newly added markets are outlined below 🧵👇 @MorphoLabs 2/ $pufETH, a native LRT by @puffer_finance, generates restaking rewards through native restaking on @Eigenlayer.

Details: the pufETH/WETH market has an LLTV of 86%, an initial supply cap of 1,000 WETH, and uses the @redstone_defi market rate oracle.

1/ With LRTs continuing to garner significant adoption, a framework for evaluating risks is paramount for users to understand the market risk landscape for each token.

Today, we published a blog on LRT market risk as part of our partnership with @EigenLayer.

Let's dive in👇🧵 2/ Our LRT Risk Framework is broken down into 4 attributes:

1️⃣ External Liquidity
2️⃣ Withdrawals
3️⃣ Volatility
4️⃣ DeFi Risk

Read on for more on how we define and evaluate these.

🚀We are excited to launch our @synthetix_io Risk Dashboard!

The dashboard will help the community understand how Gauntlet’s recommendations mitigate risk and increase capital efficiency for the protocol👇

gov.gauntlet.network/synthetix Gauntlet has now built the infrastructure to ingest market data and run simulations and economic stress tests on the @synthetix_io ecosystem.

Our mission is to drive understanding and participation in the financial systems of the future.

We're hiring across the board to do so!

https://twitter.com/sonalibasak/status/1503431628496027649

How hard are these problems? tl;dr very hard

"We are taking on the formidable engineering challenges associated with building predictive models of aggregate user behavior across DeFi" @ChiangRei, Co-Founder / CTO. "We leverage our Agent Based DSL to run thousands...

Given the astounding run-up in $AMPL price and market cap, much has been said about its mechanism.

We took a closer look at AMPL — analyzing the token's historical and trading behavior observed across exchanges.

gauntlet.network/reports/amplef… We explored strategies that AMPL traders might build upon, particularly around rebase events.

From this analysis, we observed what you might expect: rebase events have in practice driven traders to trade around them (there is an increase in trading before & after the event).