Back
Omer Goldberg
Omer Goldberg

dYdX Maker Liquidity Rewards Distribution Report

Cover Image for dYdX Maker Liquidity Rewards Distribution Report
  1. 🔍 Overview
  2. Abstract
  3. Introduction
  4. 📉 Liquidity Provider Rewards Program
  5. Q-Score
  6. Analysis of Q-Score Historical Performance
  7. Preliminary Evaluation of G Score & Capping based on Historical Data
  8. G-Score Analysis
    1. 1. Over-compensation Risk
    2. 2. Fairness Inefficiency
    3. 3. Zero-Sum Reward Distribution
  9. Reward Capping Analysis
  10. Wintermute Proposal - Analysis of Historical Data
    1. Proposed Weighting
    2. Heavily Favor Maker Volume:
    3. Heavily Favor Depth / Spread
  11. Initial Recommendations
    1. Immediate Recs
    2. Longer-term Recommendations
  12. Research and Evaluation - Utilizing Synthetic Data Sets
    1. Simulations Analysis Highlights
    2. G-score, Weighted-Score versus Q-score based on volume fairness
    3. G-Score versus Q-Score
  13. Simulations Result Summary
    1. Next Steps
  14. About the dYdX Grant Program

🔍 Overview

Chaos Labs, a passionate participant in the decentralized finance (DeFi) community, is proud to collaborate with prominent DeFi protocols. Among these, dYdX stands out as a leading decentralized exchange that facilitates perpetuals and holds a position of prominence within the industry. In line with its dedication and objective of promoting DeFi adoption, Chaos Labs endeavors to construct and disseminate open-source resources that benefit the wider developer community. In furtherance of this effort, Chaos Labs has published the inaugural report on Market Maker Liquidity Rewards Distribution.

Abstract

This paper presents an in-depth analysis of the dYdX protocol's market maker liquidity rewards optimization. By examining the different factors that contribute to the rewards offered by the dYdX protocol, we aim to identify the optimal strategies to maximize returns for market makers contributing impactful volume. Our findings provide essential insights for market makers, liquidity providers, and traders looking to maximize their returns in the dYdX ecosystem.

Introduction

Decentralized finance (DeFi) has experienced tremendous growth in recent years, with the dYdX protocol emerging as a prominent player in the decentralized exchange landscape. The protocol offers various financial services, such as margin trading, derivatives, and perpetuals, through a decentralized, non-custodial platform. This research investigates the liquidity rewards optimization in the dYdX market maker program, focusing on the factors that impact these rewards and the strategies that can be employed to maximize returns for market makers.

📉 Liquidity Provider Rewards Program

The goal of the Liquidity Provider Rewards program is to incentivize market makers to provide meaningful liquidity. Ideally, incentives should motivate makers to tighten spreads and compete on volume. However, after several epochs, we’ve identified cases in which incentive distribution could be improved to better align with impactful liquidity provisioning. This summary will review the current formula, examine live proposals and elaborate on our analysis highlighting the tradeoffs each approach introduces.

Q-Score

To encourage the provision of market liquidity, dYdX will distribute $DYDX tokens to liquidity providers based on a formula that rewards their engagement in the markets. The formula takes into account three parameters:

  • two-sided depth
  • spread (compared to the mid-market price)
  • uptime on dYdX's Layer 2 Protocol

Any Ethereum address can participate in this incentive program, provided that they meet the minimum maker volume threshold of 0.25% of the total maker volume during the preceding epoch. The distribution of $DYDX tokens will occur on a 28-day epoch basis over a period of five years and will not be subject to any vesting or lockups. Each epoch will see the distribution of 1,150,685 $DYDX tokens.

The distribution of $DYDX tokens to each liquidity provider per epoch is determined by the following function. The amount of $DYDX tokens earned depends on the proportionate share of each participant's Q-Final.

Although the formula used for computing rewards based on two-sided depth, spread, and uptime is effective and promotes crucial factors, it falls short in ensuring an equitable distribution of incentives. This is because it does not consider the maker volume. Below are some examples that illustrate cases where rewards distribution is disproportionate as a result of maker volume not being factored in.

Analysis of Q-Score Historical Performance

The LP reward distribution has been computed using the Q-Score formula over multiple epochs. Upon reviewing the rewards distribution across several epochs, it has become evident that the Q-Score formula is not optimal and can result in an unfair distribution of rewards.

Figure 1.1 clearly highlights some of the challenges. Let’s look at the maker depicted as account #5 (X-axis). This maker has contributed relatively low volume and has a disproportionate Q-score.

Figure 1.2: This image is a screenshot of distributions observed in Epoch 7. Here we can clearly view a low relative volume contribution with an ~18x multiplier on Q-Score.

Furthermore, Account #11 has a similar Q-score/volume inversion, albeit at a smaller scale. A relatively quick analysis of historical distributions highlights suboptimal outcomes.

Preliminary Evaluation of G Score & Capping based on Historical Data

Our objective was to assess the effectiveness of three proposed modifications to the existing Q-score based reward distribution formula. These modifications are as follows:

G-Score

This modification involves computing a new score, called the G-Score, which is derived from the equal-weighted geometric average of a given address's Q-score and volume share. The rewards are then distributed in proportion to each participant's G-score. 2/3 x Capping

The second modification entails capping the maximum possible reward at 2-3 times the relative volume contributed by a single address. Any remaining rewards are then redistributed pro-rata according to the volume share of the remaining participants.

Wintermute New Rewards Distribution The third modification proposes a new rewards distribution formula that incorporates maker volume and capped rewards, reduces the weight of depth, spread, and stkDYDX, and provides optional capping. Our evaluation aimed to determine the effectiveness of these modifications in addressing the issues of unfair rewards distribution that arise from the Q-score based formula.


The total rewards score for an individual LP, $Q_i$, is then calculated as follows:

G-Score Analysis

Based on our analysis of historical distributions, it appears that the proposed modifications result in a fairer rewards distribution from a volume perspective when compared to the current Q-score based formula. However, we have identified some potential risks and pitfalls that should be taken into consideration:

1. Over-compensation Risk

One potential issue with the G-score modification is that it compounds the volume portion with the Q-score, resulting in a G-score that can be several times greater than the Q-score. As a result, there are cases where a single significant Liquidity Provider (LP) can receive approximately 60% of the reward pool, and in some cases, a single maker may receive up to 70% of the reward distributions. This level of lopsided reward distribution, while it may be legitimate in some cases, can lead to a single LP dominating the market. This can discourage smaller makers and create a monopolized protocol liquidity, ultimately leading to a decrease in overall decentralization. In the long term, a lack of maker competition and diversity may harm the protocol.

2. Fairness Inefficiency

In our effort to optimize rewards distribution fairness while considering trading volume, we have observed instances where the G-score modification underperforms. There are concrete examples of Liquidity Providers (LPs) with a G-score that is approximately 30 times their trading volume. This suggests that in some cases, the G-score may not accurately reflect a participant's contribution to the protocol's liquidity.

3. Zero-Sum Reward Distribution

It is essential to consider the inverse risk that may arise from "Fairness Inefficiency." Although we strive to achieve a fair rewards distribution, it is important to remember that rewards distribution is a zero-sum game. When larger makers skew the distribution in their favor, it can negatively impact honest makers. This may lead some makers to consider providing liquidity on different platforms or protocols, ultimately harming the protocol's overall liquidity and decreasing decentralization. Therefore, it is crucial to strike a balance between fairness and efficiency when designing a rewards distribution mechanism.

Reward Capping Analysis

Capping introduces a much stronger correlation to trading volume compared to Q-score and G-score. However, after analyzing historical distributions, we’ve identified new pitfalls and types of unfairness.

1. Capping heavily incentivizes trading volume even with very low Q scores. This enables rewards of up to 100-250x the Q score.

2. Capping can significantly reduce Q-Score rewards. This can minimize the weight of the Q-score relative to trading volume.

Wintermute Proposal - Analysis of Historical Data

Proposed Weighting

Figure 2.1

Our analysis indicates that similar results can be achieved using the Weighted-Score modification with suggested scaling parameters (v=0.45, d=0.35, s=0.2) and the uncapped G-score modification (represented by green and red markers respectively). Specifically, we found that with the Weighted-Score modification, 78% of rewards were still distributed to the top two accounts, while the uncapped G-score modification resulted in 80.5% of rewards going to the same two accounts.

Heavily Favor Maker Volume:

Figure 2.2

We have conducted an analysis using a weighted score modification, setting scaling parameters to heavily favor volume (v=0.6, d=0.25, s=0.15). This modification leads to better penalization of account #4 while providing similar rewards to account #0 compared to the original set of parameters. However, even with this modification, 73% of rewards are still distributed to the top two accounts, indicating that further adjustments may be necessary to achieve a more equitable rewards distribution.

Heavily Favor Depth / Spread

Figure 2.3

In our analysis using the Weighted-Score modification, we set the scaling parameters to heavily favor Depth/Spread (v=0.25, d=0.6, s=0.15). However, this modification resulted in worse penalization of account #4, while account #0 received lower rewards compared to the original set of parameters. Furthermore, 81% of rewards are still distributed to the top two accounts, indicating that this modification does not improve the fairness of rewards distribution.

Initial Recommendations

Considering dYdX's intention to promptly address the current state of rewards distribution, we aim to provide short-term recommendations based solely on the current historical data available. However, we recognize that these recommendations may not provide a long-term solution, and therefore, we intend to conduct thorough research and analysis-based simulations to develop a more balanced and fairer solution for the future.

Immediate Recs

Based on our immediate analysis of the two improvement proposals, namely G-score and Weighted-Score (with or without capping), we conclude that both modifications can address the issue of rewards distribution unfairness. G-score can be viewed as a special case of the Weighted-Score, which gives equal weight to volume and Q-scores. However, the Weighted-Score modification has the advantage of allowing the weights to be adjusted.

While it is not entirely clear from the historical data which weights are best for achieving desired liquidity, simulations using a wider range of input synthetic data indicate that the suggested weights (v=0.45, d=0.35, s=0.2) for the Weighted-Score modification are better in terms of rewarding smaller LPs while avoiding over-penalizing large "passive" LPs (i.e., LPs with high trading volume but low Q-score).

On the other hand, capping provides greater fairness, but it also poses a higher risk of manipulation. Therefore, we recommend implementing the Weighted-Score/G-score modification over capping in the short term, with a period of review to further evaluate the effectiveness of the modification.

Longer-term Recommendations

Given the challenges we faced in identifying immediate pitfalls with the proposed modifications and the historical cases of inefficiencies or adversarial outcomes, we strongly recommend conducting in-depth research and analysis to develop a more robust and battle-tested formula to achieve dYdX's objective of fairness across its four pillars: depth, spread, uptime, and volume.

While the Weighted-Score/G-score modifications represent progress towards achieving this objective, we have determined that the distribution of weights between the pillars is still suboptimal. Therefore, further research is necessary to develop a more effective and equitable rewards distribution mechanism.

Research and Evaluation - Utilizing Synthetic Data Sets

As experts in building agent-based simulations that model real user behavior, we at Chaos Labs have leveraged our simulation platform to simulate possible future epochs. To construct these simulations, we developed the following user modes:

  1. Large Market Makers - LPs with significant liquidity that can compete for high Q-scores.
  2. Small Market Makers - LPs that have a low probability of achieving high Q-scores.
  3. Adversarial Market Makers - LPs that actively try and often succeed at gaming the Q-scores and other aspects. Based on historical data, we evaluated the possibility of an LP falling into one or more of these categories to create simulated epochs that closely resemble reality and are statistically feasible.

Based on historical data, we evaluated the possibility of an LP falling into one or more of these categories to create simulated epochs that closely resemble reality and are statistically feasible.

Using these models, we generated 10,000 possible epochs and used them to compare the efficiency of the G-score formula on key metrics.

Note - There is a lot more information and insights to derive from these simulations. This would require building more sophisticated models and adjusting our predictions and conclusions accordingly. The research presented factors in the short time frame and the immediate goal of going live with G-Score in the short term.

Simulations Analysis Highlights

Q-score, G-score, Weighted-Score on top performers

The following graphs aggregate results from 10,000 simulations to compare G-score versus Q-score in terms of rewards distributed to the top performer in each epoch:

X-Axis: Max Q Score for a single maker.

Y-Axis: Count per 10k simulations.

X-Axis: Max G Score for a single maker.

Y-Axis: Count per 10k simulations.

X-Axis: Max Weighted Score for a single maker.

Y-Axis: Count per 10k simulations.

Based on our simulations, we observe that G-score reduces the likelihood of a single top performer obtaining the majority of rewards. However, as our analysis of historical data has shown, this is not always the case in reality. Therefore, we plan to refine our "Gamers" market maker models to more closely resemble real-world behavior.

Furthermore, we find that the Weighted-Score modification reduces the likelihood of a single user obtaining over 40% of rewards in the simulated input data compared to the G-score modification, which had 50-60% in rare but possible cases. This finding supports the conclusion that the Weighted-Score modification is preferable to the G-score alternative.

G-score, Weighted-Score versus Q-score based on volume fairness

To facilitate understanding of the data, we divided the simulation samples into batches of 50 and created graphs to illustrate the maximum/minimum rewards multiplier versus volume. A multiplier of 1 indicates that the rewards are in a 1:1 proportion to the volume of a particular LP, while a multiplier of 2 indicates that the LP received rewards that are twice as large as their share in the volume.

It is important to note that the following presentations are in log scale, which makes it easier to visualize the gaps.

Y-Axis: Max G/Q score over volume in Log scale(multiplier of rewards versus Volume)

X-Axis: simulations (50)

Y-Axis: Min G/Q score over volume in Log scale(multiplier of rewards versus Volume)

X-Axis: simulations (50)

Y-Axis: Max G/Q/W score over volume in Log scale(multiplier of rewards versus Volume)

X-Axis: simulations (50)

Y-Axis: Min G/Q/W score over volume in Log scale(multiplier of rewards versus Volume)

X-Axis: simulations (50)

G-Score versus Q-Score

We narrowed the simulation samples to batches of 50 in order to expose the data in a way that is more digestible.

Similar to the data above for volume, these represent the data in relation to Q-score instead of volume. Also in log scale.

Y-Axis: Max G-score over Q-score in Log scale(multiplier of rewards versus Q-score)

X-Axis: simulations (50)

Y-Axis: Min G-score over Q-score in Log scale(multiplier of rewards versus Q-score)

X-Axis: simulations (50)

To give better context to the data above, we can see the specific top scorers that generated the ratios order in max and then minimum.

Simulations Result Summary

Based on our analysis of the simulation results it is clear that Weighted-Score/G-score is an improvement to the Q-score formula and more difficult for individual makers to manipulate. Most of the time Weighted-Score vs G-score show similar performance, however, Weighted-Score seems to perform better at mitigating disproportional single user rewards for the same simulation data sets, even when having either a disproportional Q-min score or volume share.

It is notable that there’s still work to be done to improve the efficiency of the Weighted-Score/G-score, minimizing the gaps between the Q-score and volume multipliers to the rewards. There are also risks that require further research and remediations in future iterations. These simulations, while powerful, don’t fully address (yet) these potential issues.

We have tried to highlight the “low-hanging” risks in this analysis, but in an ever-changing market, continuous review and analysis will be required to ensure that the formula and distribution strategy survive the test of time.

Next Steps

The above represents the tip of the iceberg in what research the Chaos Labs team intends to complete under this proposal. These simulations have been run to catch what is most obvious in terms of ways the equations could be gamed but have not begun to scratch the surface of potential risks.

We believe that with more time, Chaos Labs would be able to provide a more thorough analysis of the shortfalls of current proposals in addition to a newly proposed solution with a minimal surface area of attack.

Once a new equation is approved by the community, we will use these same simulations in addition to new market data to continue to stress test the LP rewards incentivization scheme to be most efficient at its stated goals: tightening spreads and competition on volumes.

Specific work we intend to do:

  • Optimize to optimal weights for the future formula to achieve the fairest distribution according to the desired metrics.
  • Review additional vulnerabilities/attack vectors in Q-score & G-score or Weighted-Score.
  • Research and iterate to formulate more resilient scoring mechanisms for fairer and tamper-proof formulas
  • Further explore situations of incentive misalignment (underpaying “good” makers, overpaying manipulators, etc.)
  • Ongoing monitoring and adjustments to stay one step ahead

About the dYdX Grant Program

If you want to learn more about the dYdX Grants Program, check out their blog.

Recent Updates

Cover Image for dYdX Chain: End of Season 4 Launch Incentive Analysis

dYdX Chain: End of Season 4 Launch Incentive Analysis

Chaos Labs presents a comprehensive review of the fourth trading season on the dYdX Chain. The analysis encompasses all facets of exchange performance, emphasizing the impact of the Launch Incentive Program.

Omer Goldberg
Omer Goldberg
Cover Image for Arbitrum STIP Risk Analysis | Case Study #1: Vertex

Arbitrum STIP Risk Analysis | Case Study #1: Vertex

As part of our recent election as the Risk Member on the Arbitrum Research & Development Committee (ARDC), Chaos Labs is excited to share a blog post detailing our first case study for the ARDC: Vertex. This is the first case study of a three-part series that entails an in-depth analysis of the risk and efficiency of the Arbitrum STIP on three major protocols, the first of which is Vertex. As requested by the DAO advocate for the ARDC, L2BEAT, Chaos Labs has begun conducting case studies on STIP recipients. This case study provides an in-depth analysis of the Arbitrum STIP program’s impact on the Vertex Protocol, focusing on its efficiency and associated risks. This analysis is part of a broader series that evaluates the STIP program across three major protocols. We will begin by introducing the STIP program and giving an overview of Vertex, followed by our team's full case study.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Oracle Risk Portal

Chaos Labs Oracle Risk Portal

Chaos Labs is excited to announce the launch of our Oracle Risk Portal. This portal is a public resource designed to offer an accessible overview of oracle feed performance, enabling stakeholders to efficiently assess and compare deviations in oracle data.

Omer Goldberg
Omer Goldberg
Cover Image for Oracle Risk and Security Standards: Price Composition Methodologies (Pt. 3)

Oracle Risk and Security Standards: Price Composition Methodologies (Pt. 3)

This chapter delves into the intricate world of Price Composition Methodologies, a foundational pillar of Oracle risk and security. It encompasses an in-depth analysis of data source selection and validation, an exploration of the limitations of rudimentary pricing methods and opportunities for improvement, concluding with an examination of the tradeoffs between price aggregation techniques grounded in real-world examples. This holistic overview guides readers through the practices and innovations that exemplify the relationship between price composition and Oracle security.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Jupiter Protocol

Chaos Labs Partners with Jupiter Protocol

Chaos Labs is thrilled to announce our strategic partnership with Jupiter, a non-custodial DEX aggregator and perpetual futures exchange on Solana. Our partnership represents a deep commitment to enhancing protocol resiliency and growth, fortifying Jupiter's market position, and cultivating a safer, more robust trading environment.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with SynFutures

Chaos Labs Partners with SynFutures

Chaos Labs is thrilled to announce our partnership with SynFutures. Our collaboration, which started in February, is centered on evaluating and enhancing SynFutures V3's pioneering Oyster AMM that allows Single-Token Concentrated Liquidity for Derivatives and a Fully On-Chain Order Book.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Chain: End of Season 3 Launch Incentive Analysis

dYdX Chain: End of Season 3 Launch Incentive Analysis

Chaos Labs presents a comprehensive review of the third trading season on the dYdX Chain. The analysis encompasses all facets of exchange performance, emphasizing the impact of the Launch Incentive Program.

Omer Goldberg
Omer Goldberg
Cover Image for Introducing Aave's Chaos Labs Risk Oracles

Introducing Aave's Chaos Labs Risk Oracles

In the fast-paced and volatile environment of DeFi, managing risk parameters across Aave's extensive network—spanning over ten deployments, hundreds of markets, and thousands of variables such as Supply and Borrow Caps, Liquidation Thresholds, Loan-to-Value ratios, Liquidation Bonuses, Interest Rates, and Debt Ceilings—has evolved into a critical, yet resource-intensive, full-time endeavor. Chaos Labs aims to streamline this paradigm by integrating Risk Oracles to automate and optimize the risk management process, achieving scalability and near-real-time risk adjustment capabilities.

Omer Goldberg
Omer Goldberg
Cover Image for Oracle Risk and Security Standards: Network Architectures and Topologies (Pt. 2)

Oracle Risk and Security Standards: Network Architectures and Topologies (Pt. 2)

Oracle Network Architecture and Topologies provides a detailed examination of how Oracle Networks are structured, data’s complex journey from source to application, and the inherent security and risk considerations within these systems. Through a deep dive into architectures, the data supply chain, and network topology, readers will understand the critical components that ensure the functionality and reliability of Oracles in DeFi, providing context for the challenges and innovative solutions that define the landscape.

Omer Goldberg
Omer Goldberg
Cover Image for Next Generation of NFT Derivatives: Chaos Labs Partners with nftperp

Next Generation of NFT Derivatives: Chaos Labs Partners with nftperp

We are excited to announce the Chaos Labs and nftperp partnership, which aims to pioneer the risk management framework for ongoing parameter optimizations for nftperp’s Perpetual trading DEX.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Elected to Lead Risk for Arbitrum Research & Development Collective

Chaos Labs Elected to Lead Risk for Arbitrum Research & Development Collective

In a significant stride toward enhancing the Arbitrum ecosystem's resilience and efficiency, Chaos Labs has been elected to spearhead Risk Management for the Arbitrum Research and Development Collective.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Chain: Launch Incentives Season 3 Mid-Season Review

dYdX Chain: Launch Incentives Season 3 Mid-Season Review

Chaos Labs presents the mid-season 2 review of full trading on the dYdX Chain. All aspects of the exchange performance are covered with a focus on the impact of the launch incentive program.

Omer Goldberg
Omer Goldberg
Cover Image for Oracle Risk and Security Standards: An Introduction (Pt. 1)

Oracle Risk and Security Standards: An Introduction (Pt. 1)

Chaos Labs is open-sourcing our Oracle Risk and Security Standards Framework to improve industry-wide risk and security posture and reduce protocol attacks and failures. Our Oracle Framework is the inspiration for our Oracle Risk and Security Platform. It was developed as part of our work leading, assessing, and auditing Oracles for top DeFi protocols.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with USDV for Genesis Risk Assessment and Strategic Growth

Chaos Labs Partners with USDV for Genesis Risk Assessment and Strategic Growth

Chaos Labs is thrilled to unveil our strategic partnership with Verified USD, a leap forward in our commitment to innovation within Tokenized Real World Asset (RWA) backed stablecoins.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Chain: Concluding Season 2 Launch Incentive Analysis

dYdX Chain: Concluding Season 2 Launch Incentive Analysis

Chaos Labs is pleased to provide a comprehensive review of the second trading season on the dYdX Chain. This analysis encompasses all facets of exchange performance, emphasizing the impact of the Launch Incentive Program.

Omer Goldberg
Omer Goldberg
Cover Image for USDC Liquidity Optimization Framework for OP Mainnet

USDC Liquidity Optimization Framework for OP Mainnet

Chaos Labs introduces a comprehensive analysis and strategic framework designed to enhance liquidity incentives and streamline the transition from bridged USDC.e to native USDC on the OP Mainnet, aiming for a seamless and efficient migration process.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Optimism Foundation

Chaos Labs Partners with Optimism Foundation

Chaos Labs is excited to collaborate with the Optimism Foundation to optimize liquidity incentives and facilitate the migration from bridged USDC.e to native USDC on OP Mainnet.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Avantis

Chaos Labs Partners with Avantis

Chaos Labs is excited to announce our new partnership with Avantis, marking a significant step forward in our journey toward innovating the world of on-chain trading. Over recent months, our collaboration with Avantis has focused on developing a genesis risk framework and the initial setting of parameters for their protocol.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Chain: Launch Incentives Season 2 Mid-Season Review

dYdX Chain: Launch Incentives Season 2 Mid-Season Review

Chaos Labs presents the mid-season 2 review of full trading on the dYdX Chain. All aspects of the exchange performance are covered with a focus on the impact of the launch incentive program.

Omer Goldberg
Omer Goldberg
Cover Image for Protocol Spotlight: Bluefin V3

Protocol Spotlight: Bluefin V3

Bluefin, the backbone of Sui's derivative exchange ecosystem, drives over 90% of on-chain trading volume. It has undergone a transformative journey from V1 to V2, fine-tuning its codebase for the Sui blockchain. In Q2 2024, Bluefin is set to unveil V3, a highly optimized iteration offering reduced feed, improved latency, and cross-margin trading accounts.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Chain Launch Incentives Program: Wash Trading Detection

dYdX Chain Launch Incentives Program: Wash Trading Detection

Chaos Labs has developed a sophisticated wash trading detection algorithm designed for the dYdX Chain Launch Incentives Program. To enhance the program's effectiveness and encourage genuine long-term activity, Chaos Labs has implemented a robust detection process that identifies and disqualifies traders generating inorganic flow from receiving incentives.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Chain: End of Season 1 Launch Incentive Analysis

dYdX Chain: End of Season 1 Launch Incentive Analysis

Chaos Labs presents the end-of-season 1 review of full trading on the dYdX Chain. All aspects of the exchange performance are covered with a focus on the impact of the launch incentive program.

Omer Goldberg
Omer Goldberg
Cover Image for The Imbalance Score: A Novel Metric for Ostium's RWA-Focused Perpetual DEXes

The Imbalance Score: A Novel Metric for Ostium's RWA-Focused Perpetual DEXes

Exploring risk mitigation levers and methodologies for weakly correlated assets, a key feature of the Ostium Perpetual DEX.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Bluefin

Chaos Labs Partners with Bluefin

Chaos Labs is thrilled to announce our partnership with Bluefin, a leader in decentralized derivatives trading. This collaboration marks a significant milestone in our mission to blend the robustness and security of blockchain technology with cutting-edge trading solutions. We aim to revolutionize how on-chain trading is experienced, ensuring a seamless and secure bridge to off-chain asset offerings.

Omer Goldberg
Omer Goldberg
Cover Image for Seamless Risk Monitoring and Alerting Platform

Seamless Risk Monitoring and Alerting Platform

Chaos Labs is excited to share our partnership with Seamless, centered around risk management and optimization, following their successful launch on Base.

Omer Goldberg
Omer Goldberg
Cover Image for sBNB Oracle Exploit Post Mortem

sBNB Oracle Exploit Post Mortem

Chaos Labs summarizes the snBNB oracle exploit affecting the Venus LST Isolated Pool. The post-mortem focuses on the event analysis and risk management efforts following the exploit.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Chain Analytics and Risk Monitoring Portal

dYdX Chain Analytics and Risk Monitoring Portal

Chaos Labs is thrilled to introduce the dYdX Chain Analytics and Risk Monitoring Portal, a significant development in our continued partnership with the dYdX community. This portal encompasses the emerging dYdX Chain, providing valuable insights and risk assessment capabilities. Additionally, it features a dynamic leaderboard that offers real-time tracking and visibility into traders' points, providing transparency and clarity regarding their positions in the Launch Incentives Program.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Chain: A Comprehensive Overview of the Launch Incentives Program

dYdX Chain: A Comprehensive Overview of the Launch Incentives Program

In collaboration with dYdX, Chaos Labs is excited to announce a $20 million liquidity incentives program to mark the launch of the new dYdX Chain. This initiative, a significant step towards enhancing user experience and liquidity, is tailored to transition users to the dYdX Chain seamlessly. It's not just a program; it's an invitation to be at the forefront of dYdX's vision, shaping the future of decentralized finance.

Omer Goldberg
Omer Goldberg
Cover Image for The Role of Oracle Security in the DeFi Derivatives Market With Chainlink and GMX

The Role of Oracle Security in the DeFi Derivatives Market With Chainlink and GMX

The DeFi derivatives market is rapidly evolving, thanks to low-cost and high-throughput blockchains like Arbitrum. Minimal gas fees and short time-to-finality make possible an optimized on-chain trading experience like the one GMX offers. This innovation sets the stage for what we anticipate to be a period of explosive growth in this sector.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Liquity Protocol

Chaos Labs Partners with Liquity Protocol

Liquity and Chaos Labs have announced a strategic collaboration centered around the development of Liquity v2, an upcoming, new Reserve-backed stablecoin protocol.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Ostium

Chaos Labs Partners with Ostium

Chaos Labs will work closely with Ostium Protocol to improve their mechanism design and create a risk modeling and monitoring system. The partnership will prioritize the system's robustness and secure functioning, helping bridge the gap between on-chain trading and off-chain asset offerings.

Omer Goldberg
Omer Goldberg
Cover Image for GMX V2 Risk Portal Product Launch

GMX V2 Risk Portal Product Launch

Chaos Labs is excited to launch the GMX V2 Synthetics Risk Hub, expanding our existing V1 GLP Risk Hub to provide complete coverage, including all protocol versions.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Ethena Labs for Mechanism Design, Economic Security and Risk Optimization

Chaos Labs Partners with Ethena Labs for Mechanism Design, Economic Security and Risk Optimization

Chaos Labs is partnering with Ethena Labs to fortify mechanism design and develop risk frameworks for the novel protocol. This collaboration is set to amplify the economic security and robustness of Ethena's innovative stablecoin, USDe.

Omer Goldberg
Omer Goldberg
Cover Image for crvUSD Risk Monitoring And Alerting Platform

crvUSD Risk Monitoring And Alerting Platform

Chaos Labs launches the crvUSD Risk Monitoring and Alerting Platform, providing thorough analytics and visibility and serving as a central hub for the crvUSD community to access a wealth of data and risk insights related to the protocol.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Risk Portal 2.0 Launch

Chaos Labs Risk Portal 2.0 Launch

Chaos Labs is proud to announce the official launch of the latest version of our Risk Hub.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Nexus Mutual for Economic Security and Risk Optimization

Chaos Labs Partners with Nexus Mutual for Economic Security and Risk Optimization

After an extensive RFP process, the Nexus Mutual Foundation selected Chaos Labs as an economic security and risk partner. This collaboration is set to fortify the future of the Ratcheting AMM (RAMM) design, a critical component of the Nexus Mutual protocol.

Omer Goldberg
Omer Goldberg
Cover Image for Radiant Risk Monitoring and Alerting Platform

Radiant Risk Monitoring and Alerting Platform

Chaos Labs launches the Radiant Risk Monitoring and Alerting Platform, providing thorough analytics and visibility and serving as a central hub for the Radiant community to access a wealth of data and risk insights related to the protocol.

Omer Goldberg
Omer Goldberg
Cover Image for Venus Risk Monitoring and Alerting Platform

Venus Risk Monitoring and Alerting Platform

Chaos Labs launches the Venus Risk Monitoring and Alerting Platform, providing thorough analytics and visibility and serving as a central hub for the Venus community to access a wealth of data and risk insights related to the protocol.

Omer Goldberg
Omer Goldberg
Cover Image for Compound Multi Chain Risk Monitoring Hub

Compound Multi Chain Risk Monitoring Hub

Chaos Labs has partnered with Compound via the Grants program, launching a state-of-the-art Compound Cross-Chain Analytics and Observability platform.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Risk Parameter Recommendation Portal

dYdX Risk Parameter Recommendation Portal

Chaos Labs and Considered.finance are excited to present our collaboration, the dYdX Risk Parameter Recommendation Portal 4. This dashboard provides real-time parameter recommendations informed by market liquidity and objective order book liquidity measures.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with TapiocaDAO for Risk Management and Optimization

Chaos Labs Partners with TapiocaDAO for Risk Management and Optimization

Chaos Labs is thrilled to announce a strategic partnership with TapiocaDAO, centered around risk management and parameter optimization for the imminent launch of the omni-chain money market protocol and USDO.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Launches the Aave Asset Listing Portal to Streamline New Collateral Onboarding

Chaos Labs Launches the Aave Asset Listing Portal to Streamline New Collateral Onboarding

Chaos Labs has launched the Aave Asset Listing Portal, a tool that will streamline onboarding new collateral to the Aave protocol. The portal automates collecting and analyzing key market data around assets, enabling the community to make informed decisions and enhance risk management.

Omer Goldberg
Omer Goldberg
Cover Image for GMX GLP Risk Hub: A Public Derivative Risk Monitoring and Analytics Platform

GMX GLP Risk Hub: A Public Derivative Risk Monitoring and Analytics Platform

Chaos Labs is proud to partner with GMX, a leading DeFi perpetual platform, to launch the GMX GLP Public Risk Hub (Version 0), a cutting-edge platform designed to provide real-time user metrics, margin-at-risk analysis, alerting, and market simulations to assess the value at risk (VaR) in fluctuating markets.

Omer Goldberg
Omer Goldberg
Cover Image for Uniswap V3 TWAP: Assessing TWAP Market  Risk

Uniswap V3 TWAP: Assessing TWAP Market Risk

Assessing the likelihood and feasibility of manipulating Uniswap's V3 TWAP oracles, focusing on the worst-case scenario for low liquidity assets.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Partners with Compound for Cross-Chain Risk Analytics Grant

Chaos Labs Partners with Compound for Cross-Chain Risk Analytics Grant

Chaos Labs, a cloud-based risk management platform for DeFi applications, has been awarded a Compound Grant to build a Cross-Chain Risk and Analytics platform.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Risk Dashboard Launches Live Alerts for Real-Time Risk Management

Chaos Risk Dashboard Launches Live Alerts for Real-Time Risk Management

Chaos Risk Dashboard has rolled out new functionality that provides real-time alerts covering crucial indicators on the Aave v3 Risk Dashboard and BENQI Risk Dashboard.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs USDC Depeg - War Room Summary

Chaos Labs USDC Depeg - War Room Summary

Chaos Labs summarizes the USDC depeg event and risk management efforts following the collapse of SVB.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Launches the BENQI Parameter Recommendations Platform

Chaos Labs Launches the BENQI Parameter Recommendations Platform

Chaos Labs launches the BENQI Parameter Recommendations Platform to streamline risk parameter recommendations for the BENQI protocol.

Omer Goldberg
Omer Goldberg
Cover Image for Introducing the GHO Risk Monitoring Dashboard by Chaos Labs

Introducing the GHO Risk Monitoring Dashboard by Chaos Labs

Chaos Labs unveils a new version of the Aave v3 Collateral At Risk Dashboard monitoring the GHO deployment on the Goerli testnet in preparation for mainnet launch.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Raises $20M in Seed Funding to Automate On-Chain Risk Optimization

Chaos Labs Raises $20M in Seed Funding to Automate On-Chain Risk Optimization

Chaos Labs raises Seed funding led by Galaxy and Paypal Ventures to automate on-chain risk optimization.

Omer Goldberg
Omer Goldberg
Cover Image for AAVE v3 Collateral At Risk Dashboard Expands Deployments Support to Ethereum v3

AAVE v3 Collateral At Risk Dashboard Expands Deployments Support to Ethereum v3

Following the successful launch of the AAVE v3 Collateral At Risk Dashboard, we're proud to announce expanded support for Ethereum v3.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Unveils Parameter Recommendation Platform.

Chaos Labs Unveils Parameter Recommendation Platform.

After becoming full-time contributors to the Aave protocol in 2022, Chaos Labs has been working on all fronts to deliver tools that will increase the community’s understanding of Aave and its potential. We’re proud to publish V0 of the Chaos Labs parameter recommendation platform to the community!

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Selected by Uniswap Foundation for TWAP Oracle Research Grant

Chaos Labs Selected by Uniswap Foundation for TWAP Oracle Research Grant

Preceded by earlier V3 TWAP oracle research, the Uniswap Foundation announces a Chaos Labs grant.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs & Hathor Nodes launch platform to optimize Osmosis incentive distribution

Chaos Labs & Hathor Nodes launch platform to optimize Osmosis incentive distribution

Funded by the Osmosis Grants Program, the pair launches an open-sourced incentives model and community dashboards.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs receives a Uniswap Foundation grant for LP strategies for V3

Chaos Labs receives a Uniswap Foundation grant for LP strategies for V3

Chaos Labs has been awarded a grant from the Uniswap Foundation to test and simulate sophisticated LP strategies.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs helps navigate DeFi volatility with an expanded Aave V2 risk partnership

Chaos Labs helps navigate DeFi volatility with an expanded Aave V2 risk partnership

Chaos Labs announces further collaboration with Aave to include Aave V2 risk coverage.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Osmosis Liquidity Incentives Portal Update

Chaos Labs Osmosis Liquidity Incentives Portal Update

An update on the Osmosis Liquidity Incentives Portal collaboration with Hathor Nodes.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Launches Benqi Risk Dashboard

Chaos Labs Launches Benqi Risk Dashboard

Chaos Labs is launching the Benqi Risk Dashboard, utilizing real-time user metrics to understand the value at risk across volatile markets as well as yield earned and paid over time.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Asset Protection Tool

Chaos Labs Asset Protection Tool

Chaos is unveiling a new tool to measure price manipulation risk and protect against it. Introducing the Chaos Labs Asset Protection Tool

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Joins AAVE as Full-Time Contributor

Chaos Labs Joins AAVE as Full-Time Contributor

After a successful governance vote, Chaos Labs is joining Aave as a full-time contributor to focus on risk management and parameter recommendations for all Aave v3 markets.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives Osmosis Grant

Chaos Labs Receives Osmosis Grant

Chaos Labs has received a grant from the Osmosis Grants Program and will partner with Hathor Nodes on optimizing the Osmosis incentives program.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs <> Benqi veQI Calculator

Chaos Labs <> Benqi veQI Calculator

Chaos Labs, a cloud security platform for DeFi applications, announces the launch of the Benqi veQI calculator.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Auction Price Curve & Keeper Gas Strategies (Pt. 4)

Maker Simulation Series: Auction Price Curve & Keeper Gas Strategies (Pt. 4)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model and simulate how Keepers with competing gas strategies impact the Auction Price Curve for liquidations.

Omer Goldberg
Omer Goldberg
Cover Image for Benqi veQI Economic Analysis

Benqi veQI Economic Analysis

Diving deep into Benqi's veQI tokenomics and utility.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Peg Stability Module (Pt. 3)

Maker Simulation Series: Peg Stability Module (Pt. 3)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model PSM simulations.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs launches AAVE v3 Risk Bot

Chaos Labs launches AAVE v3 Risk Bot

The AAVE v3 Risk bot will provide monitoring, notifications and daily summaries for risk related activity across all v3 deployments.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Flapper Surplus Dai Auctions (Pt. 2)

Maker Simulation Series: Flapper Surplus Dai Auctions (Pt. 2)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model and simulate Flapper Surplus DAI auctions.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Launches AAVE v3 Risk Application

Chaos Labs Launches AAVE v3 Risk Application

Chaos Labs, a cloud security platform for DeFi applications, has launched an AAVE v3 collateral at risk and real-time user metrics dashboard.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Flipper Black Thursday (Pt. 1)

Maker Simulation Series: Flipper Black Thursday (Pt. 1)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model and simulate Flip Auctions, liquidations and auctions.

Omer Goldberg
Omer Goldberg
Cover Image for AAVE Simulation Series: stETH:ETH Depeg (Pt. 0)

AAVE Simulation Series: stETH:ETH Depeg (Pt. 0)

A simulation series focused on economic security for the AAVE protocol. Let's examine the effect of a stETH:ETH depeg.

Omer Goldberg
Omer Goldberg
Cover Image for Maker Simulation Series: Introduction (Pt. 0)

Maker Simulation Series: Introduction (Pt. 0)

Chaos Labs, a cloud-based simulation platform for smart contract applications, has collaborated with Maker to model and simulate liquidations and auction mechanisms.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Dives Deep Into AAVE v3 Data Validity

Chaos Labs Dives Deep Into AAVE v3 Data Validity

Chaos Labs, a cloud security platform for DeFi applications, has discovered

Ron Lev
Ron Lev
Cover Image for Chaos Labs Collaborates with Benqi For Liquid Staking Analytics

Chaos Labs Collaborates with Benqi For Liquid Staking Analytics

Chaos Labs, a cloud security platform for DeFi applications, announces a partnership with Benqi to support Liquid Staking on the Avalanche network.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives AAVE Grant

Chaos Labs Receives AAVE Grant

Chaos Labs, a cloud security platform for DeFi applications, has been awarded an AAVE Grant to build a collateral at risk and real-time user metrics dashboard.

Omer Goldberg
Omer Goldberg
Cover Image for Pushing Economic Security Boundaries with MakerDAO Pt. 2

Pushing Economic Security Boundaries with MakerDAO Pt. 2

Chaos Labs, a cloud security and testing platform for smart contract applications, has created a cloud platform for Maker to test their liquidation and auction mechanisms.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Open Source Uniswap v3 TWAP Hardhat Plugin

Chaos Labs Open Source Uniswap v3 TWAP Hardhat Plugin

Chaos Labs, a cloud security platform for DeFi applications, has open source a utility package for interfacing with Uniswap v3.

Omer Goldberg
Omer Goldberg
Cover Image for Uniswap V3 TWAP Oracle Deep Dive - Pt. 2

Uniswap V3 TWAP Oracle Deep Dive - Pt. 2

An in depth look at Uniswap v3 TWAP architecture and usage in development.

Omer Goldberg
Omer Goldberg
Cover Image for dYdX Maker Liquidity Rewards Distribution Report

dYdX Maker Liquidity Rewards Distribution Report

Chaos Labs releases the dYdX Market Maker Liquidity Rewards Distribution Report.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives Chainlink Grant to build Terra Oracle Infrastructure

Chaos Labs Receives Chainlink Grant to build Terra Oracle Infrastructure

Chaos Labs, a cloud security platform for DeFi applications, has been awarded a Chainlink Grant to build tooling and infrastructure for Terra Oracles.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs releases the dYdX Perpetual Funding Rate App

Chaos Labs releases the dYdX Perpetual Funding Rate App

Chaos Labs releases the dYdX Perpetual Funding Rate application for the dYdX ecosystem.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Open Sources Chainlink Price Feed NPM Module

Chaos Labs Open Sources Chainlink Price Feed NPM Module

Chaos Labs, a cloud security platform for DeFi applications, has open source a utility package for interfacing with Chainlink price feeds.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Open Sources dYdX Trading CLI

Chaos Labs Open Sources dYdX Trading CLI

Chaos Labs, a cloud security platform for DeFi applications, has open sourced a trading tool for the dYdX ecosystem.

Omer Goldberg
Omer Goldberg
Cover Image for Pushing Economic Security Boundaries with MakerDAO

Pushing Economic Security Boundaries with MakerDAO

Chaos Labs, a cloud security and testing platform for smart contract applications, has created a cloud platform for Maker to test their liquidation and auction mechanisms.

Omer Goldberg
Omer Goldberg
Cover Image for Uniswap v3 TWAP Oracle Tooling and Deep Dive Pt. 1

Uniswap v3 TWAP Oracle Tooling and Deep Dive Pt. 1

Chaos Labs, a cloud security platform for DeFi applications, has released open source tooling for developing with Uniswap v3 TWAP Oracles.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives dYdX Grant

Chaos Labs Receives dYdX Grant

Chaos Labs, a cloud security platform for DeFi applications, has been awarded a dYdX Grant to build analytics and tooling for the dYdX ecosystem.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives Uniswap Grant

Chaos Labs Receives Uniswap Grant

Chaos Labs, a cloud security platform for DeFi applications, has been awarded a Uniswap Grant to build tooling for Uniswap v3 TWAP Oracles.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Adds Chainlink Oracle Cloud Integrations

Chaos Labs Adds Chainlink Oracle Cloud Integrations

Chaos Labs receives grant to enhance Chainlink Oracle Cloud Testing Environment.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs joins Maker SES

Chaos Labs joins Maker SES

Chaos Labs, a cloud security and testing platform for smart contract applications, has recently joined the SES incubation program.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Receives Chainlink Grant

Chaos Labs Receives Chainlink Grant

Chaos Labs, a cloud security platform for DeFi applications, has been awarded a Chainlink Grant.

Omer Goldberg
Omer Goldberg
Cover Image for Chaos Labs Mission Statement

Chaos Labs Mission Statement

Chaos Labs is a cloud security and testing platform for smart contract applications. Mission statement coming soon 🎉 🥳

Omer Goldberg
Omer Goldberg