Background

As risk-focused contributors within dYdX and the broader DeFi ecosystem, Considered.finance and Chaos Labs continuously explore mechanism design, economic security frameworks, and market risk requisites for creating decentralized protocols. We’re excited to present our latest collaboration - the dYdX Risk Parameter Recommendation Portal, generating real-time margin parameter recommendations in alignment with live market liquidity conditions. We aim to offer transparent, data-driven methodologies and tools to optimize risk management within dYdX.

The forthcoming V4 launch holds the potential to act as a landmark in the protocol's decentralization trajectory, signifying our progression toward a permissionless, transparent, on-chain derivatives exchange. Notwithstanding the potential benefits of such an open and transparent perpetual exchange, it does present numerous challenges that necessitate a collective, community-led risk framework. Stated succinctly, the goal of V4 is to achieve complete decentralization, which implies that the platform will need to operate autonomously, with the onus of risk management being transferred to the community.

As a first step to creating the tooling necessary for decentralized risk management, Chaos Labs, in collaboration with Considered.finance, has created a dashboard implementing Considered.finance research paper titled "Proactive Risk Management of dYdX Risk Parameters."

Introduction

Well-calibrated margin risk parameters serve a dual function. Optimized risk parameters shield the dYdX protocol from insolvency brought about by market volatility or malicious actors while minimally constraining standard trading activity. The dYdX Parameter Recommendation Portal offers a transparent way to suggest optimal parameter levels and all inputs informing them. The individual market orderbook metrics, in particular, offer the community a benchmark for liquidity on the exchange that can be utilized broadly in DAO decision-making processes. Recent discussions concerning the appropriate sizing of rewards underscore how this data point could be advantageous. Utilizing recently observed order book depth as the input ensures a consistent and unbiased method for calibrating margin risk parameters. Ecosystem players can feel confident that the appropriate rails are set to keep their funds and the protocol safe.

Leveraging the framework delineated in Proactive Risk Management of dYdX Risk Parameters, the portal proposes risk parameter modifications incorporating real-time market liquidity's fluid dynamics. The dYdX exchange utilizes a limited order book structure to stimulate liquidity and establish prices, which adds a layer of complexity given its reliance on market-maker behavior. Acknowledging the distinctive liquidity dynamics influenced by various factors in each market, the platform provides an objective, transparent, and systematic method for setting margin parameters that align with the exchange's liquidity dynamics.

This system is configured to evaluate trading conditions in dYdX v3 when informing parameter recommendations. The underlying data and algorithms are adaptable and robust and can be easily modified in v4 in most risk parameter frameworks.

Starting now with v3 will help inform configurations from the outset.

On the homepage of the dYdX Parameter Recommendations Portal, users can access high-level recommendations tailored to specific markets. For a comprehensive understanding of the methodology behind these recommendations, users can click on the "Discover Methodology" button, which will redirect them to the Considered Finance research paper titled "Proactive Management of dYdX Risk Parameters," providing a thorough exploration of the methodology.

On the homepage of the dYdX Parameter Recommendations Portal, users can access high-level recommendations tailored to specific markets. For a comprehensive understanding of the methodology behind these recommendations, users can click on the "Discover Methodology" button, which will redirect them to the Considered Finance research paper titled "Proactive Management of dYdX Risk Parameters," providing a thorough exploration of the methodology.

Platform Overview

The platform leverages real-time dYdX order book data at its core, recording historical data and creating an extensive observation history. Historical data is the foundation for computing recommended baseline and maximum position sizes, with the incremental position size derived accordingly.

This process provides a sound basis to protect all stakeholders through consistent application across markets. In essence, traders will only be limited from opening positions that run an intolerable risk of not being able to be liquidated in stressed market conditions.

Market-Specific Parameter Recommendations

Community members can peruse data specific to each market by selecting the desired market row. This user-friendly feature ensures accessibility and transparency of information, contributing to informed decision-making within the ecosystem.

Community members can peruse data specific to each market by selecting the desired market row. This user-friendly feature ensures accessibility and transparency of information, contributing to informed decision-making within the ecosystem.

Clicking into a market opens the Market Detail view, which displays parameter recommendations specific to a market. The Chaos Labs data infrastructure ingests real-time dYdX order book data and stores long-term observations. A rolling period of this history is then used to compute recommended baselinePositionSize, and maximumPositionSize values from which the incrementalPositionSize is inferred, based on research and algorithm by Considered Finance.

Maximum Allowable Leverage as a Function of Position Size

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The Parameter Change data visualization graphically juxtaposes Maximum Allowable Leverage and position sizes. The blue line delineates recommendations driven by market liquidity, while the orange line mirrors the present market configuration. Notably, the market-specific Portal Recommendation, depicted in blue, exhibits a steeper downward slope as a function of position size, indicating a more restricted availability of market liquidity. This allows traders room to trade higher leverage up to around 1800 ETH in this case while protecting the exchange from overstressing the orderbook above that.