Morpho Market Methodology

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Introduction

The Morpho Market Methodology provides a comprehensive risk assessment of individual Morpho markets, capturing loan and collateral dynamics alongside key protocol-specific parameters. Using Market Simulations and Liquidation Simulations, this methodology quantifies the Probability of Significant Loss (PSL) for each market.

Key Sections

Below is an overview of the core sections covered in the methodology document:

1. Market Simulations

The model uses Monte Carlo Simulations to generate daily returns on loan-to-collateral price pairs over a 30-day horizon, factoring in volatility, tail events, and collateral defaults. Key elements of the model include:

  • Morpho Market Parameters: Are used as direct inputs in the simulation
    • LLTV: Liquidation Loan-to-Value thresholds for determining when a position is subject to liquidation.
    • LIF: Liquidation Incentive Factor, incentivizing liquidators under specific market conditions.
    • Loan LTV Tranches: The distribution of loans in a specific Morpho Market
    • Market Oracle Characterization: Different types of oracles (Dynamic, Exchange Rate, Hardcoded), influence the simulation framework
  • Daily Return Profile: In determining the daily return profile, extreme returns are separated from non-extreme returns and distinct modeling approaches are applied to each segment.
    • Historical Volatility: A Normal Distribution is utilized for modeling non-extreme returns.
    • Tail Events: Extreme values exceeding a percentile threshold per asset pair are modelled separately using a Generalized Pareto Distribution
    • Collateral Default Events: In the event of a collateral asset default, the relevant asset pair can experience a significant price impact. The expected impact on the asset price is determined by a Loss Given Default (LGD).
  • Rebalancing Parameters: Considers borrower behavior, who are incentivized to rebalance their positions (e.g. deposit additional collateral) as the risk of liquidation increases.
  • LTV Simulations: The Daily Return Profile drives price simulations, which are utilized to calculate the evolution of loan-to-value ratios over a specified number of days, with the objective of modeling how frequently loans are expected to breach the LLTV.
  • Market Simulation Outputs: The model returns information on Trigger Events, or incidents when the LTV surpasses the LLTV.

2. Liquidation Simulations

The Trigger Events are isolated for further analysis, and a PSL is quantified by analyzing the quantity of incidents where despite the liquidation simulation, Bad Debt exceeds the 1% threshold.

  • Step Functions: Are utilised by the simulation to segment a daily price move into multiple linearly spaced intraday price moves. This allows for the simulation of multiple liquidation events in a single day, more accurately modeling market behavior.
  • Liquidity Parameters: Are calculated independently for each Morpho market.
    • Base Liquidity: DeFi pricing data is used to build a liquidity curve, where the USD amount of available liquidity is considered versus the slippage from the market mid-price.
    • Volatility Adjustment: This adjustment aims to capture the reality that liquidity is dependent on market conditions. Where simulated Trigger Events are the result of a relatively volatile price path (i.e. driven by tail events), recent liquidity may overstate what is likely available.
    • Market Tier Adjustment: Aims to capture the risk of liquidations occurring simultaneously across multiple Morpho and external markets, therefore reducing the available liquidity.
  • Liquidation Simulation Outputs: The following are the core outputs of the Liquidation Simulation.
    • Expected Bad Debt per Scenario Trigger: The notional amount of bad debt per Trigger Event. This is utilized to calculate the Monthly PSL.
    • Monthly PSL: Represents the probability of experiencing a significant loss event in a 30-day period. It is calculated as the number of significant loss events divided by the total number of simulations. The Monthly PSL is annualized for the purposes of comparison versus Credora PD outputs.

3. Market-Level Modifiers & Adjustments

Once PSL outputs are generated from the simulations, an additional modifier and adjustment are applied to account for bespoke, market-specific risks.

  • Oracle Risk Modifier: Addresses risks stemming from hardcoded or misconfigured oracles, or where the oracle vendor and configuration is uncertain, reflecting the potential for inaccurate or unreliable price feeds.
  • Protocol Risk Adjustment: Accounts for operational and smart contract risks inherent to the underlying network where a given Morpho market operates.

Access the Full Documentation

You can view the complete Morpho Market Methodology on GitBook.

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