Risk Analysis Methodology

The following methodology outlines how Exponent quantifies the underlying risks for a given stable-coin portfolio. The objective is to help a project better understand, assess and mitigate the fat tail risk of its treasury.

Step 1: Definition

First, the project should self-define and clarify the following variables:

1. Current monthly burn rates: ie. $100K per month

2. The total size of the current treasury: ie. $2M

3. Minimum safe runway: number of months before further cash injection/ raise is needed ie. 12 months

4. Portfolio makeup: ie. 600K USDT, 1.4M USDC

5. Definition of consequences levels: Negligible, Minor, Moderate, Major and Catastrophic

Example Consequences definition

Negligible	Loss of ~3% of the current treasury, ~30 BIPs loss of trade slippage.
Minor	Loss of ~5% of the current treasury, ~1% loss of trade slippage.
Moderate	Loss of 10% of the current treasury, a temporary halt to ability to ability to transact beyond 24 hours.
Major	Permanent loss beyond 20% of the treasury, or temporary halt to the ability to transact beyond 1 month.
Catastrophic	Permanent loss of the Treasury and run rate of fewer than 12 months.

Step 2: Conduct Analyses

Before we jump into the analyses, we must first understand different dimensions of risks vectors, such as: Regulatory, Censorship, Liquidity, Governance, Peg resilience, Slippage and Smart contract risks.

Refer to risks dimensions for more information.

The methodology combines elements of scenario analysis and risk assessment matrix to help inform and define risk vectors. It walks through different events per asset and risk dimension, defines the outcome of such events, and through degrees of consequences and likelihood- determines the threat level.

Example:

• Event Name: Slippage on thin liquidity for USDT

• Event Description: Thin liquidity on DEXs for USDT, leading to ~1% slippage on each trade

• Consequence:

• Likelihood:

Consequence

Consequence description of an event is subjective to an extent, however, they can be labeled and compared quantitatively with the above definitions.

Example:

• Event Name: Slippage on thin liquidity for USDT

• Event Description: Thin liquidity on DEXs for USDT, leading to ~1% slippage on each trade

• Consequence: Given that USDT is $600K or 30% of the entire portfolio, the impact on the portfolio is limited to: $6000 per slippage on USDT trade, therefore the risk is negligible

• Likelihood:

Likelihood

This defines the likelihood of an event. Aside from educated guesses, quantitative metrics may help to determine the probability of an event. Exponent keeps track of different definitions of the on-chain metrics within our Metrics Library.

Example:

• Event Name: Slippage on thin liquidity for USDT

• Event Description: Thin liquidity on DEXs for USDT, leading to ~1% slippage on each trade

• Consequence: Given that USDT is $600K or 30% of the entire portfolio, the impact on the portfolio is limited to: $6000 per slippage on USDT trade, therefore the risk is negligible

• Likelihood: According to historical metrics for available USDT/DAI/USDC liquidity in the Curve pool. At the point of maximum drawdown in the pool, there still exists sufficient liquidity for a swap of $~200K with < 1% slippage

Thus, we can determine that it is unlikely USDT can’t be swapped out for $400K

To conclude, the event Slippage on thin liquidity for USDT is unlikely to happen and has negligible consequences. We can then conclude that the event has a low level of importance.

The list of tail risk scenarios is TBD

Step 3: Derive Recommended Changes and Mitigation Plan

The objective of this exercise is to assist a project’s financial controller/ finance team to analyze the portfolio’s robustness against fat tail events. After the exercise, the team should investigate substantial threats within the moderate, high, and extreme areas. Once the assessment is complete, a project should take the following steps to plan for changes and mitigation of such events.

There are numerous methods to mitigate the different threat models. In the case of stablecoin- a number of risks can be mitigated through diversification. This works well to reduce the impacts of concentrated portfolio risks.

The assessment can be done periodically or followed up after mitigation plans are created.