Risk Management

Oracle-based perpetual exchanges share one standard functionality: Traders trade against the pool. The first iteration of products in this category was quite plain and straightforward—trade against the house, and the house will pay out when you win. However, as the products mature, it has become increasingly clear that sound risk management for liquidity providers is necessary to keep the system robust and sustainable. This section outlines NLP pool risk management parameters designed to protect Liquidity Providers and ultimately provide a better experience for all platform users.

Funding Rates

In order to book perpetual exchanges, funding rates are implemented to incentivize the price of the perpetual contract to trade close to the price of the underlying spot market. When the price of perpetual> spot, there will be a positive funding rate, where longs pay shorts, to incentivize shorts to balance out the market.

While this is not an apples-to-apples comparison for Oracle-based exchanges like Narwhal, a similar idea can be implemented to balance market exposure to NLP.

At any given time for a specific market, the market is exposed to a relative skew defined as (long open interest-short open interest) / net open interest.

A detailed methodology on funding rates can be found in our fees and spread section of documents. In summary:

• If the skew is long, funding is positive

• If the skew is short, funding is negative

• If the skew is perfectly balanced, funding is 0

Open Interest

With a purely synthetic trading model, the theoretical open interest a pool can support will be greater than a traditional margin model, where open interest is capped at the TVL of a Margin LP. To prevent tail risks, Narwhal also has implemented two maximum limits: maxOI and maxnetOI

maxoi Refers to the maximum open interest, on either the long or short sides, that the vault can support. This parameter is adjusted periodically according to the TVL of NLP

maxnetoi , an additional parameter implemented for risk management. It is defined as abs(Long OI - Short OI). This caps the net market exposure for a specific asset that NLP is exposed to based on each asset's maximum market risk.

Using BTC/USD as an example:

• Current long open interest/Max open interest: 1M/3M

• Current short open interest/Max open interest: 500K/3M

• Net Open interest/Max Open Interest: 1M-500k = 500K/500K

In this case, even though the max long open interest on BTC is 3M, the max net open interest cap has been reached, which means no new long positions can be opened. The vault can support an additional 1M short open interest without changing the long open interest.