Risk Management

Oracle-based perpetual exchange share one common functionality - traders trade against the pool. The first iteration of products in this category were quite plain and simple - trade against the house and the house will pay out when you win. However, as the products gains maturity, it has becoming increasingly clear that sound risk management for liquidity providers is necessary to keep the system healthy, rhobust, and sustainable. This section outlines NLP pools risk management parameters designed to protect Liquidity Providers and ultimately provide a better experience for all users of the platform.

Funding Rates

In order 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 perpetuals > 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 apple-to-apple 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.

Detailed methodology on funding rates can be found in the fees and spread section of our docs. In summary:

• If the skew is long, funding is positive

• If the skew is short, funding is negative

• If 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 side or short side that the vault can support. This parameter is adjusted periodically according to the TVL of NLP

maxnetoi is 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 the maximum market risk on each specific asset.

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. In this case the vault can support an additional 1M short open interest without changes to long open interest.