A new paper released Thursday by a team of crypto researchers hopes to complement a series of work that will eventually identify “the Black-Scholes of Decentralized Finance (DeFi)” – an equation that investors and users of DeFi use -Can properly evaluate projects and potential profit / loss metrics in popular DeFi industries such as liquidity mining.
Why is such an equation important? At first glance, liquidity mining is easy to explain: in return for providing liquidity to automated market makers like Uniswap, users are rewarded with trading fees or governance tokens, which are often expressed in APY percentages.
However, users suffer “inconsistent losses” due to fluctuations in demand for the trading pair, and a simple APY calculation on a user interface front end is not enough to paint a complete picture of what the profits might look like for liquidity providers.
According to research by Tarun Chitra, founder and CEO of the DeFi risk analysis company Gauntlet.Network and one of the three co-authors of When does the tail wag the dog? Curvature and market making, Liquidity mining is best viewed as a complex derivative.
⚠️ Paper Alert ⚠️
Q: Was this what you wondered about math?
a) Optimal amount of tokens for income incentives
b) Hedging a volatile loss with options
c) When are LPs not corrected?
A: New paper from moi, @alexhevans, @GuilleAngeris https://t.co/VeJjtSK038
– Tarun Chitra (@tarunchitra) December 17, 2020
“Most passive investment products often have a non-trivial derivative-like exposure. For example, the February 2018 collapse of ETF XIV (“volmageddon”) demonstrated the complexity of some assets that are “passive” and “safe”, ”explained Chitra to Cointelegraph. “The provision of liquidity in ATMs is not that different, although it poses new risks for owners. Liquidity providers always offset the earned fees (positive income) with large price movement losses (negative, volatile loss). “
This complexity has resulted in many liquidity mining projects being disrupted due to excessive incentives (“1e9% APY is unsustainable, too many LPs and no dealers”) or inadequate incentives from developers who don’t offer enough rewards to make inconsistent losses equalize, have failed. Ultimately, users and developers should “view agriculture as a complex derivative analog of maker-taker incentives on centralized exchanges”.
In addition, this new conceptual model can enable more granular decision-making by liquidity providers as well as more robust architectural frameworks for AMM developers.
“This paper gives developers and designers a principled opportunity to provide meaningful LP returns,” said Chitra. “APY only makes sense for fixed income assets (bonds), while pricing for derivatives makes MUCH more sensible for something like providing liquidity. We hope this will be the first in a series of works that try to find the Black-Scholes of DeFi. “
According to Chitra, successfully identifying a DeFi equivalent to the Black-Scholes model could also be key to mass adoption of DeFi. Black-Scholes was developed in the 1980s to help investors find ways to properly value stock options. This led to a massive boom in derivatives trading.
It remains to be seen whether a new model can cut through the complexity of DeFi this neatly, but this paper seems like a promising first step.