AMMs are not in equilibrium. While LPs for the top Uniswap pools have become profitable, returns within a rounding error of zero. Most people in DeFi, even those building AMMs, do not understand convexity costs, but as everyone figures it out, TVL will continue to stagnate, if not decline. Worse, many yield farming scams are predicated on the underlying yields from LPing, and if this is built on a base zero-return at best, no amount of leverage can make it generate an attractive return. 2023 and 2024 YTD Profit/USD Traded (in bps) For example, the eth-usdc pool lost 0.000048 USD per ..read more

 Recently deceased philosopher Daniel Dennett called Darwin's idea of natural selection the best idea anyone ever had, a universal solvent that melts away all the problems in biology. Dennet had contempt for Christians, coined the term 'brights' for those who shared his worldview, and thought it wise not to respect religion because of its damage to the 'epistemological fabric of society.' Like fellow atheist Richard Dawkins, he never debated biologists, just theologians. In a 2009 debate, Dennet mentioned he brought his friend, an evolutionary biologist, to a 1997 debate with Michael Behe ..read more

 Generally, markets are efficient in that it isn't easy to make above-average returns day-trading, and most mutual funds underperform market-weighted ETFs. Yet historically, in various applications, options have been underpriced for decades. For example, asset return distributions were known to have fatter tails than the lognormal distribution back in the 1960s (see Benoit Mandelbrot ('62) or Eugene Fama (' 65)). Most option market makers, however, applied the basic Black-Scholes with a single volatility parameter, which underpriced out-of-the-money options. On a single day, October 19, 1 ..read more

 A curious aspect of high-frequency data is that most come from centralized limit order books (CLOBs) where the bid-ask spread makes the data look negatively autocorrelated as trades are randomly made at the bid and the ask. The returns driving this pattern are well below transaction costs, so they do not generate an arbitrage opportunity. However, one might be tempted to use the high-frequency data to estimate variance for pricing options or convexity costs (aka impermanent loss, loss versus rebalancing). This is a problem because the 1-minute Gemini returns generate a variance estimate ..read more

A recent paper by Columbia professor Ciamac Moallemi and three Uniswap affiliates (Adams, Reynolds, and Robinson) presents a mechanism for recapturing the convexity costs. It builds upon Moallemi's previous work on automated market makers (AMMs) and arbitrage profit, published a year ago, which Moallemi presented at a16z crypto last summer. In that talk, he mentioned auctions as a way to reduce adverse selection costs for liquidity providers (LP). AMMs' big problem is that LPs generally lose money in their popular capital-efficient (v3) pools. An LP's net profitability consists ..read more

arbprofit Columbia professor Ciamac Moallemi, Uniswap's Adams, Reynolds, and Dan Robinson released a paper last week on recapturing some of the LP convexity costs by having the arbitrageurs bid for the right to trade at a reduced rate. I wanted to dive into that, but I thought it would be helpful to see how arbitrage profits relate to LP convexity costs, as this is not obvious. Further, people in this space use different terms and formulas for what I am calling the LP convexity costs, and it would be useful to clarify how they differ. Ultimately, loss vs. rebalancing (LvR), impermanent loss ..read more

The crypto bull market is back, best exemplified by worthless meme coins PEPE and Shiba rising to market caps of $3B and $21B, respectively. These types of coins have lottery-like payoffs, making them enticing buys when crypto bros are flush with 'house money.' They could also highlight a worst-case scenario for liquidity providers (LPs), who are short volatility. This is another example of the positive volatility/return correlation unique to crypto. In standard asset classes, higher volatility is correlated with negative returns, which is why a long volatility position has a negative beta in ..read more

 A puzzling aspect of automated market makers (AMMs) is that LPs, in aggregate, lose money, and no one seems to care. Uniswap is the most prominent AMM developer here, currently worth $9B. Uniswap's docs page only indirectly addresses LP profitability, pointing to theoretical papers with no data (link) or anecdotal empirical blog posts from 2019 (link). If you search this topic and look for an empirical analysis, you generally get a discursive analysis that is not even wrong. For example, one paper states Our supporting data analysis of the risks and returns of real Uniswap V3 liquidity p ..read more

 Automated market makers (AMMs) invariably present their Liquidity Providers (LPs) with convexity costs. Hedging does not eliminate or even reduce these costs but it does lower volatility. With lower cost volatility, an LP does not need as much capital to cover these losses, so considering capital is expensive, it is correct to say hedging reduces costs, though only indirectly.   Consider the pool with a token A vs. USDC in the pool. If an LP provides 777 units of liquidity, his initial LP position would look as in Table 1 below. Table 1 To model the LP's position, we can use ..read more

Last week, I commented on the University of Chicago professor Eric Budish et al.'s hedge fund sniping model but neglected a more significant point. To recap, Budish modeled a scenario likened to a Centralized Limit Order Book (CLOB), where liquidity providers (LPs) post bids and asks, and takers then take those orders (link). Assuming several high-frequency traders (HFTs) are posting the bids and asks, for any resting lone bid or ask, a stale quote will generate a race between the lone HFT LP and several HFTs acting as takers. If the race winner is random, the odds are the LP posting the order ..read more