text: 309,53,1339640488400400385,53836928,Tarun Chitra,"🚨⚠️ Paper Alert ⚠️🚨 Q: Have you wondered about math for the following? a) Optimal token qty to emit for yield farming incentives b) Hedging impermanent loss w/ options c) When do LPs not get rekt? A: New paper from moi, @alexhevans, @GuilleAngeris  <LINK> We highlight how to relate hedging costs and optimal yield farming in our final blog post 1. Greeks (∆, Γ, not @gakonst) are bounded by the curvature of the impact function 2. Curvature of CFMM controls how much you need to pay to avoid 🧛 attacks <LINK> This gives a quantitative answer to ""how much does @SushiSwap need to pay in $SUSHI to convince @UniswapProtocol liquidity for a particular pool to migrate?"" This cost varies from pair to pair and effectively decays to zero when you have a really gigantic pool <LINK> Exercise for the reader (really @MartinTassy and @_Dave__White_):  We generalize the profit conditions for Uniswap to arbitrary CFMMs. Find the proper renormalization (e.g. variance rescaling) to get a similar Kelly-style, continuous limit result for @CurveFinance <LINK> This fact lets you adjust a CFMM's curvature in order to change the interval for LP profitability Almost all ""limit order"" approximations in CFMMs that I've seen effectively end up being curvature adjustments to adjust the conditions in this tweet 👇🏾 <LINK> Which brings me to my final challenge: The @danrobinson (CFMMs) v. @SBF_Alameda (CLOBs) fight would be a infinitely more compelling if you compared 💣 continuous time, discrete price LOB 🧨 discrete time, continuous price CFMMs <LINK> For LOBs: Market makers adjust liquidity by adding/removing *discrete* price/quantity orders For CFMMs: MMs adjust liquidity by adjusting curvature (e.g. bounds for where they want liquidity to be used, adding/removing liquidity) All to replicate the famous Glosten drawing 👇🏾 <LINK> 👏🏾👏🏾👏🏾 for feedback/comments over the last 6mo: @ciamac @theyisun @adamlerer @ChiangRei @teo_leibowitz + some folks not on Twitter @CryptoCobain @alexhevans @GuilleAngeris Cobie, your brain is nuts, you never sleep and suck in heaps of information to form some dank, deep tweets  I salute you <LINK>",https://arxiv.org/abs/2012.08040,"Liquidity and trading activity on constant function market makers (CFMMs) such as Uniswap, Curve, and Balancer has grown significantly in the second half of 2020. Much of the growth of these protocols has been driven by incentivized pools or 'yield farming', which reward participants in crypto assets for providing liquidity to CFMMs. As a result, CFMMs and associated protocols, which were historically very small markets, now constitute the most liquid trading venues for a large number of crypto assets. But what does it mean for a CFMM to be the most liquid market? In this paper, we propose a basic definition of price sensitivity and liquidity. We show that this definition is tightly related to the curvature of a CFMM's trading function and can be used to explain a number of heuristic results. For example, we show that low-curvature markets are good for coins whose market value is approximately fixed and that high-curvature markets are better for liquidity providers when traders have an informational edge. Additionally, the results can also be used to model interacting markets and explain the rise of incentivized liquidity provision, also known as 'yield farming.' ",When does the tail wag the dog? Curvature and market making,9,"['🚨⚠️ Paper Alert ⚠️🚨\n\nQ: Have you wondered about math for the following?\n\na) Optimal token qty to emit for yield farming incentives\nb) Hedging impermanent loss w/ options\nc) When do LPs not get rekt?\n\nA: New paper from moi, @alexhevans, @GuilleAngeris \n\n<LINK>', 'We highlight how to relate hedging costs and optimal yield farming in our final blog post\n\n1. Greeks (∆, Γ, not @gakonst) are bounded by the curvature of the impact function\n\n2. Curvature of CFMM controls how much you need to pay to avoid 🧛 attacks\n\nhttps://t.co/WI9fbvuARv', 'This gives a quantitative answer to ""how much does @SushiSwap need to pay in $SUSHI to convince @UniswapProtocol liquidity for a particular pool to migrate?""\n\nThis cost varies from pair to pair and effectively decays to zero when you have a really gigantic pool https://t.co/ePovkIMqwD', 'Exercise for the reader (really @MartinTassy and @_Dave__White_): \n\nWe generalize the profit conditions for Uniswap to arbitrary CFMMs. Find the proper renormalization (e.g. variance rescaling) to get a similar Kelly-style, continuous limit result for @CurveFinance https://t.co/MNbrk3hPMJ', 'This fact lets you adjust a CFMM\'s curvature in order to change the interval for LP profitability\n\nAlmost all ""limit order"" approximations in CFMMs that I\'ve seen effectively end up being curvature adjustments to adjust the conditions in this tweet 👇🏾\n\nhttps://t.co/AQpS3JRLRZ', 'Which brings me to my final challenge:\n\nThe @danrobinson (CFMMs) v. @SBF_Alameda (CLOBs) fight would be a infinitely more compelling if you compared\n\n💣 continuous time, discrete price LOB \n🧨 discrete time, continuous price CFMMs https://t.co/LMFujC3jkY', 'For LOBs: Market makers adjust liquidity by adding/removing *discrete* price/quantity orders\n\nFor CFMMs: MMs adjust liquidity by adjusting curvature (e.g. bounds for where they want liquidity to be used, adding/removing liquidity)\n\nAll to replicate the famous Glosten drawing 👇🏾 https://t.co/wVRHwkhqxj', '👏🏾👏🏾👏🏾 for feedback/comments over the last 6mo:\n@ciamac @theyisun @adamlerer @ChiangRei @teo_leibowitz + some folks not on Twitter', '@CryptoCobain @alexhevans @GuilleAngeris Cobie, your brain is nuts, you never sleep and suck in heaps of information to form some dank, deep tweets \n\nI salute you https://t.co/GotXV6NQVE']",20,12,2124