Liquidity providers in concentrated AMMs face a trade-off between fee income and impermanent loss, with optimal range selection depending on volatility, tradingLiquidity providers in concentrated AMMs face a trade-off between fee income and impermanent loss, with optimal range selection depending on volatility, trading

Liquidity Providers Face a Trade-Off Between Fees and Loss in Concentrated AMMs

Abstract

1. Introduction

2. Constant function markets and concentrated liquidity

  • Constant function markets
  • Concentrated liquidity market

3. The wealth of liquidity providers in CL pools

  • Position value
  • Fee income
  • Fee income: pool fee rate
  • Fee income: spread and concentration risk
  • Fee income: drift and asymmetry
  • Rebalancing costs and gas fees

4. Optimal liquidity provision in CL pools

  • The problem
  • The optimal strategy
  • Discussion: profitability, PL, and concentration risk
  • Discussion: drift and position skew

5. Performance of strategy

  • Methodology
  • Benchmark
  • Performance results

6. Discussion: modelling assumptions

  • Discussion: related work

7. Conclusions And References

\

Conclusions

We studied the dynamics of the wealth of an LP in a CPM with CL who implements a selffinancing strategy that dynamically adjusts the range of liquidity. The wealth of the LP consists of the position value and fee revenue. We showed that the position value depreciates due to PL and the LP widens her liquidity range to minimise her exposure to PL. On the other hand, the fee revenue is higher for narrow ranges, but narrow ranges also increase concentration risk. We derived the optimal strategy to provide liquidity in a CPM with CL when the LP maximises expected utility of terminal wealth. This strategy is found in closed-form for log-utility of wealth, and it shows that liquidity provision is subject to a profitability condition. In particular, the potential gains from fees, net of gas fees and concentration costs, must exceed PL. Our model shows that the LP strategically adjusts the spread of her position around the reference exchange rate; the spread depends on various market features including tthe volatility of the rate, the liquidity taking activity in the pool, and the drift of the rate.

\

References

Adams, H., Zinsmeister, N., Salem, M., Keefer, R., Robinson, D., 2021. Uniswap v3 core. Technical Report.

Angeris, G., Chitra, T., Evans, A., 2022. When does the tail wag the dog? curvature and market making .

Angeris, G., Kao, H.T., Chiang, R., Noyes, C., Chitra, T., 2021. An analysis of uniswap markets.

Avellaneda, M., Stoikov, S., 2008. High frequency trading in a limit order book. Quantitative Finance 8, 217–224. doi:10.1080/14697680701381228.

Barger, W., Lorig, M., 2019. Optimal liquidation under stochastic price impact. International Journal of Theoretical and Applied Finance 22, 1850059.

Bergault, P., Bertucci, L., Bouba, D., Gueant, O., Guilbert, J., 2024. Price-aware automated market makers: Models ´ beyond brownian prices and static liquidity. arXiv preprint arXiv:2405.03496 .

Bergault, P., Drissi, F., Gueant, O., 2022. Multi-asset optimal execution and statistical arbitrage strategies un- ´ der Ornstein–Uhlenbeck dynamics. SIAM Journal on Financial Mathematics 13, 353–390. doi:10.1137/ 21M1407756.

Bergault, P., Evangelista, D., Gueant, O., Vieira, D., 2021. Closed-form approximations in multi-asset market making. ´ Applied Mathematical Finance 28, 101–142. doi:10.1080/1350486X.2021.1949359.

Biais, B., 1993. Price formation and equilibrium liquidity in fragmented and centralized markets. The Journal of Finance 48, 157–185.

Biais, B., Capponi, A., Cong, L.W., Gaur, V., Giesecke, K., 2023. Advances in blockchain and crypto economics. Management Science 69, 6417–6426.

Capponi, A., Jia, R., 2021. The adoption of blockchain-based decentralized exchanges. arXiv preprint arXiv:2103.08842 .

Capponi, A., Jia, R., Yu, S., 2023a. Price discovery on decentralized exchanges. Available at SSRN 4236993 .

Capponi, A., Jia, R., Zhu, B., 2023b. The paradox of just-in-time liquidity in decentralized exchanges: More providers can sometimes mean less liquidity. Available at SSRN .

Cartea, A., Donnelly, R., Jaimungal, S., 2017. Algorithmic trading with model uncertainty. SIAM Journal on Financial ´ Mathematics 8, 635–671. Cartea, A., Donnelly, R., Jaimungal, S., 2018. Enhancing trading strategies with order book signals. Applied Mathe- ´ matical Finance 25, 1–35. Cartea, A., Drissi, F., Monga, M., 2022. Decentralised finance and automated market making: Execution and specu- ´ lation. Available at SSRN 4144743 .

Cartea, A., Drissi, F., Monga, M., 2023a. Execution and statistical arbitrage with signals in multiple automated market ´ makers, in: 2023 IEEE 43rd International Conference on Distributed Computing Systems Workshops (ICDCSW), IEEE. pp. 37–42.

Cartea, A., Drissi, F., Monga, M., 2023b. Predictable losses of liquidity provision in constant function markets and ´ concentrated liquidity markets. Applied Mathematical Finance 30, 69–93.

Cartea, A., Drissi, F., S ´ anchez-Betancourt, L., Siska, D., Szpruch, L., 2023c. Automated market makers designs ´ beyond constant functions. Available at SSRN 4459177 .

Cartea, A., Jaimungal, S., Penalva, J., 2015. Algorithmic and high-frequency trading. Cambridge University Press.

Cartea, A., Jaimungal, S., Ricci, J., 2014. Buy low, sell high: A high frequency trading perspective. SIAM Journal on ´ Financial Mathematics 5, 415–444.

Cartea, A., Jaimungal, S., S ´ anchez-Betancourt, L., 2021. Latency and liquidity risk. International Journal of Theoret- ´ ical and Applied Finance 24, 2150035.

Cartea, A., S ´ anchez-Betancourt, L., 2021. The shadow price of latency: Improving intraday fill ratios in foreign ´ exchange markets. SIAM Journal on Financial Mathematics 12, 254–294.

Cartea, A., Wang, Y., 2020. Market making with alpha signals. International Journal of Theoretical and Applied ´ Finance 23, 2050016.

Chiu, J., Koeppl, T.V., 2019. Blockchain-based settlement for asset trading. The Review of Financial Studies 32, 1716–1753.

Donnelly, R., 2022. Optimal execution: A review. Applied Mathematical Finance 29, 181–212.

Donnelly, R., Lorig, M., 2020. Optimal trading with differing trade signals. Applied Mathematical Finance 27, 317–344. Drissi, F., 2022. Solvability of differential riccati equations and applications to algorithmic trading with signals. Applied Mathematical Finance 29, 457–493. doi:10.1080/1350486X.2023.2241130.

Drissi, F., 2023. Models of market liquidity: Applications to traditional markets and automated market makers. Available at SSRN 4424010 . Engel, D., Herlihy, M., 2021a. Composing networks of automated market makers, in: Proceedings of the 3rd ACM Conference on Advances in Financial Technologies, pp. 15–28.

Engel, D., Herlihy, M., 2021b. Presentation and publication: Loss and slippage in networks of automated market makers. arXiv preprint arXiv:2110.09872 .

Fan, Z., Marmolejo-Cossio, F., Moroz, D.J., Neuder, M., Rao, R., Parkes, D.C., 2021. Strategic liquidity provision in uniswap v3. arXiv preprint arXiv:2106.12033 .

Fan, Z., Marmolejo-Coss´ıo, F.J., Altschuler, B., Sun, H., Wang, X., Parkes, D., 2022. Differential liquidity provision in uniswap v3 and implications for contract design, in: Proceedings of the Third ACM International Conference on AI in Finance, pp. 9–17.

Forde, M., Sanchez-Betancourt, L., Smith, B., 2022. Optimal trade execution for Gaussian signals with power-law ´ resilience. Quantitative Finance 22, 585–596.

Fukasawa, M., Maire, B., Wunsch, M., 2023. Model-free hedging of impermanent loss in geometric mean market makers. arXiv preprint arXiv:2303.11118 .

Goyal, M., Ramseyer, G., Goel, A., Mazieres, D., 2023. Finding the right curve: Optimal design of constant function ` market makers, in: Proceedings of the 24th ACM Conference on Economics and Computation, pp. 783–812.

Gueant, O., 2016. The Financial Mathematics of Market Liquidity: From optimal execution to market making. ´ volume 33. CRC Press.

Gueant, O., 2017. Optimal market making. Applied Mathematical Finance 24, 112–154. doi: ´ 10.1080/1350486X. 2017.1342552.

He, X.D., Yang, C., Zhou, Y., 2024. Liquidity pool design on automated market makers. arXiv preprint arXiv:2404.13291 .

Heimbach, L., Schertenleib, E., Wattenhofer, R., 2022. Risks and returns of Uniswap v3 liquidity providers.

Ho, T.S., Stoll, H.R., 1983. The dynamics of dealer markets under competition. The Journal of Finance 38, 1053– 1074.

Lı, T., Naik, S., Papanicolaou, A., Schonleber, L., 2023. Yield farming for liquidity provision . ¨

Lipton, A., Treccani, A., 2021. Blockchain and Distributed Ledgers: Mathematics, Technology, and Economics. World Scientific.

Lommers, K., Kim, J., Skidan, B., 2023. The case for stochastically dynamic AMMs. Preprint.

Milionis, J., Moallemi, C.C., Roughgarden, T., 2023. Automated market making and arbitrage profits in the presence of fees. arXiv preprint arXiv:2305.14604 .

Milionis, J., Moallemi, C.C., Roughgarden, T., Zhang, A.L., 2022. Automated market making and loss-versusrebalancing. arXiv preprint arXiv:2208.06046 .

:::info Authors:

  1. Alvaro Cartea ´
  2. Fayc¸al Drissia
  3. Marcello Monga

:::

:::info This paper is available on arxiv under CC0 1.0 Universal license.

:::

\

Market Opportunity
Polytrade Logo
Polytrade Price(TRADE)
$0.05403
$0.05403$0.05403
+0.12%
USD
Polytrade (TRADE) Live Price Chart
Disclaimer: The articles reposted on this site are sourced from public platforms and are provided for informational purposes only. They do not necessarily reflect the views of MEXC. All rights remain with the original authors. If you believe any content infringes on third-party rights, please contact service@support.mexc.com for removal. MEXC makes no guarantees regarding the accuracy, completeness, or timeliness of the content and is not responsible for any actions taken based on the information provided. The content does not constitute financial, legal, or other professional advice, nor should it be considered a recommendation or endorsement by MEXC.

You May Also Like

Ethereum Options Expiry Shows Risks Below $2,900

Ethereum Options Expiry Shows Risks Below $2,900

The post Ethereum Options Expiry Shows Risks Below $2,900 appeared on BitcoinEthereumNews.com. Ether (ETH) has been unable to sustain prices above $3,400 for the
Share
BitcoinEthereumNews2025/12/25 10:24
Fed forecasts only one rate cut in 2026, a more conservative outlook than expected

Fed forecasts only one rate cut in 2026, a more conservative outlook than expected

The post Fed forecasts only one rate cut in 2026, a more conservative outlook than expected appeared on BitcoinEthereumNews.com. Federal Reserve Chairman Jerome Powell talks to reporters following the regular Federal Open Market Committee meetings at the Fed on July 30, 2025 in Washington, DC. Chip Somodevilla | Getty Images The Federal Reserve is projecting only one rate cut in 2026, fewer than expected, according to its median projection. The central bank’s so-called dot plot, which shows 19 individual members’ expectations anonymously, indicated a median estimate of 3.4% for the federal funds rate at the end of 2026. That compares to a median estimate of 3.6% for the end of this year following two expected cuts on top of Wednesday’s reduction. A single quarter-point reduction next year is significantly more conservative than current market pricing. Traders are currently pricing in at two to three more rate cuts next year, according to the CME Group’s FedWatch tool, updated shortly after the decision. The gauge uses prices on 30-day fed funds futures contracts to determine market-implied odds for rate moves. Here are the Fed’s latest targets from 19 FOMC members, both voters and nonvoters: Zoom In IconArrows pointing outwards The forecasts, however, showed a large difference of opinion with two voting members seeing as many as four cuts. Three officials penciled in three rate reductions next year. “Next year’s dot plot is a mosaic of different perspectives and is an accurate reflection of a confusing economic outlook, muddied by labor supply shifts, data measurement concerns, and government policy upheaval and uncertainty,” said Seema Shah, chief global strategist at Principal Asset Management. The central bank has two policy meetings left for the year, one in October and one in December. Economic projections from the Fed saw slightly faster economic growth in 2026 than was projected in June, while the outlook for inflation was updated modestly higher for next year. There’s a lot of uncertainty…
Share
BitcoinEthereumNews2025/09/18 02:59
Arizona Senator Proposes Exempting Bitcoin and Crypto from Taxes

Arizona Senator Proposes Exempting Bitcoin and Crypto from Taxes

Understanding the specific tax exemption proposal's scope, mechanics, and limitations provides foundation for evaluating feasibility and implications. The exemption presumably covers capital gains taxes on cryptocurrency appreciation at state level, though personal income tax and corporate tax treatment requires clarification. Scope questions include whether exemption applies to trading profits, mining income, staking rewards, DeFi yields, NFT sales, and business cryptocurrency revenue.
Share
MEXC NEWS2025/12/25 11:47