Abstract
The emerging decentralized financial ecosystem (DeFi) is comprised of numerous protocols, one type being lending protocols. People make transactions in lending protocols, each of which is attributed to a specific blockchain address which could represent an externally-owned account (EOA) or a smart contract. Using Aave, one of the largest lending protocols, we summarize the transactions made by each address in each quarter from January 1, 2021, through December 31, 2022. We cluster these quarterly summaries to identify and name common patterns of quarterly behavior in Aave. We then use these clusters to glean insights into the dominant behaviors in Aave. We show that there are three kinds of keepers, i.e., a specific type of users tasked with the protocol’s governance, but only one kind of keeper finds consistent success in making profits from liquidations. We identify the largest-scale accounts in Aave and the highest-risk kinds of behavior on the platform. Additionally, we use the temporal aspect of the clusters to track how common behaviors change through time and how usage has shifted in the wake of major events that impacted the crypto market, and we show that there seem to be problems with user retention in Aave as many of the addresses that perform transactions do not remain in the market for long.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
- 7.
References
www.fortune.com/2022/01/04/crypto-banned-china-other-countries/
www.coindesk.com/learn/the-fall-of-terra-a-timeline-of-the-meteoric-rise-and-crash-of-ust-and-luna/
www.theguardian.com/business/2023/jan/11/ftx-fraud-value-crypto-sbf
Adler, A.: lamW: Lambert-W Function (2015). https://doi.org/10.5281/zenodo.5874874,www.CRAN.R-project.org/package=lamW, r package version 2.1.1
Antonio Juliano: dYdX: A Standard for Decentralized Margin Trading and Derivatives. Tech. rep. (09 2017), www.whitepaper.dydx.exchange/
Bezdek, J.C., Ehrlich, R., Full, W.: Fcm: The fuzzy c-means clustering algorithm. Comput. Geosci. 10(2), 191–203 (1984). https://doi.org/10.1016/0098-3004(84)90020-7, www.sciencedirect.com/science/article/pii/0098300484900207
Boado, E.: AAVE Protocol Whitepaper. Technical report (01 2020). www.cryptocompare.com/media/38553941/aave_protocol_whitepaper_v1_0.pdf
Boado, E.: AAVE Protocol Whitepaper V2.0. Technical report (12 2020). www.cryptorating.eu/whitepapers/Aave/aave-v2-whitepaper.pdf
Buterin, V.: Ethereum: A next-generation smart contract and decentralized application platform (2014). www.github.com/ethereum/wiki/wiki/White-Paper
Cebeci, Z.: Comparison of internal validity indices for fuzzy clustering. J. Agricult. Inf. (2), 1–14 (2019). https://doi.org/10.17700/jai.2019.10.2.537
Choi, S.M., Park, J., Nguyen, Q., Cronje, A.: Fantom: a scalable framework for asynchronous distributed systems (2018). https://doi.org/10.48550/ARXIV.1810.10360, www.arxiv.org/abs/1810.10360
Frangella, E., Herskind, L.: AAVE V3 Technical Paper. Technical report (01 2022). www.github.com/aave/aave-v3-core/blob/master/techpaper/Aave_V3_Technical_Paper.pdf
Green, A., Cammilleri, C., Erickson, J.S., Oshani, Seneviratne, Bennett, K.P.: Defi survival analysis: insights into risks and user behaviors (2022). www.marble-conference.org/marble2022-cfp
Kanani, J., Sandeep Nailwal, A.A.: Matic network whitepaper. www.github.com/maticnetwork/whitepaper (2020)
Kalodner, H.A., Goldfeder, S., Chen, X., Weinberg, S.M., Felten, E.W.: Arbitrum: Scalable, private smart contracts. In: USENIX Security Symposium (2018)
Kolde, R.: pheatmap: Pretty Heatmaps (2019). www.CRAN.R-project.org/package=pheatmap, r package version 1.0.12
Kozhan, R., Viswanath-Natraj, G.: Decentralized stablecoins and collateral risk. WBS Finance Group Research Paper Forthcoming (2021)
MakerDAO: The Maker Protocol: MakerDAO’s Multi-Collateral Dai (MCD) System. Technical report. www.makerdao.com/en/whitepaper/#abstract
Mueller, P.: Defi leveraged trading: Inequitable costs of decentralization (2022). www.dx.doi.org/10.2139/ssrn.4241356
Qin, K., Zhou, L., Gamito, P., Jovanovic, P., Gervais, A.: An empirical study of defi liquidations: Incentives, risks, and instabilities. In: Proceedings of the 21st ACM Internet Measurement Conference, pp. 336–350 (2021)
R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2022). www.R-project.org/
Leshner, R., Hayes, G.: Compound: The money market protocol. Technical report. (02 2019). www.compound.finance/documents/Compound.Whitepaper.pdf
Rousseeuw, P.J.: Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53–65 (1987). https://doi.org/10.1016/0377-0427(87)90125-7, www.sciencedirect.com/science/article/pii/0377042787901257
Sekniqi, K., Laine, D., Buttolph, S., Sirer, E.G.: Avalanche platform (2020). www.assets.website-files.com/5d80307810123f5ffbb34d6e/6008d7bbf8b10d1eb01e7e16_Avalanche%20Platform%20Whitepaper.pdf
Team, H.: Harmony technical whitepaper (2020). www.harmony.one/whitepaper.pdf
Thorndike, R.: Who belongs in the family? Psychometrika 18(4), 267–276 (1953). https://doi.org/10.1007/BF02289263
Tyneway, M.: Optimism (2020). www.github.com/ethereum-optimism/optimism
Acknowledgements
The authors acknowledge the support from NSF IUCRC CRAFT center research grants (CRAFT Grants #22003, #22006) for this research. The opinions expressed in this publication and its accompanying code base do not necessarily represent the views of NSF IUCRC CRAFT. This work was supported by the Rensselaer Institute for Data Exploration and Applications (IDEA). We also would like to thank Amberdata for providing some of the data used in this work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Green, A., Giannattasio, M., Wang, K., Erickson, J.S., Seneviratne, O., Bennett, K.P. (2023). Characterizing Common Quarterly Behaviors in DeFi Lending Protocols. In: Pardalos, P., Kotsireas, I., Knottenbelt, W.J., Leonardos, S. (eds) Mathematical Research for Blockchain Economy. MARBLE 2023. Lecture Notes in Operations Research. Springer, Cham. https://doi.org/10.1007/978-3-031-48731-6_4
Download citation
DOI: https://doi.org/10.1007/978-3-031-48731-6_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-48730-9
Online ISBN: 978-3-031-48731-6
eBook Packages: Economics and FinanceEconomics and Finance (R0)