Curve Finance Data Challenge Review & Insights Research
This contest offered incentives to explore the inner workings of Curve Finance. Participants analyzed trading volume patterns and behaviors on this decentralized exchange tailored for stablecoin trading and yield farming. Focused on technology adoption, this challenge examined liquidity pools, AMMs, CRV, veCRV, and utilized open data for their analysis.
Abstract
This research report encapsulates the findings from the Curve Finance Data Challenge, a competition that engaged 34 participants in a comprehensive analysis of the decentralized finance protocol. The challenge produced an average report length of 25 pages amongst competitors. Inside these pages covered a spectrum of topics from Exploratory Data Analysis (EDA), to the impact of veCRV on the protocol's governance and machine learning models. Participants investigated unusual activities, evaluated trading strategies, and analyzed the interplay between trading volume and liquidity. Additionally, the challenge spotlighted BIS use cases, pros, and cons, and the development of Predictive analytics via machine learning models, showcasing the integration of advanced data science in finance.
These diverse deep dives collectively contributed mature insights into the workings of Curve Finance, marking a significant step forward in the understanding and application of other market-leading decentralized finance protocols. The following provides a synopsis of facts, stats, challenge podium winners, and takeaways from this research sprint.
Winning Reports
Before the fun, we must spotlight the top 3 winners of this challenge that competed for a $5k USDC prize pool The winners are as follows:
1st Derek Hoyt:
Full report available to download: https://market.oceanprotocol.com/asset/did:op:6e723167d6abb94e2fb6e8a8d3aadbb1d89f00ab52ba914b2adbb35e7c947131
Winning Report Characteristics: Business Readiness, Statistical Inference, Data-driven recommendations
2nd Cyril Mawutor:
Full report available to download: https://market.oceanprotocol.com/asset/did:op:cc060649580fce423d483ce6fb7bac93bd5267bf8aa3019b46e7d41dabda1b71
Winning Report Characteristics: Data-driven recommendations, historical research, and application, Data quality
3rd Elisa Anderson:
Full report available to download: https://market.oceanprotocol.com/asset/did:op:64551ff16216542706af417fcdf0cd32e3c91f07c656ffeb20de91e448a1b0aa
Winning Report Characteristics: Business Readiness, Data-driven recommendations, Quantitative Research
This data challenge offered a wide range of topics about curve protocol. Key findings, indicators, and leading metrics are presented below in corresponding order to the data challenge hosted November — December 2023.
Part 1: Exploratory Data Analysis (EDA)
MEV
Over 25,000 MEV-related transactions have been executed through Curve. This is better said as game players game the game. Curve MEV basic statistics present an alternative indicator of on-chain movement and behavioral finance. This only accounts for transactions made on blockchain, and is a principal in decentralized finance to consider before further signs.
A key question presented in exploratory data analysis was to find significant changes in trading volume and identify potential causation.
The analysis in a basket of reports revealed the same three dates with the most significant changes in trading volume on Curve Finance.
These dates and their corresponding trading volumes are as follows:
• February 14, 2021: A trading volume of approximately 1.2935 × 1019
• August 14, 2020: A trading volume of approximately 1.116318 × 1019
• September 11, 2021: A trading volume of approximately 1.02 × 1019
These dates are significant as they represent the highest spikes in trading activity, indicating either increased user engagement or specific market events that drove many
transactions. Further investigation into these dates may provide insights into external factors or internal protocol changes influencing trading behavior on the Curve Finance platform.
Post/pre veCRV
veCRV (vote-escrowed CRV token) in 2020 brought voting power and enhanced community participation to its ecosystem. Quantitatively, it reduced token circulation by locking CRV into veCRV. Effectively reducing circulating supply drives the long-term alignment of CRV holders and the success + longevity of the protocol.
The plots below show the daily transaction count and volume around the veCRV launch date, highlighted by the red dashed line.
Protocol Averages
How did veCRV impact daily transactions and gas prices? The most straight-forward answer, plus statistical proof are shown in this snippet:
Trading Moving Averages
The 30-day moving average shows a smoothing of the daily fluctuations and indicates a sustained increase in veCRV token holders = There’s a steady increase in the amount of CRV being locked up, showing a growing interest in boosted yields incentive to the veCRV holders and also potentially participating in the governance of the protocol through veCRV.
Peak Trading Hours
The provided data on hourly trading volume demonstrates a distinct pattern of daily fluctuations. Trading activity exhibits a clear upward trend from the early morning hours, reaching its peak between 14:00 and 17:00 GMT. This period, encompassing the European and American afternoon hours, coincides with the overlap of major trading markets and heightened market activity. The peak trading hours, defined as the periods with the highest trading volume, are:
● 14:00 GMT to 15:00 GMT
● 16:00 GMT to 17:00 GMT
During these peak hours, trading volume consistently exceeds USD 160 billion, indicating a surge in market activity and investor participation.
Project Marinara — DeFi at work
A bonus question here entertained a thesis made this year for The Bank for International Settlements (BIS) and Project Mariana using Curve Finance Technology.
The Bank for International Settlements (BIS), often referred to as the “central bank of central banks,” is an international organization that fosters cooperation among central banks and other financial institutions. Established in 1930, the BIS plays a crucial role in promoting financial stability and facilitating international monetary cooperation. So why do they want to use Curve AMM and liquidity dynamic structure?
The integration of Automated Market Maker (AMM) technology, as exemplified by Project Mariana’s innovative use of Curve Finance algorithms, marks a paradigm shift in the landscape of cross-border financial transactions. The application of AMM mitigates long-standing financial risks by ensuring immediate execution and settlement of trades, effectively minimizing credit and settlement risks. This rapid, real-time settlement model reinforces financial trust and stability, revolutionizing how central banks exchange and manage digital currencies.
Key benefits from the responses post-experiment include:
• BIS aims to improve the efficiency and transparency of foreign exchange trading and settlement using AMMs.
• The use of Curve’s unique bonding curve in Project Mariana to minimize slippage in large transactions.
• The experiment with wCBDC-based foreign exchange trading and the development of bridges for asset transfers between different wCBDC systems.
• The use of a modified ERC-20 token standard for issuing wCBDCs, emphasizing interoperability between different central banks’ systems.
An example model made by a data challenge participants offers a fair ground for how to exchange architecture can occur:
This offers some Potential Benefits…
Efficiency: Integration can lead to faster and more cost-effective cross-border CBDC transactions.
Liquidity: Enhanced liquidity in CBDC pairs can mitigate price volatility and improve overall market stability.
Innovation: Incorporating DeFi technology fosters innovation in the central banking sector.
And a multitude of Macro Challenges…
Regulatory Compliance: Ensuring compliance with existing financial regulations and adapting them to the open source “decentralized” nature of DeFi is a significant challenge.
User Education: Users, including central banks, may need education on the intricacies of decentralized technologies and how to navigate them securely.
Summary
The Curve Finance Data Challenge report offered in-depth analyses from 34 participants on the decentralized finance protocol. It includes exploratory data analysis, the impact of veCRV on governance, analysis of unusual activities, trading strategies, and the relationship between trading volume and liquidity. The report also examined BIS use cases, and the application of predictive analytics through machine learning, highlighting the intersection of data science and finance. Key findings include insights on MEV transactions, significant changes in trading volumes, the influence of veCRV on transactions and gas prices, and trends in peak trading hours. The report also explores Project Mariana’s use of Curve Finance technology, underscoring potential benefits and challenges in integrating DeFi with traditional financial systems.
What Protocol would you like to see dove into next? Reach out to the Ocean Core team if your DeFi protocol could benefit from predictive analytics from a data challenge with Ocean Protocol.
Reach out to us in our discord #data-science-hub channel: https://discord.gg/yFRPH9PCN4
To see past, current, and future data challenges sponsored by Ocean, please visit https://oceanprotocol.com/earn/data-challenges.
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