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ProFi

Welcome to ProFi, the ultimate platform designed to simplify crypto trading for newbies. Our risk-adjusted safeness scores, calculated through a highly accurate algorithm, ensure a hassle-free trading experience.

ProFi

Created At

ETHOnline 2023

Winner of

🏊 Scroll — Pool Prize

Project Description

ProFi is a revolutionary project that aims to provide a comprehensive solution for crypto newbies . Crypto trading is a tough deal if you wish to steal cool profits & also keep risk of ponzi tokens spamming you away! But, that's no more the case. We introduce you to ProFi where we offer a one-stop platform, empowering users to navigate the complex world of cryptocurrencies with ease.

Understanding the importance of risk assessment in crypto trading, ProFi utilizes an advanced algorithm to calculate risk-adjusted safeness scores. Backtested on various crypto tokens, our algorithm achieves an impressive accuracy of 85%+

By leveraging advanced algorithms, ProFi's risk assessment and safeness scores provide accurate predictions on potential risk factors, helping users make smarter trading decisions.

ProFi's algorithm is rigorously backtested on a wide range of crypto tokens, ensuring its robustness and reliability in evaluating the risk associated with different cryptocurrencies.

How it's Made

  1. Well, the show begins with The Graph . We deployed a subgraph of our own to fetch the financial data of different tokens & use them for analysis.

  2. Then we started analysing data to deduce patterns & figure out patterns affecting the prices & safeness, volatility & market sentiment.

  3. To make that data public for everyone, we deployed that data on Web3.storage.

  4. We also build our app on FVM!

  5. But we need to constantly update the financial data so we also deployed it on Tableland

  6. Then, we deployed the smart contracts on Mantle & Scroll.

Finally we built a cool UX on react where the users can get the parameters of the algorithm and get the safeness score all at one click of a button.

Challenges

  1. We faced problems in data collection. We couldn't find a subgraph for it so we had to create & deploy our own.
  2. We also faced problems in analysing the parameters & assigning appropriate weights to them.
  3. Backtesting took around 1 complete week. That took a lot of sweat!
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