Created on 25th February 2024
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Quantitative finance is $14B industry (as of 2021) and DeFi has already reached $20B as of last year. The former has sophisticated modeling tools for paper trading without deploying their algorithms to the real world so they don't lose their billions of dollars of assets under management ($300B in 2023), so why doesn't DeFi for it's billions? ($92B in March '24).
When companies have massive expenditures like a $50M rocket launch, they run thousands of models and simulations to make sure it doesn't crash and burn. Because there isn't a well known, easy to use tool for this type of modeling with a simple enough user interface for initial modeling, nor a comprehensive modeling tool for modifying relevant parametrs in depth, we get disaster scenarios like the $LUNA crash that could've been easily avoided with simple modeling.
By using DeFiPy - the first and only open source Python package for modelling in DeFi that is a full Python refactor of UniSwap V2 smart contracts, and the 0x real time price API, we were able to combine the two into a live paper trading tool that allows users to select from the various blockchains, tokens, and stablecoins that 0x Price API provides to select a live liquidity pool as the basis of the modeling tool.
We also added the ability for users to select modeling parameters, such as the maximum swap size allowed by the pool, the randomized trading bias between the selected coin and respective stablecoin in the pool, and the profitability of your position based on liquidity provided.
On top of all that we've launched a live dashboard so that users can easily interact with the model and visualize relevant activity and parameters, all while tracking the live pool data from the 0x Price API.
These are the first steps necessary to make simple DeFi modeling a norm in the industry by simulating data based on a live price feed so that we can avoid the all too common crash and burns that plague the industry.
Tracks Applied (2)
0x
Technologies used
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