Utilising Dynamic Weigths Changing with the goal of minimizing Impermanent Loss (IL) through implementing a open-loop, closed loop system(s) in a Balancer pool. Repository for containing all my working documents for the TE Balancer AMM research group See the HackMD for a more thorough overview
Ideally the codebase would reference the balancerv2cad python library found here, however I temporarily copied in the codebase with some modifications to particular methods to fit my needs. I would like to revert back to referencing the library again in the future.
Dataset | Description | Source |
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data/Binance_ETHUSDT_minute.csv | 1-Minute granular ETHUSDT pricing history data | http://www.cryptodatadownload.com/data/binance/ |
Notebook | Description |
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Math_Challenges.ipynb | Contains 'minimal' python implementation using vanilla, Pandas, Numpy etc. |
Python_Lib_Example.ipynb | Utilises the balancerv2cad python library to provide an approach to the Challenge math problems and further modeling |
playground.ipynb | WIP - Playing around with ETL on-chain data ingestion |
v2_simulation.ipynb | Dynamic Weights adjusting AMMs simulation notebook |