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Jupyter Notebook 97.72% Makefile 0.04% Python 2.23% Shell 0.01% Dockerfile 0.01%
ethereum blockchain python dao uniswap graph algorithmic-trading cryptocurrency edge trading

blockchain-science-py's Introduction

โ›“๐Ÿ“Š๐Ÿ blockchain science - python edition




my cryptography experiments


  • fixed-graph-py, generate zero-knowledge proof symbolic graphs:
    • in zkps we want to prove a statement where f evaluated at x_i results in (y_1,...,y_n), i.e., f(x_1, ..., x_n) = (y_1, ..., y_n). this can be expressed as a fixed computational graph, where relationships between nodes are related by operations such as multiplication or addition. in addition, some nodes can be related with an equality relationship on which the node's value is computed outside of the graph and constrained by a hint.



my trading bots and strategies


  • cointegration trading bots and CLI:
    • run highly customized trading bots with statistical algorithmic strategies such as cointegration. Include an option for docker deployment.



my jupyter notebooks










external resources


blockchain-science-py's People

Contributors

go-outside-helper avatar mia-stein avatar

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blockchain-science-py's Issues

Build and deploy bot2


Bot2's setup:

1. check constants inside .env
2. connect to REST API and Websockets
3. set leverage
4. start a loop with "while True"

Bot2's execution (inside a while True loop)

5. get z-score
6. check open positions and net P&L
7. close all positions if z-score is not relevant or if poor P&L performance
8. check how much capital is invested
9. open new positions
10. repeat each time period

Finish writing/deploying bot2

Bot2's setup:

  1. check constants inside .env
  2. connect to REST API and Websockets
  3. set leverage
  4. start a loop with "while True"

Bot2's execution (inside a while True loop)

  1. get z-score
  2. check open positions and net P&L
  3. close all positions if z-score is not relevant or if poor P&L performance
  4. check how much capital is invested
  5. open new positions
  6. repeat each time period

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