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Challenge DF

Challenge DF is a data science competition, run as part of Ocean Data Farming (DF). Each week, there is 5,000 OCEAN available, going to those who predict the price of ETH with the lowest error.

To participate, follow: Challenge DF Instructions

More info: "Introducing Challenge DF".

Example End-to-End Flows

These are example full submissions to the challenge. You can use any of them as a starting point.

  • Simple: To-the-point example, with simple input data (just ETH price) and simple model (linear dynamical model)
  • Model optimization: Same as Simple with added optimization using cross-validation to select best hyperparameters.
  • Compare models: Build models that predict 1-12 hours ahead in one shot. Compare linear, SVM, RF, and NN models.

Example Data Sources

These are examples of how to get data from various places. Each place has its own benefits.

Get ETH price data:

Inspiration: ideas for data & modeling

Here are ideas to get even more accurate results.

Inspiration from algorithmic trading

Getting into the head of a trader might inspire you in predicting ETH.

To help with that, the algorithmic trading flow README does a walk-through of the "Freqtrade" open-source trading tool with a custom trading strategy.

Appendix: Past challenges

Before Challenge DF, we held monthly "Predict-ETH" Challenges from Oct 2022 to Jul 2023 (7 total). Here they are:

Appendix: Predict-eth library

Predict-eth is a library on pypi.

To install: pip3 install predict-eth

To further develop it :

Metadata

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