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ML techiques are used to forecast short term returns in 14 popular cryptocurrencies. We have amassed a dataset of millions of rows of high-frequency market data dating back to 2018 which you can use to build your model.

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G-Research Crypto Forecasting

Over $40 billion worth of cryptocurrencies are traded every day. They are among the most popular assets for speculation and investment, yet have proven wildly volatile. Fast-fluctuating prices have made millionaires of a lucky few, and delivered crushing losses to others. Could some of these price movements have been predicted in advance?

In this competition, you'll use your machine learning expertise to forecast short term returns in 14 popular cryptocurrencies. We have amassed a dataset of millions of rows of high-frequency market data dating back to 2018 which you can use to build your model. Once the submission deadline has passed, your final score will be calculated over the following 3 months using live crypto data as it is collected.

The simultaneous activity of thousands of traders ensures that most signals will be transitory, persistent alpha will be exceptionally difficult to find, and the danger of overfitting will be considerable. In addition, since 2018, interest in the cryptomarket has exploded, so the volatility and correlation structure in our data are likely to be highly non-stationary.

This repo constitutes an attempt on the following Kaggle competition: https://www.kaggle.com/c/g-research-crypto-forecasting/overview/description

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ML techiques are used to forecast short term returns in 14 popular cryptocurrencies. We have amassed a dataset of millions of rows of high-frequency market data dating back to 2018 which you can use to build your model.

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