Each row of the dataset describes an investment vehicle at a certain date.

Here follows a concise description of the columns of the three files comprising the dataset, X_train and y_train.


  • date: A sequentially increasing integer representing a date. Time between subsequent dates is a constant, denoting an unknown but fixed frequency at which the data is sampled. The initial training dataset is composed of 268 dates.

  • id: A unique identifier representing the investment vehicle at a given date. Note that the same asset has a different id at each date.

  • 0,...,460: Anonymized features describing an investment vehicle at a given date. Derived from high-quality market data.


  • date: Same as in X_train.

  • id: Same as in X_train.

  • y: The target value to predict. It is related to the future performance of the investment vehicle at the given date. The value is normalized between -1 and 1.


  • Same structure as X_train but comprises only a few dates. This file is used to simulate the submission process locally via crunch.test(), or cruch test. The aim is to help participants debug their code and have successful submissions. A successful local test usually means no errors during execution on the submission platform.

The dataset is obfuscated.


  • X_train.parquet

  • y_train.parquet

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