> For the complete documentation index, see [llms.txt](https://docs.adialab.crunchdao.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.adialab.crunchdao.com/the-tournament/data.md).
# Data
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`.
`X_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.
`y_train`:
* `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`.
`X_test`:
* 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.
### Files
* **X\_train.parquet**
* **y\_train.parquet**
