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size_categories:
- 1M<n<10M
tags:
- finance
- crypto
- BTC
---
# Dataset Description
These datasets contain **financial data related to Bitcoin**. They are used to train a **reinforcement learning (RL) agent** whose objective is to learn how to trade the Bitcoin market.
The agent relies on an architecture inspired by the **System 1 / System 2 cognitive model**:
- **System 1**: responsible for fast decision-making during trading.
- **System 2**: a pre-trained neural network designed to analyze the market regime and provide macro-level context to improve the decisions made by System 1.
More specifically, **System 2** is trained to **identify the market regime for the next 24 hours** and provide this information to System 1 in order to guide its trading actions.
The data is organized into **two main groups of datasets**: **Macro-State** and **Micro-State**.
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# Macro-State
The **Macro-State** group contains data describing the **macroeconomic evolution of the Bitcoin market as well as the state of the Bitcoin network**.
These datasets are used to **train System 2**, whose role is to detect market regimes.
The variables in these datasets are obtained from **transformations applied to raw on-chain and macro-financial data**, such as:
- **MVRV**
- **NVT**
- **Hash Rate**
- and other similar metrics.
The goal of these transformations is to **extract informative signals about the market structure and dynamics**, helping the agent better understand its environment.
Each row corresponds to **one day of market history**.
The datasets belonging to this group are:
- `metric_pretrain.csv`
- `metric_train.csv`
- `metric_test.csv`
---
# Micro-State
The **Micro-State** group contains data describing the **short-term microeconomic dynamics of the Bitcoin market**.
These datasets are used to **train System 1**, which performs the trading decisions.
Each row corresponds to **one hour of market history**.
The variables in this group are derived from **calculations based on OHLCV data (Open, High, Low, Close, Volume)**, allowing the extraction of indicators relevant for short-term trading decisions.
The datasets belonging to this group are:
- `price_train.csv`
- `price_test.csv`
---
# Dataset Time Range
The **overall market history** covered by the datasets spans from **2015/01/01 to 2026/03/03**, but the exact time ranges vary depending on the dataset:
1. **metric_pretrain.csv**: 2015/01/01 – 2018/07/19
2. **metric_train.csv**: 2018/07/20 – 2023/05/31
3. **metric_test.csv**: 2023/06/01 – 2026/03/03
4. **price_train.csv**: 2018/07/20 – 2023/05/31
5. **price_test.csv**: 2023/06/01 – 2026/03/03 |