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Darrius2020/RL_quant_btc

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Hugging Face2026-03-30 更新2026-03-29 收录
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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**. --- # 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
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Darrius2020
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