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| annotations_creators: | |
| - automated | |
| language: | |
| - en | |
| license: | |
| - mit | |
| task_categories: | |
| - time-series-forecasting | |
| - reinforcement-learning | |
| tags: | |
| - finance | |
| - stock-market | |
| - technical-analysis | |
| - yfinance | |
| size_categories: | |
| - 10K<n<100K | |
| # π Multi-Agent RL Trading System - Dataset | |
| This dataset contains historical OHLCV (Open, High, Low, Close, Volume) data for **AAPL**, **MSFT**, and **GOOGL**, pre-processed for Reinforcement Learning based trading systems. | |
| ## π Dataset Content | |
| The dataset consists of CSV files downloaded via `yfinance`: | |
| * `AAPL.csv`: Apple Inc. daily data (Jan 2018 - Dec 2024). | |
| * `MSFT.csv`: Microsoft Corp. daily data (Jan 2018 - Dec 2024). | |
| * `GOOGL.csv`: Alphabet Inc. daily data (Jan 2018 - Dec 2024). | |
| ## π Columns | |
| | Column | Description | | |
| | :--- | :--- | | |
| | **Date** | Trading date (YYYY-MM-DD) | | |
| | **Open** | Opening price | | |
| | **High** | Highest price of the day | | |
| | **Low** | Lowest price of the day | | |
| | **Close** | Closing price (Adjusted for splits/dividends) | | |
| | **Volume** | Number of shares traded | | |
| ## βοΈ Usage | |
| This data is designed to be fed into a Feature Engineering pipeline (calculating RSI, MACD, etc.) before being used by the `TradingEnv`. | |
| ```python | |
| import pandas as pd | |
| # Load data | |
| df = pd.read_csv("AAPL.csv", parse_dates=['Date'], index_col='Date') | |
| print(df.head()) | |
| ``` | |
| ## π Related Models | |
| * **Trained Agents**: [AdityaaXD/Multi-Agent_Reinforcement_Learning_Trading_System_Models](https://huggingface.co/AdityaaXD/Multi-Agent_Reinforcement_Learning_Trading_System_Models) | |
| * **GitHub Repository**: [ADITYA-tp01/Multi-Agent-Reinforcement-Learning-Trading-System-Data](https://github.com/ADITYA-tp01/Multi-Agent-Reinforcement-Learning-Trading-System-Data) | |
| ## β οΈ Source | |
| Data was sourced from Yahoo Finance API. Not intended for real financial advice or live trading decisions. | |
| ## π οΈ Credits | |
| Collected by **Adityaraj Suman** for the Multi-Agent RL Trading System project. | |