---
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
---

# 📊 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.

## 📁 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).

## 📝 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 |

## ⚙️ 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())
```

## 🔗 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)


## ⚠️ Source

Data was sourced from Yahoo Finance API. Not intended for real financial advice or live trading decisions.

## 🛠️ Credits

Collected by **Adityaraj Suman** for the Multi-Agent RL Trading System project.