📈 Algorithmic Trading Simulator (SMA Crossover)

A Python-based backtesting tool that implements a 20/50-day Simple Moving Average (SMA) crossover strategy.
It fetches historical stock data via Yahoo Finance, executes trades with next-day discipline to avoid look-ahead bias, logs results into SQLite, and generates equity curve plots comparing the strategy against a Buy & Hold benchmark.

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🔧 Features

• 📊 Historical stock data retrieval with yFinance
• 📉 Implements short-term vs long-term SMA crossover strategy
• 🗄️ Logs trades and returns into SQLite database for reproducibility
• 📈 Plots equity curve vs Buy & Hold benchmark using matplotlib
• ✅ Avoids look-ahead bias by executing trades next day

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🛠️ Tech Stack

• Python 3.11
• pandas, NumPy
• yFinance
• matplotlib
• SQLite

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🚀 Quickstart

Clone the repository and set up your environment:

git clone https://github.com/USERNAME/trading-simulator.git
cd trading-simulator

# Create and activate virtual environment
python -m venv .venv
.venv\Scripts\activate   # On Windows

# Install dependencies
pip install -r requirements.txt

Run the backtest:
python backtest.py

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## 📊 Example Output

Running the backtest on **Nvidia Corporation (NVDA)** produces:

- `equity.png` → Equity curve of strategy vs Buy & Hold  
- `trades.db` → SQLite database log of trades  

Example equity curve output:
(See equity.png in the folder)
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