algorithmic-trading-engine

# ⚡ Algorithmic Trading Engine ### Quantitative Strategy Backtester · 3D Interactive Analytics · ML-Ready ![Python](https://img.shields.io/badge/Python-3.10+-3776ab?logo=python&logoColor=white) ![Streamlit](https://img.shields.io/badge/Streamlit-Live%20App-ff4b4b?logo=streamlit&logoColor=white) ![Plotly](https://img.shields.io/badge/Plotly-3D%20Interactive-3d3d3d?logo=plotly&logoColor=white) ![scikit-learn](https://img.shields.io/badge/scikit--learn-ML%20Models-f7931e?logo=scikit-learn&logoColor=white) ![XGBoost](https://img.shields.io/badge/XGBoost-Gradient%20Boosting-189fdd)
[🚀 **Launch Live Engine**](https://algorithmic-trading-engine-falgun-gadhiya.streamlit.app/) | [📊 **Interactive 3D Charts**](https://gadhiyafalgun-arch.github.io/algorithmic-trading-engine/) | [💻 **Source Code**](https://github.com/gadhiyafalgun-arch/algorithmic-trading-engine)

📸 Preview

👆 Click the image to launch the live engine

🧠 What It Does

A full end-to-end algorithmic trading engine that runs a complete pipeline on 8 stocks (AAPL, GOOGL, MSFT, AMZN, TSLA, SPY & more) from 2020–2024:

Phase	Description
📥 Data Pipeline	Fetches and cleans daily OHLCV data via `yfinance`
📐 Indicators	SMA, EMA, RSI, MACD, Bollinger Bands, ATR, Stochastic, VWAP
🎯 Strategies	SMA Crossover, RSI, MACD, Bollinger Bands, Combined Multi-Signal
📈 Backtesting	Realistic simulation — 0.1% commission, 0.05% slippage, stop-loss/take-profit
⚖️ Risk Management	VaR, Sharpe/Sortino/Calmar ratios, max drawdown, position sizing
🤖 Machine Learning	XGBoost + Random Forest with 100+ features, walk-forward validation
📊 Visualization	13 interactive 3D Plotly charts + Streamlit dashboard

🎮 Live Engine Features

🚀 Launch the Live Engine →

Feature	What You Can Do
🔀 Stock Selector	Switch between multiple listed stocks
📅 Date Range	Customize backtest period (2020–2024)
🎯 Strategy Picker	Choose from 5 strategies including Combined Multi-Signal
💰 Capital & Costs	Adjust initial capital, commission, and slippage
⚡ Risk Slider	Drag to see Low → Medium → High risk impact in real time
📊 Performance Grade	Auto-graded performance summary with key metrics

📊 Interactive 3D Charts

🌐 View Static 3D Charts →

Drag the ⚡ Risk Level slider to explore:

🟢 Low risk (0.25×) — Smaller positions, steadier equity curve
🟡 Medium risk (1.0×) — Default, balanced risk/return
🔴 High risk (3.0×) — Larger positions, amplified gains & drawdowns

Chart	Description
📊 Risk Bar (3D)	Portfolio backtest with interactive risk slider
📈 Equity Comparison	Side-by-side strategy equity curves
🤖 ML Signal	Machine learning buy/sell signals
📉 MACD	MACD momentum analysis
💼 Portfolio Backtest	Multi-stock portfolio results

🚀 Run Locally

```bash

Clone the repo

git clone https://github.com/gadhiyafalgun-arch/algorithmic-trading-engine.git cd algorithmic-trading-engine

Install dependencies

pip install -r requirements.txt

Run the full pipeline (generates charts)

python main.py

Or launch the Streamlit app locally

streamlit run app.py