Multi-Market Algorithmic Trading Strategies

📌 Overview

This repository contains two complete algorithmic trading systems developed and tested across six global markets (forex and crypto). The goal was to create a risk-managed framework capable of generating consistent monthly returns while keeping drawdown tightly controlled.

✅ Strategy 1: Momentum (Candle-based)

• Triggered by price action momentum (e.g., consecutive bullish/bearish candles)
• SL/TP dynamically scaled based on candle structure
• Tested on BTCUSD, ETHUSD, and EURUSD

✅ Strategy 2: Hilega Milega (Indicator-based)

• Based on crossover signals using Hilega Milega indicator + RSI filters
• Trailing stop logic built into the system
• Tested on AUDUSD, AUDCAD, and USDJPY

📈 Results Summary

• Avg Monthly Return: ~4.16%
• Max Drawdown: ≤10%
• Markets Tested: BTCUSD, ETHUSD, EURUSD, AUDCAD, AUDUSD, USDJPY
• Prop Firm Challenge: Successfully passed (13% profit in under 3 months)

📂 Repository Structure

. ├── strategies/ │ ├── momentum/ │ │ ├── strategy_1_momentum.py │ │ └── output1.csv │ ├── hm/ │ │ ├── strategy_2_hilega_milega.py │ │ └── output2.csv ├── utils/ │ ├── momentum/ │ │ └── maxloss_momentum.py │ ├── hm/ │ │ └── maxloss_hm.py ├── results/ │ └── [performance snapshots, trade logs, screenshots] └── README.md

🧠 Key Features

• Multi-market execution with normalized x scaling logic
• SL/TP optimization through variable-based segmentation
• Drawdown computation from every possible start-date
• Strategy-layered portfolio allocation
• Real-world backtests, not just theoretical models

📢 Notes

• The project was built iteratively over a year, combining manual backtesting, code-based simulations, and live trading validation.
• Code is not beginner-friendly by design — it’s real-world quant logic, not a tutorial.
• All strategy logic and supporting files are publicly shared for credibility and transparency.

📜 License

MIT License — free to use, adapt, and modify with attribution.

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For the full story behind how this project was built and validated, check out my LinkedIn article (https://www.linkedin.com/posts/swapnil-phutane-64100129a_from-raw-ideas-to-code-testing-optimization-activity-7343247964938653698-MHhO?utm_source=share&utm_medium=member_desktop&rcm=ACoAAEhCalEBSXurViZCpRx8NIRefuIxDnAAucI).