Hello,
I am looking for an experienced Python developer with strong knowledge of financial data handling, technical indicators, and backtesting frameworks to help validate a rule-based intraday trading strategy across multiple CFD instruments.
This is NOT a PineScript job.
I need a Python-based backtest that accurately simulates entries, exits, risk management, and multi-factor confluence conditions.
You will be provided with a clear, step-by-step specification outlining -
-Higher timeframe directional bias
-Multi-indicator confluences
-Liquidity sweep logic
-Break of structure detection
-Optional fair-value gap filter
-Risk & trade management rules
-Session-based execution windows
Your job is to translate that spec into a backtest, run it across historical data, and produce performance metrics.
What You Will Build -
-A Python script/notebook that:
-Loads OHLCV data for 5-minute timeframe
-Aggregates 4H candles for bias
-Computes multiple indicators (EMA, RSI, VWAP, ATR)
-Detects liquidity sweeps and internal structure breaks
-Executes trades based on the provided rules
-Applies ATR-based SL and fixed R:R TP
-Restricts trades to specific sessions
-Supports optional filters (toggle via parameters)
-Ensures only one open trade at a time
-Outputs full backtest results
-A final backtest report including -
-Win rate
-Expectancy (avg R per trade)
-Drawdown
-Equity curve
-Trades per session
-Distribution of returns
-Results per symbol (Gold, NAS100, US30)
Required Skills -
-Strong Python (Pandas, NumPy, TA-Lib or custom indicator coding)
-Experience with financial OHLCV data
-Experience building custom backtesting engines, not just using pre-built libraries
-Ability to detect structural patterns (swing highs/lows, BOS/iBOS)
-Ability to write clean, modular, well-commented code
-Clear communication
Deliverables -
1.Executable Python script or Jupyter notebook
2.Code implementing all entry, exit, and confluence rules
3.A run-ready backtest I can execute on my machine
4.Backtest results + summary report
5.Ability to tweak parameters (e.g. SL multiplier, FVG filter on/off)
What I Will Provide -
-A precise written specification with mathematical, coder-ready rules
-All trade logic (nothing to guess or interpret)
-Session rules
-Risk model
-Optional filters
-Example outputs for clarity
Project Type -
-One-time project
-Expected duration: 3–7 days
-Clear milestones:
-Setup & data → logic implementation → full backtest → final report
To Apply, Please Provide -
-Examples of similar backtesting or quantitative trading work
-Your experience with algo logic or indicator coding
-Confirmation you can start immediately
(You do not need to know PineScript — this is fully Python.)
Apply Now
Apply Now