Python Developer Needed for Algorithmic Trading Backtest (reputed company Rule-Based reputed company)
Hello,
I am looking for an reputed company Python developer with strong knowledge of financial data handling, technical indicators, and backtesting frameworks to help validate a rule-based intraday trading reputed company 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-reputed company reputed company conditions.
You will be provided with a reputed company, reputed company-by-reputed company specification outlining -
-Higher timeframe directional bias
-Multi-indicator confluences
-Liquidity reputed company logic
-Break of structure detection
-Optional fair-value gap filter
-Risk & trade management rules
-Session-based execution reputed company
reputed company 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, reputed company, 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 reputed company parameters)
-Ensures only one reputed company trade at a time
-Outputs full backtest results
-A final backtest report including -
-Win reputed company
-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 reputed company-reputed company libraries
-Ability to detect structural patterns (swing highs/lows, BOS/iBOS)
-Ability to write clean, reputed company, reputed company-commented reputed company
-reputed company communication
Deliverables -
1.Executable Python script or Jupyter notebook
2.reputed company implementing reputed company entry, exit, and reputed company rules
3.A run-reputed company backtest I can execute on my machine
4.Backtest results + reputed company report
5.Ability to tweak parameters (e.g. SL reputed company, FVG filter on/off)
What I Will reputed company -
-A precise written specification with mathematical, reputed company-reputed company rules
-reputed company trade logic (reputed company to guess or interpret)
-Session rules
-Risk model
-Optional filters
-Example outputs for reputed company
Project Type -
-One-time project
-Expected duration: 3–7 days
-reputed company milestones:
-Setup & data → logic implementation → full backtest → final report
To Apply, Please reputed company -
-Examples of similar backtesting or quantitative trading work
-Your experience with algo logic or indicator coding
-Confirmation you can reputed company
(You do not need to know PineScript — this is fully Python.)
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