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Specifications – Development of an MQL5 Expert Advisor (Reverse Engineering)

Project context:
I have access to a real trading history consisting of more than 500 trades executed over a period of approximately 3 years. These trades have been exported into a CSV file containing all available information, including date, time, symbol, order type, entry price, and exit price.

Important:
I do not have access to the original trading strategy that generated these trades.
The goal of this project is therefore to reconstruct a trading logic through reverse engineering, based solely on the existing historical data. This project should be considered a reverse engineering task: all analytical methods, trading indicators, and quantitative approaches are acceptable as long as the required deliverables are met.

Main objective:
To develop an Expert Advisor (EA), preferably in MQL5 or alternatively in Python, capable of:

  • Reproducing at least 90% of the trades contained in the CSV file during backtesting

  • Being usable in the future, both in live trading conditions and for further backtesting

  • Relying exclusively on the provided historical data

Provided data:

  • A CSV file containing the full trade history

  • Each row represents a single trade and includes, among others:

    • Date

    • Time

    • Instrument (e.g. XAUUSD)

    • Order type (BUY / SELL)

    • Entry price

    • Exit price

The developer will be expected to:

  • Analyze the provided data

  • Identify recurring patterns, rules, or common conditions

  • Derive an exploitable and coherent algorithmic trading logic

Functional scope of the Expert Advisor:
The EA must be able to:

  • Identify entry conditions (BUY / SELL)

  • Determine exit conditions

  • Be primarily specialized for gold (XAUUSD), with the possibility of deployment on other assets

  • Manage:

    • Stop Loss

    • Take Profit

    • Trade duration (maximum trade duration of 5 hours)

Backtesting requirements:

  • The EA must be fully backtestable on MetaTrader 5

  • It must allow a direct comparison between:

    • Trades generated by the EA

    • Trades contained in the CSV file

  • Minimum requirement: ≥ 90% match rate (dates, trade direction, and acceptable timing tolerance)

Parameters and configuration:

  • Adjustable parameters, including:

    • Trading hours

    • Price and timing tolerances

    • Money management (risk percentage per trade or fixed lot size)

  • The strategy should allow future optimization

Technical constraints:

  • Programming language: MQL5 or Python

  • Platform: MetaTrader 5

  • Code must be:

    • Clean

    • Well-commented

    • Well-structured

    • Easy to modify and maintain

  • Full compatibility with the MT5 Strategy Tester is required

Expected approach (Reverse Engineering):
The project relies on a strong analytical and quantitative approach, which may include:

  • Statistical analysis of trade entries and exits

  • Detection of rules based on:

    • Time-based conditions

    • Volatility

    • Price levels

    • Technical indicators (such as market volume profile, Fibonacci retracements, supply and demand zones, order flow)

  • Progressive reconstruction of a coherent and robust trading strategy

The final strategy does not need to be identical to the original one, as long as it:

  • Reproduces the historical trades

  • Is usable for future trading

  • Is profitable

Expected deliverables:

  • The Expert Advisor source and compiled files (.mq5 + .ex5) or the Python code

  • A detailed documentation explaining:

    • The strategy logic

    • Available parameters

    • Known limitations

    • Required libraries (for Python-based solutions)

  • A backtesting report demonstrating:

    • The trade matching rate versus the CSV

    • Overall performance over at least 5 years

Project validation criteria:
The project will be considered successfully completed if:

  • The EA reproduces at least 90% of the trades from the CSV during backtesting

  • The code is functional and usable

  • The strategy logic is clear and properly documented

  • The strategy is profitable on XAUUSD

Detailed report required, explaining:

  • The full project workflow

  • The reasoning and analytical process

  • The research and analysis tools used

  • The technical implementation


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1000 - 2000 USD