フリーランスセクション

Developing an EA Trading Advisor via Reverse Engineering

MQL5 エキスパート 売買ロボット/指標のデバッグ ストラテジーの最適化

指定

To develop a fully functional EA trading advisor that replicates the performance of an existing successful trading system. The EA to be created by reverse engineering a 1-year historical track containing all deals and orders, utilizing an "Octopus"-like strategy involving multiple Moving Averages (MAs) and additional indicators for order placement and grid-like order multiplication.

Project Scope

  • Data Analysis: Examine and interpret the provided 1-year trading data to understand the underlying strategy.
  • Strategy Identification: Identify the specific indicators and logic used for trade entry, order multiplication, and grid management.
  • EA Development: Code the identified strategy into a MetaTrader-compatible EA.
  • Backtesting & Optimization: Validate the EA's performance through backtesting, ensuring it mirrors the original strategy's profit and drawdown metrics.

Subtasks

Subtask 1: Identify Trade Entry Points

  • Analyze the historical data to identify patterns and signals preceding each trade entry.
  • Identify the types and configurations of indicators used.
  • Document the criteria for initiating a new trade.
Subtask 2: Understand Order Multiplication Logic
  • Examine the sequence and conditions under which additional orders are placed.
  • Identify the grid parameters, such as distance between orders, maximum number of multiplications, and order sizing rules.

Subtask 3: Develop the EA Code

  • Code the trade entry logic
  • Incorporate risk management features such take-profit, and maximum drawdown limits.

Subtask 4: Backtest and Validate the EA

  • Conduct back testing using the provided 1-year historical data.
  • Compare the EA’s performance metrics (profit, drawdown, number of trades, etc.) with the original track.
  • Optimize parameters if necessary to achieve similar performance outcomes.

On top of budget you will get a working strategy similar to original which has proven 4-years successful track.

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プロジェクト情報

予算
300 - 500 USD