The ComplexMarketPredictor is an advanced Expert Advisor (EA) for MetaTrader 5 that is based on precise modeling and prediction of market movements. This system combines advanced mathematical methods inspired by the history of financial mathematics to analyze and forecast cyclical trends and stochastic variations:
- Sine Functions: Detailed modeling of cyclical price movements.
- Fast Fourier Transform (FFT): Examination of frequency components and fractal structures in historical data.
- Sigmoidal Functions: Integration of volatility and nonlinear dynamics.
- Monte Carlo Simulations: Application of statistical methods to simulate random price deviations and determine an expected average value.
The goal of this project is to develop a robust and scientifically grounded model to support precise trading decisions.
- Installed MetaTrader 5.
Once implemented, the EA continuously analyzes market data to make informed trading decisions. The key components of this model include:
- Sine Component: Precise detection and modeling of cyclical price movements to identify recurring patterns.
- Fractal Component (FFT): Analysis of dominant frequencies in historical price series using Fourier transformation.
- Sigmoid Component: Assessment of price volatility based on ATR (Average True Range) to model nonlinear price developments.
- Monte Carlo Component: Simulation of numerous random price developments to produce robust statistical predictions.
- Trading Decision Logic: Algorithmic derivation of buy or sell decisions based on predefined thresholds.
Despite a fully implemented decision logic, the system is currently inactive as no trades are being executed. Potential causes include:
- Suboptimal parameter selection.
- Unmet trading conditions.
This open-source project offers numerous points for scientific and technical improvements. Suggestions for further development include:
- Parameter Optimization: Exploration and implementation of additional models and optimization methods to enhance accuracy.
- Advanced Trading Logic: Development of new trading strategies and integration of advanced risk management techniques.
- Efficiency Enhancements: Improving runtime performance through algorithmic optimizations.
- Comprehensive Error Handling: Identification and consideration of potential error scenarios.
- Integration of New Analytical Tools: Use of machine learning algorithms and advanced statistical methods to improve precision.
- Trade Execution: Addressing existing issues that hinder the execution of trades.
This project is licensed under the MIT License. Detailed information can be found in the attached LICENSE file.
This project was initiated by Mustafa Seyyid Sahin and published as an open-source initiative to further develop automated trading strategies. The goal is to collaboratively work with the community to create innovative solutions and contribute to scientific discussions.