fts

–@STCGoal The FTS methodology combines fractal geometry, technical indicators, and AI to identify profitable trading opportunities by analyzing five dimensions: Fractal, Momentum, Acceleration/Deceleration, Zone, and Balance Lines.

Goal: To develop a comprehensive understanding of the FTS methodology and provide guidance on the necessary steps to prepare data for bot and recognition learning using an appropriate model.

Objectives:

1. Understand the FTS Methodology:
   • Review the five dimensions of the FTS methodology: Fractal, Momentum, Acceleration/Deceleration, Zone, and Balance Lines.
   • Comprehend the principles and concepts behind each dimension.
2. Data Preparation for Bot and Recognition Learning:
   • Identify the relevant features to extract from market data for each dimension.
   • Apply appropriate feature engineering techniques to enhance data quality and predictive power.
   • Split the data into training and testing sets for model evaluation.
3. Model Selection and Training:
   • Explore different machine learning models suitable for the FTS methodology.
   • Train and evaluate models using the prepared data, optimizing parameters for best performance.
4. Deployment and Evaluation:
   • Deploy the trained model in a bot or recognition system for real-time market analysis.
   • Monitor and evaluate the performance of the system, making adjustments as needed.

Expected Outcomes:

• A thorough understanding of the FTS methodology and its application in trading.
• A well-prepared dataset for bot and recognition learning.
• A trained and optimized model that effectively captures the dynamics of the FTS methodology.
• A deployed system that leverages the FTS methodology for profitable trading opportunities.

SEE: Wiki