I developed a relative value indicator for the Maasai Dashboard platform. This project aims to provide traders with an effective tool to assess whether an asset is overvalued or undervalued relative to economic benchmarks, using data normalization techniques and advanced statistical analyses :• Designed and implemented a relative value indicator, incorporating data normalization methods to handle different scales and enhance comparison accuracy.• Applied entropy to gauge market volatility and uncertainty, thereby refining the analysis.• Enhanced the MACD (Moving Average Convergence Divergence) by implementing a double MACD configuration, which improved signal filtering and accuracy.• Created a comprehensive strategy by integrating the relative value indicator with the refined MACD and other technical tools.• Identified buy and sell signals through the development of a cohesive strategy based on all integrated indicators.• Performed unit and integration testing to verify the reliability and robustness of the indicator.

• Preprocessed Arabic text data by normalizing and extracting features for advanced analysis.• Developed and implemented co-clustering algorithms using hierarchical clustering techniques to uncover patterns in Arabic text.• Applied biclustering methods to simultaneously cluster documents and terms, enhancing thematic coherence.• Assessed model performance with metrics like silhouette score, and provided insights to refine clustering results.