feat: Add CTH/EVEI module for CPI event analysis

[AlejoMalia]

The Comprehensive Eventual Valuation Structure (EVEI) and Tetrasociohistorical Context (CTH) theoretical framework offers key benefits by integrating a deep contextual analysis with Kalshi's event-based prediction markets. This innovative system is designed to systematically quantify events, combining socio-historical, political, and economic factors to generate more precise and robust predictions.

I am currently seeking projects to demonstrate the value of this framework, and I propose this enhancement for Kalshi with the goal of optimizing its predictions. By bringing them closer to reality through an enriched analysis, this system overcomes the limitations of estimations based on insufficient data. By incorporating CTH/EVEI, Kalshi can improve the accuracy of its markets, identify arbitrage opportunities, and provide users with more valuable information for their decision-making.

Key Features of the CTH/EVEI Module for Kalshi

• 🔍 CTH Contextual Analysis: Integrates sociohistorical, political, and economic factors for precise event prediction.
• 📊 EVEI Event Quantification: Computes event significance to prioritize high-impact markets.
• ⚖️ Market Consensus Comparison: Identifies prediction-market discrepancies for arbitrage opportunities.
• 📈 Surprise Metrics: Quantifies prediction accuracy against actual outcomes for market efficiency analysis.
• 💾 Robust API Integration & Data Export: Supports Kalshi API with error handling and CSV result export.

Note on the nature of this Pull Request:
—This project is an experimental initiative for scientific and academic research purposes. Its primary objective is to test the CTH/EVEI theoretical framework in a real-world setting, using Kalshi data. The code is designed as a proof of concept to demonstrate the framework's value and is not optimized for production use. I welcome any comments or suggestions regarding the framework's potential or its implementation.