Computer Science + Data Science & AI
Inflation forecasting with context, foundation models and MCP.
A double Final Degree Project exploring when economic news, institutional communication and external context improve inflation forecasts, and turning that research workflow into a reproducible web platform.
Core takeaway
More context is not automatically better.
Context helps when it is aligned with the target series, available at the right time, and integrated without leakage or noise. Simpler baselines still matter.
Forecasting evidence
Results across Spain CPI, Global CPI and European HICP.
Software platform
From experiment files to an inspectable forecasting system.
Backend
Frontend
PostgreSQL
MongoDB
Docker
MLflow
MCP
Drift analysis
Final documents
Two theses, one integrated project.
Data Science & AI
Forecasting inflation with contextual signals
Model comparison across statistical, deep learning and foundation time-series models, with MCP-driven contextual inputs.
Open PDFComputer Science
Reproducible forecasting experimentation platform
Full-stack web platform with forecasting adapters, experiment tracking, databases, Docker deployment and MCP integration.
Open PDF