supporting better risk management when a theme cools. Unlike static index methodologies or single-dimension factor approaches such as momentum, quality, or sentiment, Thesis combines thematic index expertise, deep-learning-driven risk scores, and disciplined rules-based methodology design to create a more adaptive, risk-aware approach to thematic rotation