Quantifying Trade Policy Volatility: An AI-driven Sentiment Index Approach to Reciprocal Tariffs and Market Resilience in the Indian Textile Industry

This study develops a novel India-specific media-based Reciprocal Tariff Sentiment Index to examine the evolution of trade policy uncertainty (TPU) and its association with the Indian textile sector during the US reciprocal tariff episodes between September 2024 and September 2025. The sentiment index is constructed using newspaper articles and validated against the US TPU index. An event-study framework is employed to examine the stock price responses of major textile firms listed on the National Stock Exchange to key tariff-related announcements, while a regression analysis investigates the contemporaneous association between TPU and India’s textile exports to the United States. The findings indicate that major tariff-related announcements were accompanied by significant abnormal stock returns around several policy events. The regression results further suggest that higher TPU is associated with weaker month-on-month growth in India’s textile exports to the United States. The regression here is not used to assess any causal relation; rather, it is a description regarding the nature of the effect of TPU pertaining to US reciprocal tariffs on the monthly momentum of textile exports. Overall, the evidence indicates that reciprocal tariff-related uncertainty coincided with changes in both financial market performance and export activity, highlighting the importance of predictable trade policies and clear policy communication in reducing uncertainty for export-oriented industries.

JEL Codes : C55, F13, F14, G12, G14, G17