[3Win5] Poster session 3

[3Win5-70] Price Sentiment Index with Segmented Information of Consumers and Businesses

〇Masahiro Suzuki^1,2, Hiroki Sakaji³ (1.The University of Tokyo, 2.Nikko Asset Management Co., Ltd., 3.Hokkaido University)

Keywords:Price Index, Large Language Model, Text Mining, Economy Watchers Survey

We develop price sentiment indices (PSI) to analyze price trends from both consumer and corporate perspectives. We extract price-related comments from the Economy Watchers Survey and classify their price direction using pre-trained language models including large language models (LLMs). We show that combining FinBERT and LLM can classify the direction of prices more efficiently and more accurately. We then develop detailed PSIs from the perspectives of consumer and business, as well as goods and services, by categorizing comments based on the domain and the respondent's industry. The PSIs show higher correlations with existing indices compared to previous studies. Notably, the PSIs for consumers exhibit even stronger correlations.