本篇文章使用 Sun 等（2021）基于股吧发帖构建的个股投资者情绪指数，选取沪深 300 股指中包含的十个一级行业指数：300 能源、300 原材料、300工业、300 主要消费、300 可选消费、300 医药卫生、300 金融地产、300 信息技术、300 通信服务、300 公用事业；利用指数成分股及其成分股的投资者情绪指数构建了行业投资者情绪指数。通过行业投资者情绪指数及其行业指数回报的自回归模型，发现公用事业为投资者情绪不敏感行业；并将投资者情绪敏感行业依据其回归系数划分为三个等级：最敏感的为工业、原材料及信息技术；较敏感的为医药卫生、通信服务和金融地产；一般敏感的为主要消费、可选消费及能源。另外，本文对十个行业的指数波动率做统计，发现投资者情绪敏感越敏感的行业波动率倾向于越高；并通过最敏感行业不同方向上的投资者情绪的回归结果发现，看涨情绪能给市场带来显著正向影响，而看跌情绪对市场影响并不显著。本文首次将 A 股市场按照十个一级行业分类，量化每个行业的情绪敏感性进行排序，为构建不同风险特征的投资组合提供了一定参考价值。

This paper develops an industry investor sentiment index for ten first-class industries included by CSI 300 by using Gubasenti, an individual investor sentiment index for the stock market in China. We use the constituents and their weekly Gubasenti of ten industry index: CSI 300 Energy Index, Materials Index, Industrials Index, Consumer Discretionary Index, Consumer Staples Index, Health Care Index, Financials Index, Information Technology Index, Telecommunication Services Index and Utilities Index and construct the industry sentiment index. Through the autoregressive model of the return for each industry index with its industry sentiment as an independent variable, we discover that the Utilities industry isn’t sensitive to investor’s sentiment, while the rest nine industries are sensitive to it in different levels, with Industrials, Materials and Information Technology as the most sensitive industries; Health Care, Telecommunication Services and Financials as the second, Consumer Discretionary, Consumer Staples and Energy as the least sensitive. Thenwe summarize the volatilities of ten industries and find that the more sensitive anindustry are to investor’s sentiment, the more likely the industry owns a highervolatility. Through regression of the three most sensitive industries returns with industry sentiment in different directions as independent variables, it is found that bullish sentiment has a significant positive impact on the market, while bearish sentiment doesn’t have a significant impact on it. For the first time, the A-share market is classified according to ten first-level industries, and the emotional sensitivity of each industry is quantified, which provides a certain reference value for the construction of portfolios with different risk characteristics.