In:
SAGE Open, SAGE Publications, Vol. 13, No. 1 ( 2023-01), p. 215824402311521-
Abstract:
Using 34 products from China’s commodity futures market, this study examines the impact of social network attention and sentiment on its futures market returns. A machine learning text analysis algorithm was used to construct social network investor sentiment in consultation with three search volume indices. We find that: social network sentiment is a good predictor of commodity futures returns, investor attention has a significant positive impact on returns and absolute returns, and the Baidu index is better at forecasting returns than the Sogou and 360 indices. In addition, we examine how social network sentiment affects returns at different levels. We find that extremely high, market social network sentiments of investors changed the predicted results significantly; thus, the bases of the specified trading strategies of investors were altered. Regulators should therefore incorporate investor sentiment into regulatory targets and enhance retail investor education.
Type of Medium:
Online Resource
ISSN:
2158-2440
,
2158-2440
DOI:
10.1177/21582440231152131
Language:
English
Publisher:
SAGE Publications
Publication Date:
2023
detail.hit.zdb_id:
2628279-3
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