A Trading Strategy Based on Analysts' Industry Analyses - Evidence from Textual Analyses of Analyst Reports in Chinese Stock Market

Applying a deep-learning method that is efficient in differentiating the order of words, we extract the tone of analysts' industry analyses to measure analyst expertise and aggregate it at industry level as OPNI. Based on OPNI, we successfully construct the industry hedging portfolio that longs...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Emerging markets finance & trade 2023-08, Vol.59 (10), p.3378-3389
Hauptverfasser: Wu, Lunwen, Gao, Di, Su, Wanxuan, Liang, Dawei, Du, Qianqian
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Applying a deep-learning method that is efficient in differentiating the order of words, we extract the tone of analysts' industry analyses to measure analyst expertise and aggregate it at industry level as OPNI. Based on OPNI, we successfully construct the industry hedging portfolio that longs industries with highest OPNI and shorts industries with lowest OPNI, which generates significant and robust abnormal returns. Furthermore, we find that the industry hedging portfolio based on industry-level numerical forecasts cannot generate significant returns. Additionally, in mechanism analyses, we find that the informativeness of analysts' industry analyses is driven by its predictability on industry-level unexpected revenues and earnings. Our findings suggest that industry analyses in analysts' reports contain incremental value about their industry expertise, which is beyond analysts' quantitative forecasts.
ISSN:1540-496X
1558-0938
DOI:10.1080/1540496X.2023.2218968