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News sentiment and stock return: Evidence from managers’ news coverages

News sentiment and stock return: Evidence from managers’ news coverages
News sentiment and stock return: Evidence from managers’ news coverages

In this paper, we construct a monthly news-based manager sentiment (S M) based on the tone of managers’ news reports. Statistically, S M has excellent predictability for the subsequent month's return in both in- and out-of-sample periods. we find that S M contains additional information to forecast stock returns compared to popular economic predictors. After analysing the prediction performance at different sentiment levels, it is found that the prediction power of S M is far better in the high sentiment period than in the low sentiment period. In terms of investing, S M also generates considerable economic value for investors who use forecasting information to optimise their stock portfolios.

Chinese stock market, Forecasting, News sentiment, Return predictability
1544-6123
102959
Xu, Yongan
d555b693-6ad8-4140-9eb5-a7a58b966324
Liang, Chao
156910f6-c89e-473e-a7d2-0f1065e5f01c
Li, Yan
381d8970-4e2e-4a37-9315-2962a25bb46a
Huynh, Toan L.d.
5ce01bb6-0184-49cc-8f34-aae3a1169e47
Xu, Yongan
d555b693-6ad8-4140-9eb5-a7a58b966324
Liang, Chao
156910f6-c89e-473e-a7d2-0f1065e5f01c
Li, Yan
381d8970-4e2e-4a37-9315-2962a25bb46a
Huynh, Toan L.d.
5ce01bb6-0184-49cc-8f34-aae3a1169e47

Xu, Yongan, Liang, Chao, Li, Yan and Huynh, Toan L.d. (2022) News sentiment and stock return: Evidence from managers’ news coverages. Finance Research Letters, 48, 102959, [102959]. (doi:10.1016/j.frl.2022.102959).

Record type: Article

Abstract

In this paper, we construct a monthly news-based manager sentiment (S M) based on the tone of managers’ news reports. Statistically, S M has excellent predictability for the subsequent month's return in both in- and out-of-sample periods. we find that S M contains additional information to forecast stock returns compared to popular economic predictors. After analysing the prediction performance at different sentiment levels, it is found that the prediction power of S M is far better in the high sentiment period than in the low sentiment period. In terms of investing, S M also generates considerable economic value for investors who use forecasting information to optimise their stock portfolios.

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Accepted/In Press date: 6 May 2022
e-pub ahead of print date: 7 May 2022
Published date: August 2022
Additional Information: Publisher Copyright: © 2022
Keywords: Chinese stock market, Forecasting, News sentiment, Return predictability

Identifiers

Local EPrints ID: 468350
URI: http://eprints.soton.ac.uk/id/eprint/468350
ISSN: 1544-6123
PURE UUID: aa62c0d1-ba1f-496a-b718-ab24616ca983
ORCID for Toan L.d. Huynh: ORCID iD orcid.org/0000-0002-6653-7447

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Date deposited: 10 Aug 2022 18:18
Last modified: 11 May 2024 04:01

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Contributors

Author: Yongan Xu
Author: Chao Liang
Author: Yan Li
Author: Toan L.d. Huynh ORCID iD

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