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Forecasting Power of Sentiment on Stock Return

Pong, King Yin LU and Cao, Yu LU (2015) BUSP70 20151
Department of Business Administration
Abstract
We study the predictability of sentiment on stock return of the Hong Kong market. We measure sentiment by forming composite sentiment indices from several proxies using principal component analysis and the partial least square method. We find that sentiment measures using either method have similar in-sample forecasting power but the one formed by using partial least square method has better out-of-sample predictability on stock return. We do not find any sentiment predictability on the cross-section of stock return.
Popular Abstract
We study the predictability of sentiment on stock return of the Hong Kong market. We measure sentiment by forming composite sentiment indices from several proxies using principal component analysis and the partial least square method. We find that sentiment measures using either method have similar in-sample forecasting power but the one formed by using partial least square method has better out-of-sample predictability on stock return. We do not find any sentiment predictability on the cross-section of stock return.
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author
Pong, King Yin LU and Cao, Yu LU
supervisor
organization
course
BUSP70 20151
year
type
H2 - Master's Degree (Two Years)
subject
keywords
principal component analysis, return, sentiment, partial least square
language
English
id
5468904
date added to LUP
2015-06-08 16:00:25
date last changed
2015-06-08 16:00:25
@misc{5468904,
  abstract     = {We study the predictability of sentiment on stock return of the Hong Kong market. We measure sentiment by forming composite sentiment indices from several proxies using principal component analysis and the partial least square method. We find that sentiment measures using either method have similar in-sample forecasting power but the one formed by using partial least square method has better out-of-sample predictability on stock return. We do not find any sentiment predictability on the cross-section of stock return.},
  author       = {Pong, King Yin and Cao, Yu},
  keyword      = {principal component analysis,return,sentiment,partial least square},
  language     = {eng},
  note         = {Student Paper},
  title        = {Forecasting Power of Sentiment on Stock Return},
  year         = {2015},
}