Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/156402
DC FieldValue
dc.titleIS MARKET SENTIMENT PREDICTIVE OF STOCK RETURNS?
dc.contributor.authorVENETIA WONG WEE TENG
dc.date.accessioned2019-07-05T02:09:03Z
dc.date.available2019-07-05T02:09:03Z
dc.date.issued2019-04-08
dc.identifier.citationVENETIA WONG WEE TENG (2019-04-08). IS MARKET SENTIMENT PREDICTIVE OF STOCK RETURNS?. ScholarBank@NUS Repository.
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/156402
dc.description.abstractThis paper formally studies market sentiment and its performance as a predictor of stock returns in the Singapore context. Market sentiment is determined by applying sentiment analysis to news articles. Sentiment can be decomposed into its constituent variables concerning mood, modality, and subjectivity, among others. I find that market sentiment is a useful predictor of returns, although the extent depends on the sentiment variables incorporated into the model and the predictive model’s implementation, which is subject to the model-selection criteria. Moreover, I draw three key findings from patterns across my various selected models. First, negative sentiment exerts a greater influence on stock returns than positive sentiment. Second, although positive sentiment typically raises returns and negative sentiment typically lowers re- turns, there exists a subjectivity reversal effect where the directions reverse if the sentiment is subjective in nature. Finally, the predictability of stock returns using market sentiment appears non-constant over time. JEL Codes: C58, C80, D84, G14, G17.
dc.subjectSentiment Analysis
dc.subjectStock Returns
dc.subjectFinancial Forecasting
dc.typeThesis
dc.contributor.departmentECONOMICS
dc.contributor.supervisorDENIS TKACHENKO
dc.description.degreeBachelor's
dc.description.degreeconferredBachelor of Social Sciences (Honours)
Appears in Collections:Bachelor's Theses

Show simple item record
Files in This Item:
File Description SizeFormatAccess SettingsVersion 
Venetia Wong Wee Teng AY1819 Sem 2.pdf410.11 kBAdobe PDF

RESTRICTED

NoneLog In

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.