Forecasting stock price movements with multiple data sources: Evidence from stock market in China

2020 ◽  
Vol 542 ◽  
pp. 123389 ◽  
Author(s):  
Zhongbao Zhou ◽  
Meng Gao ◽  
Qing Liu ◽  
Helu Xiao
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Data Sources ◽  
Multiple Data Sources ◽  
Multiple Data ◽  
Price Movements ◽  
Stock Price Movements

scholarly journals The Effect of The Match Results on Bali United’s Stock Price Movements

2020 ◽  
Vol 3 (1) ◽  
pp. 26
Author(s):  
Agung Novianto Margarena ◽  
Arian Agung Prasetiyawan
Keyword(s):  
Stock Market ◽  
Stock Prices ◽  
Stock Price ◽  
European Countries ◽  
Football Club ◽  
Study Results ◽  
Price Movements ◽  
Positive Effect ◽  
Stock Price Movements

This study was conducted due to differences in the study results inseveral countries related to the effect of the match results on stockmovements. Dimic et. al (2019) stated the match results effect themovement of stock prices, while Mishra & Smyth (2010) stated thevice versa. Then, Floros (2014) put forward different results throughthe study of four clubs in four European countries. Thus, this studyreexamines the effect of the match results on the stock pricemovement of Bali United. Moreover, Bali United is the first SoutheastAsian football club to be listed on the stock market. This study uses aquantitative method with a sample of 31 Bali United’s matches afterlisted on the stock market. The data were analyzed using simple linearregression with SPSS 21 with either won, drawn or lost match resultsrepresented by goal margins. The stock price movements arerepresented by stock prices after the results of the match. It was foundthat the results of the match had a positive effect on the stockmovement of Bali United

Stock market tweets annotated with emotions

Corpora ◽  
2020 ◽  
Vol 15 (3) ◽  
pp. 343-354
Author(s):  
Fernando J. Vieira da Silva ◽  
Norton T. Roman ◽  
Ariadne M.B.R. Carvalho
Keyword(s):  
Machine Learning ◽  
Stock Market ◽  
Stock Price ◽  
Brazilian Portuguese ◽  
Learning Models ◽  
Stock Trading ◽  
Emotion Identification ◽  
Price Movements ◽  
Machine Learning Models ◽  
Stock Price Movements

As stock trading became a popular topic on Twitter, many researchers have proposed different approaches to make predictions on it, relying on the emotions found in messages. However, detailed studies require a reasonably sized corpus with emotions properly annotated. In this work, we introduce a corpus of tweets in Brazilian Portuguese annotated with emotions. Comprising 4,277 tweets, this is, to the best of our knowledge, the largest annotated corpus available in the stock market domain for this language. Amongst its possible uses, the corpus lends itself to the application of machine learning models for automatic emotion identification, as well as to the study of correlations between emotions and stock price movements.

Why does China's stock market have highly synchronous stock price movements? An information supply perspective

2015 ◽  
Vol 31 (1) ◽  
pp. 68-79 ◽  
Author(s):  
Karen Jingrong Lin ◽  
Khondkar E. Karim ◽  
Clairmont Carter
Keyword(s):  
Stock Market ◽  
Stock Price ◽  
Price Movements ◽  
Stock Price Movements

Individualism, synchronized stock price movements, and stock market volatility

2019 ◽  
Vol 15 (3) ◽  
pp. 371-403
Author(s):  
Feng Zhan
Keyword(s):  
Stock Market ◽  
National Culture ◽  
Stock Price ◽  
Market Volatility ◽  
Investor Behavior ◽  
Stock Market Volatility ◽  
Content Type ◽  
Individualistic Culture ◽  
Price Movements ◽  
Stock Price Movements

PurposeThe purpose of this paper is to examine the impact of national culture on herding behavior across international financial markets.Design/methodology/approachThe relation between national culture and investor behavior, and how it impacts overall market volatility is studied by examining synchronized stock price movements and stock market volatility in 47 countries around the world over the period of January 2003–May 2012.FindingsThe author finds that nations with lower values of individualistic culture are more likely to have a higher number of synchronized stock price movements. Further, the correlation between stock price movements apparently increases stock market volatility. Nations with high individualistic culture have a lower number of synchronized stock price movements and, thus, have lower levels of stock market volatility. The positive relationship between synchronized stock price movements and stock market volatility is stronger for emerging markets during the financial crisis from June 2007 to December 2008.Originality/valueThe empirical results in this paper indicate that a portion of the difference in market level volatility is attributed to the investor bias of different cultures. Investor behavior bias creates excess volatility that drives stock prices away from fundamentals. This impact is strong in nations with lower individualistic culture. The result from this research could also have a wide implication in the investment industry.

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