Can Big Data Help Predict Financial Market Dynamics?: Evidence from the Korean Stock Market

2017 ◽  
Author(s):  
Dong-Jin Pyo
2020 ◽  
Vol 49 (4) ◽  
pp. 589-641
Author(s):  
Cheoljun Eom ◽  
Uk Chang ◽  
Byung Jin Kang ◽  
Woo Baik Lee ◽  
Jong Won Park

This study examines the effects of investor attention on momentum in the Korean stock market. The results reveal significant negative momentum profits in stock groups with high investor attention (high turnover stocks), but insignificant results in those with low investor attention (low turnover stocks). Within high turnover stock groups, the winner portfolio has a declining price trend and insignificant performance, while the loser portfolio realizes significant positive performance through a substantial price increase in the future period. The momentum effect is highly dependent on the reversed performance of the loser portfolio. Second, the performance of the large overreaction stock group shows a more significant negative momentum effect compared to the low overreaction stock group, that is, the degree of overreaction significantly affects the momentum effect. Third, negative momentum profits are consistently observed regardless of the market dynamics. Specifically, more substantial and significant negative performance occurs in the transition market, where the market situation reverses between the past and future periods. Fourth, negative momentum profits are consistently identified even after controlling for the impact of common factors and volatility and liquidity into turnover. Our findings are qualitatively different from the characteristics of the traditional momentum effects generally reported in Western countries.


2020 ◽  
Vol 8 (3) ◽  
pp. 83-87
Author(s):  
N. A. Shevchenko ◽  
V. D. Kalinova

The article discusses the relevance of the introduction of digital technologies in the financial sector. Special attention is paid to the evolution of the stock market due to its digitalization. Various options for the practical use of digital technologies in the described area are shown by analyzing big data and identifying significant patterns. The authors ' proposals will improve the efficiency and validity of decision-making in the financial sector.


2020 ◽  
Vol 45 (2) ◽  
pp. 247-280
Author(s):  
Su Jeong Lee ◽  
Seunghwan Kim ◽  
Seunghee Yang

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