Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/316523 
Authors: 
Year of Publication: 
2017
Citation: 
[Journal:] East Asian Economic Review (EAER) [ISSN:] 2508-1667 [Volume:] 21 [Issue:] 2 [Year:] 2017 [Pages:] 147-165
Publisher: 
Korea Institute for International Economic Policy (KIEP), Sejong-si
Abstract: 
This study quantifies the dynamic interrelationship between the KOSPI index return and search query data derived from the Naver DataLab. The empirical estimation using a bivariate GARCH model reveals that negative contemporaneous correlations between the stock return and the search frequency prevail during the sample period. Meanwhile, the search frequency has a negative association with the one-week- ahead stock return but not vice versa. In addition to identifying dynamic correlations, the paper also aims to serve as a test bed in which the existence of profitable trading strategies based on big data is explored. Specifically, the strategy interpreting the heightened investor attention as a negative signal for future returns appears to have been superior to the benchmark strategy in terms of the expected utility over wealth. This paper also demonstrates that the big data-based option trading strategy might be able to beat the market under certain conditions. These results highlight the possibility of big data as a potential source-which has been left largely untapped-for establishing profitable trading strategies as well as developing insights on stock market dynamics.
Subjects: 
Big Data
Dynamic Correlation
NAVER DataLab
Stock Return
KOSPI
JEL: 
G10
G12
G14
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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