지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
이용수
초록· 키워드
오류제보하기
Together with soaring interest on Big Data, now there are vigorous reports that unearth various social values lying underneath those data from a number of application areas. Among those reports many are using such data as Internet search histories from Google site, social relationships from Facebook, and transactional or locational traces collected from various ubiquitous devices. Many of those researches, however, are conducted based on the data sets that are accumulated over the North American and European areas, which means that direct interpretation and application of social values exhibited by those researches to the other areas like Korea can be a disturbing task.
This research has started from a validation study against Korean environment of the former paper which says an investment strategy that exploits up and down of Google search volume on a carefully selected set of terms shows high market performance. A huge difference between North American and Korean environment can be eye witnessed via the distinction in profit rates that are exhibited by the corresponding set of search terms. Two sets of search terms actually presented low correlation in their profit rates over two financial markets. Even in an experiment which compares the profit rates with two different investment periods with the same set of search terms showed no such meaningful result that outperforms the market average. With all these results, we cautiously conclude that establishing an investment strategy that exploits Internet search volume over a specified word set needs more conscious approach.
This research has started from a validation study against Korean environment of the former paper which says an investment strategy that exploits up and down of Google search volume on a carefully selected set of terms shows high market performance. A huge difference between North American and Korean environment can be eye witnessed via the distinction in profit rates that are exhibited by the corresponding set of search terms. Two sets of search terms actually presented low correlation in their profit rates over two financial markets. Even in an experiment which compares the profit rates with two different investment periods with the same set of search terms showed no such meaningful result that outperforms the market average. With all these results, we cautiously conclude that establishing an investment strategy that exploits Internet search volume over a specified word set needs more conscious approach.
목차
Abstract
1. 서론
2. 관련 연구 및 배경
3. 실험 분석
4. 결론 및 논의 사항
참고문헌
참고문헌 (18)
참고문헌 신청
1. [단행본] - 료스케 / 2012 / 빅 데이터 비즈니스 / 도서출판 더 숲
2. [단행본] - 송민정 / 2012 / 빅 데이터가 만드는 비즈니스 미래지도 / 한스 미디어
3. [단행본] - 윤형중 / 2012 / 이제는 빅 데이터 시대 / e비즈북스
4. [보고서] - 한국정보화진흥원 / 2011 / 신가치창출 엔진, 빅 데이터의 새로운 가능성과 대응 전략
5. [학술지(정기간행물)] - Bollen, J. / 2011 / Twitter mood predicts the stock market / Journal of Computational Science 2 (1) : 1 ~ 8
2. [단행본] - 송민정 / 2012 / 빅 데이터가 만드는 비즈니스 미래지도 / 한스 미디어
3. [단행본] - 윤형중 / 2012 / 이제는 빅 데이터 시대 / e비즈북스
4. [보고서] - 한국정보화진흥원 / 2011 / 신가치창출 엔진, 빅 데이터의 새로운 가능성과 대응 전략
5. [학술지(정기간행물)] - Bollen, J. / 2011 / Twitter mood predicts the stock market / Journal of Computational Science 2 (1) : 1 ~ 8
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