文章基本信息

标题：Factor Model based on contents analysis of Stock BBS Postings
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作者：Hirohiko Suwa ; Eiichi Umehara ; Toshizumi Ohta 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2012
卷号：27
期号：6
页码：376-383
DOI：10.1527/tjsai.27.376
出版社：The Japanese Society for Artificial Intelligence
摘要：We aim to develop a new factor of stock BBS postings that is different from our BMB factor. In our previous study, the contents of stock BBS postings are classified into two categories; i.e. the bullish postings and the bearish postings, and our BMB factor is based on these categories. The results of recent study suggest that the contents of stock BBS postings may be represented by employing more than one index. To develop a new factor, we use a morphological analysis and a PCA to analyze the contents of stock BBS postings. As results, we develop a new factor that based on principal component score and it represented the return of stock, and in that they are not correlated with our BMB factor.
关键词：factor model ; Internet BBS ; content of message ; stock return