Logistics forum based prediction on stock index using intelligent data analysis and processing of online web posts

Autor: Wanyun Cheng, Na Sun, Jinghua Zhao
Rok vydání: 2019
Předmět:
Zdroj: Journal of Ambient Intelligence and Humanized Computing. 11:3575-3584
ISSN: 1868-5145
1868-5137
DOI: 10.1007/s12652-019-01520-x
Popis: This paper focuses on the e-commerce contents of logistics forum. We construct four logistics forums metrics on the degree of busyness and emotional states of the logistics staffs based through hypertext analysis techniques. By choosing a set of individual stocks from e-commerce sector and establishing e-commerce stock index, we examine the empirical evidence of the predictability and degree of influence of e-commerce logistics forum on e-commerce stock index. We find that emotion index and size of web posts may help predict ratio of earnings whereas emotion index, web post index, and disagreement index may help predict exchange volumes. Meanwhile, logistics forum metrics have short term or mid-term influence on e-commerce stock index, ratio of earnings, volatility, and trading volume whereas the influence of emotion index could last more than 40 weeks. Our results help people to understand the interrelationship between the forum contents of logistics social network and stock market activities and provide important decision advice for investors.
Databáze: OpenAIRE
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