English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 91913/122132 (75%)
Visitors : 25780573      Online Users : 204
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 會計學系 > 期刊論文 >  Item 140.119/121467
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/121467

    Title: The association between stock price volatility and financial news - a sentiment analysis approach
    Authors: Seng, Jia-Lang
    Yang, Hsiao-Fang
    Contributors: 會計系
    Keywords: Sentiment analysis;Empirical study;Data analytics;Financial media;Prototype system;Stock price volatility
    Date: 2017
    Issue Date: 2018-12-22 11:47:42 (UTC+8)
    Abstract: Purpose - The purpose of this study is to develop the dictionary with grammar and multiword structure has to be used in conjunction with sentiment analysis to investigate the relationship between financial news and stock market volatility. Design/methodology/approach - An algorithm has been developed for calculating the sentiment orientation and score of data with added information, and the results of calculation have been integrated to construct an empirical model for calculating stock market volatility. Findings - The experimental results reveal a statistically significant relationship between financial news and stock market volatility. Moreover, positive (negative) news is found to be positively (negatively) correlated with positive stock returns, and the score of added information of the news is positively correlated with stock returns. Model verification and stock market volatility predictions are verified over four time periods (monthly, quarterly, semiannually and annually). The results show that the prediction accuracy of the models approaches 66% and stock market volatility with a particular trend-predicting effect in specific periods by using moving window evaluation. Research limitations/implications - Onlyone news source is usedandthe researchperiod is only twoyears; thus, future studies should incorporate several data sources and usea longer period to conducta more in-depthanalysis. Practical implications - Understanding trends in stock market volatility can decrease risk and increase profit from investment. Therefore, individuals or businesses can feasibly engage in investment activities for profit by understanding volatility trends in capital markets. Originality/value - The ability to exploit textual information could potentially increase the quality of the data. Few scholars have applied sentiment analysis in investigating interdisciplinary topics that cover information management technology, accounting and finance. Furthermore, few studies have provided support for structured and unstructured data. In this paper, the efficiency of providing the algorithm, the model and the trend in stock market volatility has been demonstrated.
    Relation: KYBERNETES,46(8), 1341-1365
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1108/K-11-2016-0307
    DOI: 10.1108/K-11-2016-0307
    Appears in Collections:[會計學系] 期刊論文

    Files in This Item:

    File Description SizeFormat
    K-11-2016-0307.pdf405KbAdobe PDF133View/Open

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback