Author: Deng, Jianmin Dave
Title: Same firm, same news, different reaction empirical study on China A+H shares
Advisors: Wei, Steven (AF)
Degree: D.B.A.
Year: 2019
Subject: Stocks -- Prices
Investment analysis
Stock exchanges -- China -- Hong Kong
Stock exchanges -- China
Hong Kong Polytechnic University -- Dissertations
Department: Faculty of Business
Pages: 71 pages
Language: English
Abstract: This paper studies the daily returns of China A+H shares cross-listed and traded in the China stock markets (referred to as A shares) and the Hong Kong stock market (referred to as H shares) and finds that the stock price fluctuations of A+H shares have obvious differences for the same news on the same trading day in both markets. An algorithm based on big data mining and AI techniques is used to analyze the relationship between more than 110,000 news items related to the stock prices of A+H shares from 2014 to 2016. The publication of a news item related to a cross-listed firm results in a significantly different impact on the daily returns for the same company between the two markets. I further analyze the news sentiment and document that bad news is positively correlated with the difference of the daily return, while good news results in no significant difference. Furthermore, the launch of the cross-boundary investment channel, "Shanghai-Hong Kong Stock Connect Scheme" in November 2014, has actually not reduced the gap between the two markets. This empirical study take big data logic and use AI technology as new attempt to analyze the sample, and adds a new dimension to the line of research on the A+H stock price return based on news information and opens the door for future studies.
Rights: All rights reserved
Access: restricted access

Files in This Item:
File Description SizeFormat 
5671.pdfFor All Users (off-campus access for PolyU Staff & Students only)774.82 kBAdobe PDFView/Open


Copyright Undertaking

As a bona fide Library user, I declare that:

  1. I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
  2. I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
  3. I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.

By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.

Show full item record

Please use this identifier to cite or link to this item: https://theses.lib.polyu.edu.hk/handle/200/11195