Predicting the Co-movement of Stocks in the Hong Kong Stock Market

Chen Chuxun, Jean H Y LAI*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

Stock co-movement was examined in Finance research but not in the IT research. Previous studies revealed that the co-movement is usually caused by either the determinants of the stocks’ values, habitat movements between stocks, or the change in portfolio composition. Most of the studies used a statistical approach to uncover the co-movement relation between stocks. This paper takes a combination of the statistical approach and the machine learning approach to: (1) prove the existence of stock co-movement; and (2) identify a prediction model that can forecast the stock co-movement. Both supervised and unsupervised methods are used. In this study, the inter-day stock data in the real estate industry were extracted from the Yahoo finance in Hong Kong. After cleaning the data, stocks of the industry were categorized into two groups by its market capitalization. The correlation between the two trading data set is tested. Support Vector Machine (SVM) is used to train the prediction model. The predictive power of the model looks good.

Original languageEnglish
Title of host publicationGenetic and Evolutionary Computing - Proceedings of the 12th International Conference on Genetic and Evolutionary Computing, 2018
EditorsJeng-Shyang Pan, Shih-Pang Tseng, Jerry Chun-Wei Lin, Bixia Sui
PublisherSpringer Verlag
Pages723-734
Number of pages12
ISBN (Print)9789811358401
DOIs
Publication statusPublished - 2019
Event12th International Conference on Genetic and Evolutionary Computing, ICGEC 2018 - Changzhou, China
Duration: 14 Dec 201817 Dec 2018

Publication series

NameAdvances in Intelligent Systems and Computing
Volume834
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference12th International Conference on Genetic and Evolutionary Computing, ICGEC 2018
Country/TerritoryChina
CityChangzhou
Period14/12/1817/12/18

Scopus Subject Areas

  • Control and Systems Engineering
  • Computer Science(all)

User-Defined Keywords

  • K-means clustering
  • Stock Co-movement
  • Support vector machine

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