Data mining investigation of co-movements on the Taiwan and China stock markets for future investment portfolio

On June 29, 2010, Taiwan signed an Economic Cooperation Framework Agreement (ECFA) with China as a major step to open markets between Taiwan and China. Thus, the ECFA will contribute by creating a closer relationship between China and Taiwan through economic and market interactions. Co-movements of the world's national financial market indexes are a popular research topic in the finance literature. Some studies examine the co-movements and the benefits of international financial market portfolio diversification/integration and economic performance. Thus, this study investigates the co-movement in the Taiwan and China (Hong Kong) stock markets under the ECFA using a data mining approach, including association rules and clustering analysis. Thirty categories of stock indexes are implemented as decision variables to observe the behavior of stock index associations during the periods of ECFA implementation. Patterns, rules, and clusters of data mining results are discussed for future stock market investment portfolio.

[1]  G. Meric,et al.  Co-movements of sector index returns in the world's major stock markets in bull and bear markets: Portfolio diversification implications , 2008 .

[2]  E. Fama,et al.  Efficient Capital Markets : II , 2007 .

[3]  Changyu Wang,et al.  Relative Strength Strategies in China's Stock Market: 1994-2000 , 2004 .

[4]  Shu-Hsien Liao,et al.  Mining stock category association and cluster on Taiwan stock market , 2008, Expert Syst. Appl..

[5]  R. Rigobón,et al.  No Contagion, Only Interdependence: Measuring Stock Market Comovements , 2002 .

[6]  Colm Kearney,et al.  Is North and Southeast Asia becoming a yen block , 2007 .

[7]  Panos M. Pardalos,et al.  Mining market data: A network approach , 2006, Comput. Oper. Res..

[8]  R. Haugen.  Modern investment theory , 1986 .

[9]  Lu Zheng,et al.  Investor Flows and Stock Market Returns , 2011 .

[10]  Michel Beine,et al.  Liberalisation and stock market co-movement between emerging economies , 2007 .

[11]  Yi-Fan Wang,et al.  A personalized recommender system for the cosmetic business , 2004, Expert Syst. Appl..

[12]  Sunil S. Poshakwale,et al.  The dynamics between stock returns and mutual fund flows: empirical evidence from the Greek market , 2005 .

[13]  Eva Liljeblom,et al.  The benefits from international diversification for Nordic investors , 1997 .

[14]  David Enke,et al.  The use of data mining and neural networks for forecasting stock market returns , 2005, Expert Syst. Appl..

[15]  Jeffrey Edwards,et al.  Evaluating Growth Volatility Susceptibility within Regional Free Trade Agreements , 2011 .

[16]  Michael Graham,et al.  Integration of 22 emerging stock markets: A three-dimensional analysis , 2012 .

[17]  Linlin Niu,et al.  Co-Movements of Shanghai and New York Stock Prices by Time-Varying Regressions , 2011 .

[18]  Roberto Rigobon,et al.  On the Measurement of the International Propagation of Shocks , 1999 .

[19]  Yuanchen Chang,et al.  The pricing of foreign exchange risk around the Asian financial crisis: evidence from Taiwan's stock market , 2002 .

[20]  Barry Devlin,et al.  Data Warehouse: From Architecture to Implementation , 1996 .

[21]  Shu-hsien Liao,et al.  Mining the co-movement between foreign exchange rates and category stock indexes in the Taiwan financial capital market , 2011, Expert Syst. Appl..

[22]  Joseph Kang,et al.  Contrarian and momentum strategies in the China stock market: 1993–2000 , 2002 .

[23]  Se-Hak Chun,et al.  Dynamic adaptive ensemble case-based reasoning: application to stock market prediction , 2005, Expert Syst. Appl..

[24]  Mevlut Ture,et al.  Comparing classification techniques for predicting essential hypertension , 2005, Expert Syst. Appl..

[25]  Rakesh Agrawal,et al.  Parallel Mining of Association Rules , 1996, IEEE Trans. Knowl. Data Eng..

[26]  Bernd Wilfling,et al.  Institutional Investors and Stock Returns Volatility: Empirical Evidence from a Natural Experiment , 2009 .

[27]  M. Úriz,et al.  Validating spongia, an expert system for sponge identification , 1999 .

[28]  Natalie Y. Oh,et al.  Relations between mutual fund flows and stock market returns in Korea , 2007 .

[29]  Wonsik Sul,et al.  The Asian financial crisis and the co-movement of Asian stock markets , 2002 .

[30]  Tomasz Imielinski,et al.  Mining association rules between sets of items in large databases , 1993, SIGMOD Conference.

[31]  R. Rigobón,et al.  No Contagion, Only Interdependence: Measuring Stock Market Co-Movements , 1999 .

[32]  Shu-hsien Liao,et al.  Mining the co-movement in the Taiwan stock funds market , 2011, Expert Syst. Appl..

[33]  Das Amrita,et al.  Mining Association Rules between Sets of Items in Large Databases , 2013 .

[34]  Liang Zhang,et al.  The return to value in Asian stock markets , 2008 .

[35]  Timothy K. Chue.  Time-Varying Risk Preferences and Emerging Market Co-Movements , 2002 .

[36]  Mara Madaleno,et al.  International stock market indices comovements: a new look , 2012 .

[37]  Ioannis N. Kouris,et al.  Using Information Retrieval techniques for supporting data mining , 2005, Data Knowl. Eng..

[38]  David E. Rapach,et al.  In-sample vs. out-of-sample tests of stock return predictability in the context of data mining , 2006 .

[39]  Marianne Sensier,et al.  Co-movements between US and UK stock prices: the role of time-varying conditional correlations , 2009 .

[40]  Michael N. Vrahatis,et al.  The New k-Windows Algorithm for Improving the k-Means Clustering Algorithm , 2002, J. Complex..

[41]  Xinwei Zheng,et al.  Market liquidity risk factor and financial market anomalies: Evidence from the Chinese stock market , 2010 .

[42]  Yan Gao,et al.  What Comprises IPO Initial Returns: Evidence from the Chinese Market , 2010 .

[43]  Guglielmo Maria Caporale,et al.  Testing for Financial Contagion between Developed and Emerging Markets During the 1997 East Asian Crisis , 2005 .

[44]  Jeong‐Bon Kim,et al.  IPO underpricing in China’s new stock markets , 2004 .