IDEAS home Printed from https://ideas.repec.org/a/gei/journl/v4y2017i2p237-247.html
   My bibliography  Save this article

A Principal Component Approach to Measuring Investor Sentiment in Hong Kong

Author

Listed:
  • Terence Tai-Leung Chong, Bingqing Cao, Wing Keung Wong

    (The Chinese University of Hong Kong, Hong Kong)

Abstract

In light of the increasing integration between China and Hong Kong, this paper develops a new market sentiment index for the Hong Kong stock market, one of the largest stock market in the world. The components of the sentiment measure includes the turnover ratio, short-selling volume, money flow, HIBOR and return of the U.S. and Japanese markets. We also include the Shanghai and Shenzhen Composite index in our measure to capture the influence of Chinese markets on the Hong Kong market. A threshold regression model using the sentiment index as a threshold variable is estimated to capture the state of the Hong Kong stock market. The result of \citeA{hansen2000sample} likelihood ratio test divides Hong Kong's stock market into three regimes. It is shown that when our sentiment index is above (below) the upper (lower) threshold, the HSI generally moves upward (downward). We also show that the trading rule which shorts (longs) the HSI or S\&P/HKEx LargeCapIndex when the sentiment index is above (below) the upper threshold value can beat the buy-and-hold strategy.

Suggested Citation

  • Terence Tai-Leung Chong, Bingqing Cao, Wing Keung Wong, 2017. "A Principal Component Approach to Measuring Investor Sentiment in Hong Kong," Journal of Management Sciences, Geist Science, Iqra University, Faculty of Business Administration, vol. 4(2), pages 237-247, October.
    • Handle: RePEc:gei:journl:v:4:y:2017:i:2:p:237-247
    as

    Download full text from publisher

    File URL: http://geistscience.com/JMS/Issue2-17/Article4/JMS1704206.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Chong, Terence Tai-Leung & Lam, Tau-Hing & Yan, Isabel Kit-Ming, 2012. "Is the Chinese stock market really inefficient?," China Economic Review, Elsevier, vol. 23(1), pages 122-137.
    2. Lunde A. & Timmermann A., 2004. "Duration Dependence in Stock Prices: An Analysis of Bull and Bear Markets," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 253-273, July.
    3. Baker, Malcolm & Stein, Jeremy C., 2004. "Market liquidity as a sentiment indicator," Journal of Financial Markets, Elsevier, vol. 7(3), pages 271-299, June.
    4. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, vol. 78(2), pages 405-440, March.
    5. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    6. Schmeling, Maik, 2009. "Investor sentiment and stock returns: Some international evidence," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 394-408, June.
    7. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    8. Bruce E. Hansen, 2000. "Sample Splitting and Threshold Estimation," Econometrica, Econometric Society, vol. 68(3), pages 575-604, May.
    9. Lee, Charles M C & Shleifer, Andrei & Thaler, Richard H, 1991. "Investor Sentiment and the Closed-End Fund Puzzle," Journal of Finance, American Finance Association, vol. 46(1), pages 75-109, March.
    10. Haiqiang Chen & Terence Tai Leung Chong & Yingni She, 2014. "A principal component approach to measuring investor sentiment in China," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 573-579, April.
    11. Changyun Wang, 2001. "Investor Sentiment and Return Predictability in Agricultural Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(10), pages 929-952, October.
    12. Hoang, Thi-Hong-Van & Wong, Wing-Keung & Zhu, Zhenzhen, 2015. "Is gold different for risk-averse and risk-seeking investors? An empirical analysis of the Shanghai Gold Exchange," Economic Modelling, Elsevier, vol. 50(C), pages 200-211.
    13. Guo, Xu & Wong, Wing-Keung, 2016. "Multivariate Stochastic Dominance for Risk Averters and Risk Seekers," MPRA Paper 70637, University Library of Munich, Germany.
    14. Frank J. Fabozzi & Chun-Yip Fung & Kin Lam & Wing-Keung Wong, 2013. "Market overreaction and underreaction: tests of the directional and magnitude effects," Applied Financial Economics, Taylor & Francis Journals, vol. 23(18), pages 1469-1482, September.
    15. Lee, Keun Yeong, 2006. "The contemporaneous interactions between the U.S., Japan, and Hong Kong stock markets," Economics Letters, Elsevier, vol. 90(1), pages 21-27, January.
    16. Guo, Xu & Wong, Wing-Keung & Zhu, Lixing, 2016. "Almost stochastic dominance for risk averters and risk seeker," Finance Research Letters, Elsevier, vol. 19(C), pages 15-21.
    17. Ephraim Clark & Zhuo Qiao & Wing-Keung Wong, 2016. "Theories Of Risk: Testing Investor Behavior On The Taiwan Stock And Stock Index Futures Markets," Economic Inquiry, Western Economic Association International, vol. 54(2), pages 907-924, April.
    18. Egozcue, Martín & García, Luis Fuentes & Wong, Wing-Keung & Zitikis, Ricardas, 2011. "Do investors like to diversify? A study of Markowitz preferences," European Journal of Operational Research, Elsevier, vol. 215(1), pages 188-193, November.
    19. Adrian R. Pagan & Kirill A. Sossounov, 2003. "A simple framework for analysing bull and bear markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 23-46.
    20. Haiqiang Chen & Terence Tai-Leung Chong & Xin Duan, 2010. "A principal-component approach to measuring investor sentiment," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 339-347.
    21. Neal, Robert & Wheatley, Simon M., 1998. "Do Measures of Investor Sentiment Predict Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(4), pages 523-547, December.
    22. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    23. Fong, Wai Mun & Lean, Hooi Hooi & Wong, Wing Keung, 2008. "Stochastic dominance and behavior towards risk: The market for Internet stocks," Journal of Economic Behavior & Organization, Elsevier, vol. 68(1), pages 194-208, October.
    24. Lam, Kin & Liu, Taisheng & Wong, Wing-Keung, 2010. "A pseudo-Bayesian model in financial decision making with implications to market volatility, under- and overreaction," European Journal of Operational Research, Elsevier, vol. 203(1), pages 166-175, May.
    25. Qiao, Zhuo & Chiang, Thomas C. & Wong, Wing-Keung, 2008. "Long-run equilibrium, short-term adjustment, and spillover effects across Chinese segmented stock markets and the Hong Kong stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(5), pages 425-437, December.
    26. Zhou, Xiangyi & Zhang, Weijin & Zhang, Jie, 2012. "Volatility spillovers between the Chinese and world equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 247-270.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Nguyen Huu Hau & Tran Trung Tinh & Hoa Anh Tuong & Wing-Keung Wong, 2020. "Review of Matrix Theory with Applications in Education and Decision Sciences," Advances in Decision Sciences, Asia University, Taiwan, vol. 24(1), pages 28-69, March.
    2. Baochen Yang & Yifang Liu & Yunpeng Su, 2023. "Earnings communication conferences and post‐earnings‐announcement drift: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(2), pages 2145-2185, June.
    3. Pan, Wei-Fong, 2018. "Evidence of Investor Sentiment Contagion across Asset Markets," MPRA Paper 88561, University Library of Munich, Germany.
    4. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections," Tinbergen Institute Discussion Papers 18-024/III, Tinbergen Institute.
    5. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," JRFM, MDPI, vol. 11(1), pages 1-29, March.
    6. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, And Big Data: Connections," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 36-94, December.
    7. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(1), pages 1-29, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muhammad Zia Ur Rehman & Zain ul Abidin & Faisal Rizwan & Zaheer Abbas & Sajjad Ahmad Baig, 2017. "How investor sentiments spillover from developed countries to developing countries?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1309096-130, January.
    2. Haiqiang Chen & Terence Tai Leung Chong & Yingni She, 2014. "A principal component approach to measuring investor sentiment in China," Quantitative Finance, Taylor & Francis Journals, vol. 14(4), pages 573-579, April.
    3. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2019. "Firm-specific investor sentiment and daily stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    4. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2013. "Investor sentiment effect in stock markets: Stock characteristics or country-specific factors?," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 572-591.
    5. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, and Big Data: Connections," Tinbergen Institute Discussion Papers 18-024/III, Tinbergen Institute.
    6. Hou, Yang & Meng, Jiayin, 2018. "The momentum effect in the Chinese market and its relationship with the simultaneous and the lagged investor sentiment," MPRA Paper 94838, University Library of Munich, Germany.
    7. Liang, Chao & Xu, Yongan & Wang, Jianqiong & Yang, Mo, 2022. "Whether dimensionality reduction techniques can improve the ability of sentiment proxies to predict stock market returns," International Review of Financial Analysis, Elsevier, vol. 82(C).
    8. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," JRFM, MDPI, vol. 11(1), pages 1-29, March.
    9. Aissia, Dorsaf Ben, 2016. "Home and foreign investor sentiment and the stock returns," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 71-77.
    10. Yang, Yan & Copeland, Laurence, 2014. "The Effects of Sentiment on Market Return and Volatility and The Cross-Sectional Risk Premium of Sentiment-affected Volatility," Cardiff Economics Working Papers E2014/12, Cardiff University, Cardiff Business School, Economics Section.
    11. Yiannis Karavias & Stella Spilioti & Elias Tzavalis, 2021. "Investor sentiment effects on share price deviations from their intrinsic values based on accounting fundamentals," Review of Quantitative Finance and Accounting, Springer, vol. 56(4), pages 1593-1621, May.
    12. Finter, Philipp & Niessen-Ruenzi, Alexandra & Ruenzi, Stefan, 2010. "The impact of investor sentiment on the German stock market," CFR Working Papers 10-03, University of Cologne, Centre for Financial Research (CFR).
    13. Wang, Wenzhao & Su, Chen & Duxbury, Darren, 2022. "The conditional impact of investor sentiment in global stock markets: A two-channel examination," Journal of Banking & Finance, Elsevier, vol. 138(C).
    14. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2014. "Is cognitive bias really present in analyst forecasts? The role of investor sentiment," International Business Review, Elsevier, vol. 23(4), pages 824-837.
    15. Han, Xing & Li, Youwei, 2017. "Can investor sentiment be a momentum time-series predictor? Evidence from China," Journal of Empirical Finance, Elsevier, vol. 42(C), pages 212-239.
    16. Kim-Hung Pho & Thi Diem-Chinh Ho & Tuan-Kiet Tran & Wing-Keung Wong, 2019. "Moment Generating Function, Expectation And Variance Of Ubiquitous Distributions With Applications In Decision Sciences: A Review," Advances in Decision Sciences, Asia University, Taiwan, vol. 23(2), pages 65-150, June.
    17. Ung, Sze Nie & Gebka, Bartosz & Anderson, Robert D.J., 2023. "Is sentiment the solution to the risk–return puzzle? A (cautionary) note," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    18. Yuan Li, 2022. "Mood Beta, Sentiment and Stock Returns in China," SAGE Open, , vol. 12(1), pages 21582440221, February.
    19. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 11(1), pages 1-29, March.
    20. Chia-Lin Chang & Michael McAleer & Wing-Keung Wong, 2018. "Decision Sciences, Economics, Finance, Business, Computing, And Big Data: Connections," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 36-94, December.

    More about this item

    Keywords

    Principal component analysis; market sentiment; CSI 300; threshold model;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gei:journl:v:4:y:2017:i:2:p:237-247. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Imtiaz ARIF (email available below). General contact details of provider: https://geistscience.com/JMS/index.php .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.