IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i20p5600-d275421.html
   My bibliography  Save this article

Assessing Investor Belief: An Analysis of Trading for Sustainable Growth of Stock Markets

Author

Listed:
  • Yan Han

    (School of Humanities and Social Science, Beijing Institute of Technology, Beijing 100081, China)

  • Xue-Feng Shao

    (Business School, University La Trobe Sydney Campus, Sydney, NSW 2000, Australia)

  • Xin Cui

    (Business School, University of International Business and Economics, Beijing 100029, China)

  • Xiao-Guang Yue

    (Rattanakosin International College of Creative Entrepreneurship, Rajamangala University of Technology Rattanakosin, Nakon Patom 73170, Thailand)

  • Kelvin Joseph Bwalya

    (School of Consumer Intelligence and Information System, University of Johannesburg, APK Campus, Johannesburg 2006, South Africa)

  • Otilia Manta

    (Romanian Academy, Center for Financial and Monetary Research-Victor Slăvescu, 010071 Bucharest, Romania)

Abstract

Investors’ beliefs are the driving force behind the trading of stocks and, hence, sustainable stock returns. Although investors’ beliefs are usually unobservable, this study develops a new approach to estimate investors beliefs. Following well-established rational learning and market microstructure models, it is assumed that informed traders submit market orders according to their beliefs, whereas market makers/uninformed traders make Bayesian inferences about the informed traders’ private signals after observing the total order flows. By fitting intraday transaction data to this model, we can estimate the daily belief uncertainties of informed and uninformed investors; this estimation is performed on S&P 500 stocks. The belief parameters estimated by this approach have incremental explanatory power to bid-ask spreads. The findings show that market makers’ belief uncertainty plays a more important role in determining sustainable stock returns than informed traders’. Implications of these findings include: (a) the larger market maker group is influencing the market trends; (b) this dominant group is making decisions based on diverse types of data; and (c) increased understanding of the diversity of belief parameters may facilitate strategies to enhance sustainable returns, however, stock trading is still significantly influenced by emotive factors worthy of further research.

Suggested Citation

  • Yan Han & Xue-Feng Shao & Xin Cui & Xiao-Guang Yue & Kelvin Joseph Bwalya & Otilia Manta, 2019. "Assessing Investor Belief: An Analysis of Trading for Sustainable Growth of Stock Markets," Sustainability, MDPI, vol. 11(20), pages 1-18, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:20:p:5600-:d:275421
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/20/5600/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/20/5600/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. David Easley & Soeren Hvidkjaer & Maureen O'Hara, 2002. "Is Information Risk a Determinant of Asset Returns?," Journal of Finance, American Finance Association, vol. 57(5), pages 2185-2221, October.
    2. Aydoğan Alti & Paul C. Tetlock, 2014. "Biased Beliefs, Asset Prices, and Investment: A Structural Approach," Journal of Finance, American Finance Association, vol. 69(1), pages 325-361, February.
    3. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    4. Easley, David & de Prado, Marcos Lopez & O'Hara, Maureen, 2016. "Discerning information from trade data," Journal of Financial Economics, Elsevier, vol. 120(2), pages 269-285.
    5. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    6. Andrade, Sandro C. & Chang, Charles & Seasholes, Mark S., 2008. "Trading imbalances, predictable reversals, and cross-stock price pressure," Journal of Financial Economics, Elsevier, vol. 88(2), pages 406-423, May.
    7. Jiang Wang, 1993. "A Model of Intertemporal Asset Prices Under Asymmetric Information," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(2), pages 249-282.
    8. Chung, Kee H. & Elder, John & Kim, Jang-Chul, 2010. "Corporate Governance and Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 265-291, April.
    9. Banerjee, Snehal & Green, Brett, 2015. "Signal or noise? Uncertainty and learning about whether other traders are informed," Journal of Financial Economics, Elsevier, vol. 117(2), pages 398-423.
    10. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2002. "Order imbalance, liquidity, and market returns," Journal of Financial Economics, Elsevier, vol. 65(1), pages 111-130, July.
    11. Huang, Roger D & Stoll, Hans R, 1997. "The Components of the Bid-Ask Spread: A General Approach," The Review of Financial Studies, Society for Financial Studies, vol. 10(4), pages 995-1034.
    12. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    13. F. M. Bandi & J. R. Russell, 2008. "Microstructure Noise, Realized Variance, and Optimal Sampling," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 75(2), pages 339-369.
    14. Richard A. Lambert & Christian Leuz & Robert E. Verrecchia, 2011. "Information Asymmetry, Information Precision, and the Cost of Capital," Review of Finance, European Finance Association, vol. 16(1), pages 1-29.
    15. Evan W. Anderson & Eric Ghysels & Jennifer L. Juergens, 2005. "Do Heterogeneous Beliefs Matter for Asset Pricing?," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 875-924.
    16. Hörner, Johannes & Lovo, Stefano & Tomala, Tristan, 2018. "Belief-free price formation," Journal of Financial Economics, Elsevier, vol. 127(2), pages 342-365.
    17. George, Thomas J & Kaul, Gautam & Nimalendran, M, 1991. "Estimation of the Bid-Ask Spread and Its Components: A New Approach," The Review of Financial Studies, Society for Financial Studies, vol. 4(4), pages 623-656.
    18. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    19. David Easley & Maureen O'hara, 2004. "Information and the Cost of Capital," Journal of Finance, American Finance Association, vol. 59(4), pages 1553-1583, August.
    20. Ekkehart Boehmer & Eric K. Kelley, 2009. "Institutional Investors and the Informational Efficiency of Prices," The Review of Financial Studies, Society for Financial Studies, vol. 22(9), pages 3563-3594, September.
    21. Glosten, Lawrence R. & Harris, Lawrence E., 1988. "Estimating the components of the bid/ask spread," Journal of Financial Economics, Elsevier, vol. 21(1), pages 123-142, May.
    22. Bessembinder, Hendrik, 2003. "Issues in assessing trade execution costs," Journal of Financial Markets, Elsevier, vol. 6(3), pages 233-257, May.
    23. McInish, Thomas H & Wood, Robert A, 1992. "An Analysis of Intraday Patterns in Bid/Ask Spreads for NYSE Stocks," Journal of Finance, American Finance Association, vol. 47(2), pages 753-764, June.
    24. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    25. Lin, Ji-Chai & Sanger, Gary C & Booth, G Geoffrey, 1995. "Trade Size and Components of the Bid-Ask Spread," The Review of Financial Studies, Society for Financial Studies, vol. 8(4), pages 1153-1183.
    26. Chordia, Tarun & Subrahmanyam, Avanidhar, 2004. "Order imbalance and individual stock returns: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 72(3), pages 485-518, June.
    27. George Tannous & Juan Wang & Craig Wilson, 2013. "The Intraday Pattern of Information Asymmetry, Spread, and Depth: Evidence from the NYSE," International Review of Finance, International Review of Finance Ltd., vol. 13(2), pages 215-240, June.
    28. Brennan, Michael J. & Chordia, Tarun & Subrahmanyam, Avanidhar & Tong, Qing, 2012. "Sell-order liquidity and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 105(3), pages 523-541.
    29. Snehal Banerjee, 2011. "Learning from Prices and the Dispersion in Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 24(9), pages 3025-3068.
    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. Jingxuan Liu & Ping Qiao & Jian Ding & Luke Hankinson & Elodie H. Harriman & Edward M. Schiller & Ieva Ramanauskaite & Haowei Zhang, 2020. "Will the Aviation Industry Have a Bright Future after the COVID-19 Outbreak? Evidence from Chinese Airport Shipping Sector," JRFM, MDPI, vol. 13(11), pages 1-14, November.
    2. Xue-Feng Shao & Kostas Gouliamos & Ben Nan-Feng Luo & Shigeyuki Hamori & Stephen Satchell & Xiao-Guang Yue & Jane Qiu, 2020. "Diversification and Desynchronicity: An Organizational Portfolio Perspective on Corporate Risk Reduction," Risks, MDPI, vol. 8(2), pages 1-16, May.
    3. Shilu Sun & Tiantian Li & Hong Ma & Rita Yi Man Li & Kostas Gouliamos & Jianming Zheng & Yan Han & Otilia Manta & Ubaldo Comite & Teresa Barros & Nelson Duarte & Xiao-Guang Yue, 2020. "Does Employee Quality Affect Corporate Social Responsibility? Evidence from China," Sustainability, MDPI, vol. 12(7), pages 1-19, March.
    4. Otilia Manta & Kostas Gouliamos & Jie Kong & Zhou Li & Nguyen Minh Ha & Rajendra Prasad Mohanty & Hongmei Yang & Ruihui Pu & Xiao-Guang Yue, 2020. "The Architecture of Financial Networks and Models of Financial Instruments According to the “Just Transition Mechanism” at the European Level," JRFM, MDPI, vol. 13(10), pages 1-24, October.
    5. Otilia MANTA, 2020. "The State Aid Instrument For Sustaining Competitiveness In The Context Of Current Crises," Contemporary Economy Journal, Constantin Brancoveanu University, vol. 5(4), pages 54-68.

    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. Jagjeev Dosanjh, 2017. "Exchange Initiatives and Market Efficiency: Evidence from the Australian Securities Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2017.
    2. repec:uts:finphd:34 is not listed on IDEAS
    3. Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
    4. Lamoureux, Christopher G. & Wang, Qin, 2015. "Measuring private information in a specialist market," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 92-119.
    5. Ledenyov, Dimitri O. & Ledenyov, Viktor O., 2015. "Wave function method to forecast foreign currencies exchange rates at ultra high frequency electronic trading in foreign currencies exchange markets," MPRA Paper 67470, University Library of Munich, Germany.
    6. Bardong, Florian & Bartram, Söhnke M. & Yadav, Pradeep K., 2005. "Informed Trading, Information Asymmetry and Pricing of Information Risk: Empirical Evidence from the NYSE," MPRA Paper 13586, University Library of Munich, Germany, revised 10 Oct 2008.
    7. Chang, Sanders S. & Wang, F. Albert, 2015. "Adverse selection and the presence of informed trading," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 19-33.
    8. Chung, Dennis & Hrazdil, Karel, 2010. "Liquidity and market efficiency: A large sample study," Journal of Banking & Finance, Elsevier, vol. 34(10), pages 2346-2357, October.
    9. Odders-White, Elizabeth R. & Ready, Mark J., 2008. "The probability and magnitude of information events," Journal of Financial Economics, Elsevier, vol. 87(1), pages 227-248, January.
    10. Pascual, Roberto & Escribano, Álvaro & Tapia, Mikel, 2000. "Adverse selection costs, trading activity and liquidity in the NYSE: an empirical analysis in a dynamic context," UC3M Working papers. Economics 7276, Universidad Carlos III de Madrid. Departamento de Economía.
    11. Cenesizoglu, Tolga & Grass, Gunnar, 2018. "Bid- and ask-side liquidity in the NYSE limit order book," Journal of Financial Markets, Elsevier, vol. 38(C), pages 14-38.
    12. Jinliang Li & Chunchi Wu, 2006. "Daily Return Volatility, Bid-Ask Spreads, and Information Flow: Analyzing the Information Content of Volume," The Journal of Business, University of Chicago Press, vol. 79(5), pages 2697-2740, September.
    13. Sadka, Ronnie, 2006. "Momentum and post-earnings-announcement drift anomalies: The role of liquidity risk," Journal of Financial Economics, Elsevier, vol. 80(2), pages 309-349, May.
    14. Ivanov, Stoyu I., 2016. "Analysis of ETF bid-ask spread components," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 249-259.
    15. Rubin, Amir, 2007. "Ownership level, ownership concentration and liquidity," Journal of Financial Markets, Elsevier, vol. 10(3), pages 219-248, August.
    16. Sun, Yuxin & Ibikunle, Gbenga, 2017. "Informed trading and the price impact of block trades: A high frequency trading analysis," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 114-129.
    17. Kim, Sukwon Thomas & Stoll, Hans R., 2014. "Are trading imbalances indicative of private information?," Journal of Financial Markets, Elsevier, vol. 20(C), pages 151-174.
    18. Vinay Patel, 2015. "Price Discovery in US and Australian Stock and Options Markets," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 27, July-Dece.
    19. Peress, Joel & Schmidt, Daniel, 2021. "Noise traders incarnate: Describing a realistic noise trading process," Journal of Financial Markets, Elsevier, vol. 54(C).
    20. Valeria Martinez & Yiuman Tse & Jullavut Kittiakarasakun, 2013. "Volatility, trade size, and order imbalance in China and Japan exchange traded funds," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 37(2), pages 293-307, April.
    21. Araújo, Gustavo Silva & Barbedo, Claudio Henrique da S. & Vicente, José Valentim M., 2014. "The adverse selection cost component of the spread of Brazilian stocks," Emerging Markets Review, Elsevier, vol. 21(C), pages 21-41.

    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:gam:jsusta:v:11:y:2019:i:20:p:5600-:d:275421. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.