IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-04703041.html
   My bibliography  Save this paper

When Buffett Meets Bollinger: An Integrated Approach to Fundamental and Technical Analysis

Author

Listed:
  • Zhaobo Zhu

    (Audencia Business School)

  • Licheng Sun

    (Old Dominion University, Strome College of Business)

Abstract

Motivated by the implication of return extrapolation models that a joint consideration of past price changes and firm fundamentals could efficiently identify stock mispricing, we propose an integrated approach that combines fundamental and technical information.This integrated approach generates substantial economic gains, which are comparable to those of strategies double-sorted on characteristics related to high turnover and trading costs and state-of-the-art machine learning strategies in existing studies. The performance net of transaction costs is still attractive. Simple transaction cost mitigation approaches could further enhance the performance of the integrated approach by reducing portfolio turnover. Consistent with behavioral models, limits to arbitrage and information asymmetry play a significant role in explaining the super performance of this integrated approach.

Suggested Citation

  • Zhaobo Zhu & Licheng Sun, 2024. "When Buffett Meets Bollinger: An Integrated Approach to Fundamental and Technical Analysis," Post-Print hal-04703041, HAL.
  • Handle: RePEc:hal:journl:hal-04703041
    Note: View the original document on HAL open archive server: https://hal.science/hal-04703041v1
    as

    Download full text from publisher

    File URL: https://hal.science/hal-04703041v1/document
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Novy-Marx, Robert, 2013. "The other side of value: The gross profitability premium," Journal of Financial Economics, Elsevier, vol. 108(1), pages 1-28.
    2. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
    3. Scruggs, John T., 2007. "Noise trader risk: Evidence from the Siamese twins," Journal of Financial Markets, Elsevier, vol. 10(1), pages 76-105, February.
    4. Avramov, Doron & Kaplanski, Guy & Levy, Haim, 2018. "Talking Numbers: Technical versus fundamental investment recommendations," Journal of Banking & Finance, Elsevier, vol. 92(C), pages 100-114.
    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. Barber, Brad M. & Lee, Yi-Tsung & Liu, Yu-Jane & Odean, Terrance, 2014. "The cross-section of speculator skill: Evidence from day trading," Journal of Financial Markets, Elsevier, vol. 18(C), pages 1-24.
    7. Bernard, Vl & Thomas, Jk, 1989. "Post-Earnings-Announcement Drift - Delayed Price Response Or Risk Premium," Journal of Accounting Research, Wiley Blackwell, vol. 27, pages 1-36.
    8. Zhaobo Zhu & Licheng Sun & Min Chen, 2023. "Fundamental strength and the 52-week high anchoring effect," Review of Quantitative Finance and Accounting, Springer, vol. 60(4), pages 1515-1542, May.
    9. Cheol‐Ho Park & Scott H. Irwin, 2007. "What Do We Know About The Profitability Of Technical Analysis?," Journal of Economic Surveys, Wiley Blackwell, vol. 21(4), pages 786-826, September.
    10. Barberis, Nicholas & Greenwood, Robin & Jin, Lawrence & Shleifer, Andrei, 2015. "X-CAPM: An extrapolative capital asset pricing model," Journal of Financial Economics, Elsevier, vol. 115(1), pages 1-24.
    11. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    12. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    13. Han, Yufeng & Yang, Ke & Zhou, Guofu, 2013. "A New Anomaly: The Cross-Sectional Profitability of Technical Analysis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1433-1461, October.
    14. Barberis, Nicholas & Greenwood, Robin & Jin, Lawrence & Shleifer, Andrei, 2018. "Extrapolation and bubbles," Journal of Financial Economics, Elsevier, vol. 129(2), pages 203-227.
    15. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
    16. Michael J. Cooper & Huseyin Gulen & Michael J. Schill, 2008. "Asset Growth and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 63(4), pages 1609-1651, August.
    17. Chordia, Tarun & Shivakumar, Lakshmanan, 2006. "Earnings and price momentum," Journal of Financial Economics, Elsevier, vol. 80(3), pages 627-656, June.
    18. Brad M. Barber & Terrance Odean, 2001. "Boys will be Boys: Gender, Overconfidence, and Common Stock Investment," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 261-292.
    19. Zhi Da & Qianqiu Liu & Ernst Schaumburg, 2014. "A Closer Look at the Short-Term Return Reversal," Management Science, INFORMS, vol. 60(3), pages 658-674, March.
    20. Easley, David & Kiefer, Nicholas M & O'Hara, Maureen, 1997. "One Day in the Life of a Very Common Stock," The Review of Financial Studies, Society for Financial Studies, vol. 10(3), pages 805-835.
    21. Xuemin (Sterling) Yan & Lingling Zheng, 2017. "Fundamental Analysis and the Cross-Section of Stock Returns: A Data-Mining Approach," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1382-1423.
    22. Zhaobo Zhu & Licheng Sun & Min Chen, 2023. "Fundamental Strength and the 52-Week High Anchoring Effect," Post-Print hal-04086076, HAL.
    23. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    24. Shleifer, Andrei & Vishny, Robert W, 1997. "The Limits of Arbitrage," Journal of Finance, American Finance Association, vol. 52(1), pages 35-55, March.
    25. Beaver, William & McNichols, Maureen & Price, Richard, 2007. "Delisting returns and their effect on accounting-based market anomalies," Journal of Accounting and Economics, Elsevier, vol. 43(2-3), pages 341-368, July.
    26. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
    27. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    28. Piotroski, JD, 2000. "Value investing: The use of historical financial statement information to separate winners from losers," Journal of Accounting Research, Wiley Blackwell, vol. 38, pages 1-41.
    29. Kewei Hou & Chen Xue & Lu Zhang, 2015. "Editor's Choice Digesting Anomalies: An Investment Approach," The Review of Financial Studies, Society for Financial Studies, vol. 28(3), pages 650-705.
    30. Andrew W. Lo & Harry Mamaysky & Jiang Wang, 2000. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Journal of Finance, American Finance Association, vol. 55(4), pages 1705-1765, August.
    31. Zhu, Zhaobo & Sun, Licheng & Yung, Kenneth & Chen, Min, 2020. "Limited investor attention, relative fundamental strength, and the cross-section of stock returns," The British Accounting Review, Elsevier, vol. 52(4).
    32. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    33. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    34. Pontiff, Jeffrey, 2006. "Costly arbitrage and the myth of idiosyncratic risk," Journal of Accounting and Economics, Elsevier, vol. 42(1-2), pages 35-52, October.
    35. Robert F. Stambaugh & Jianfeng Yu & Yu Yuan, 2015. "Arbitrage Asymmetry and the Idiosyncratic Volatility Puzzle," Journal of Finance, American Finance Association, vol. 70(5), pages 1903-1948, October.
    36. Zhu, Zhaobo & Sun, Licheng & Chen, Min, 2019. "Fundamental strength and short-term return reversal," Journal of Empirical Finance, Elsevier, vol. 52(C), pages 22-39.
    37. Clifford S. Asness & Tobias J. Moskowitz & Lasse Heje Pedersen, 2013. "Value and Momentum Everywhere," Journal of Finance, American Finance Association, vol. 68(3), pages 929-985, June.
    38. Joseph D. Piotroski & Eric C. So, 2012. "Identifying Expectation Errors in Value/Glamour Strategies: A Fundamental Analysis Approach," The Review of Financial Studies, Society for Financial Studies, vol. 25(9), pages 2841-2875.
    39. Hoffmann, Arvid O.I. & Shefrin, Hersh, 2014. "Technical analysis and individual investors," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 487-511.
    40. Shumway, Tyler, 1997. "The Delisting Bias in CRSP Data," Journal of Finance, American Finance Association, vol. 52(1), pages 327-340, March.
    41. Fama, Eugene F. & French, Kenneth R., 2006. "Profitability, investment and average returns," Journal of Financial Economics, Elsevier, vol. 82(3), pages 491-518, December.
    42. Da, Zhi & Huang, Xing & Jin, Lawrence J., 2021. "Extrapolative beliefs in the cross-section: What can we learn from the crowds?," Journal of Financial Economics, Elsevier, vol. 140(1), pages 175-196.
    43. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    44. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    Full references (including those not matched with items on IDEAS)

    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. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
    2. Zhu, Zhaobo & Ding, Wenjie & Jin, Yi & Shen, Dehua, 2023. "Dissecting the idiosyncratic volatility puzzle: A fundamental analysis approach," Research in International Business and Finance, Elsevier, vol. 66(C).
    3. Doron Avramov & Guy Kaplanski & Avanidhar Subrahmanyam, 2022. "Postfundamentals Price Drift in Capital Markets: A Regression Regularization Perspective," Management Science, INFORMS, vol. 68(10), pages 7658-7681, October.
    4. Zhu, Zhaobo & Sun, Licheng & Yung, Kenneth & Chen, Min, 2020. "Limited investor attention, relative fundamental strength, and the cross-section of stock returns," The British Accounting Review, Elsevier, vol. 52(4).
    5. Jacobs, Heiko, 2015. "What explains the dynamics of 100 anomalies?," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 65-85.
    6. Mazouz, Khelifa & Wu, Yuliang, 2022. "Why do firm fundamentals predict returns? Evidence from short selling activity," International Review of Financial Analysis, Elsevier, vol. 79(C).
    7. Robert F. Stambaugh & Yu Yuan, 2017. "Mispricing Factors," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1270-1315.
    8. Khasawneh, Maher & McMillan, David G. & Kambouroudis, Dimos, 2024. "Left-tail risk and UK stock return predictability: Underreaction, overreaction, and arbitrage difficulties," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    9. Zhu, Zhaobo & Sun, Licheng & Yung, Kenneth, 2020. "Fundamental strength strategy: The role of investor sentiment versus limits to arbitrage," International Review of Financial Analysis, Elsevier, vol. 71(C).
    10. Kewei Hou & Chen Xue & Lu Zhang, 2017. "Replicating Anomalies," NBER Working Papers 23394, National Bureau of Economic Research, Inc.
    11. Wu, Yuliang & Mazouz, Khelifa, 2016. "Long-term industry reversals," Journal of Banking & Finance, Elsevier, vol. 68(C), pages 236-250.
    12. Lu Zhang, 2017. "The Investment CAPM," European Financial Management, European Financial Management Association, vol. 23(4), pages 545-603, September.
    13. Yin, Libo & Wei, Ya & Han, Liyan, 2020. "Firms' profit instability and the cross-section of stock returns: Evidence from China," Research in International Business and Finance, Elsevier, vol. 53(C).
    14. Clarke, Charles, 2022. "The level, slope, and curve factor model for stocks," Journal of Financial Economics, Elsevier, vol. 143(1), pages 159-187.
    15. Tran, Vu Le, 2023. "Sentiment and covariance characteristics," International Review of Financial Analysis, Elsevier, vol. 86(C).
    16. Ang, Tze Chuan ‘Chewie’ & Lam, F.Y. Eric C. & Wei, K.C. John, 2020. "Mispricing firm-level productivity," Journal of Empirical Finance, Elsevier, vol. 58(C), pages 139-163.
    17. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    18. Wang, Baolian, 2019. "The cash conversion cycle spread," Journal of Financial Economics, Elsevier, vol. 133(2), pages 472-497.
    19. Bui, Dien Giau & Kong, De-Rong & Lin, Chih-Yung & Lin, Tse-Chun, 2023. "Momentum in machine learning: Evidence from the Taiwan stock market," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
    20. Li, Kai, 2021. "Nonlinear effect of sentiment on momentum," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).

    More about this item

    Keywords

    Fundamental Analysis; Technical Analysis; Arbitrage Risk; Informed Trading;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:hal:journl:hal-04703041. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.