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Fundamental characteristics, machine learning, and stock price crash risk

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  • Jiang, Fuwei
  • Ma, Tian
  • Zhu, Feifei

Abstract

We investigate the application of machine learning algorithms for predicting stock price crash risks by employing a set of firm-specific characteristics of the Chinese stock market. The results suggest that machine learning techniques are superior in capturing the nuances of stock price crash risk, particularly through profitability and value versus growth features. These techniques perform well within state-owned enterprises and during periods of low economic policy uncertainty, and predictive insights primarily originate from intra-industry dynamics. In addition, we offer corporate finance- and financial market-based interpretations of machine learning's predictability, as well as a comprehensive understanding of its key determinants.

Suggested Citation

  • Jiang, Fuwei & Ma, Tian & Zhu, Feifei, 2024. "Fundamental characteristics, machine learning, and stock price crash risk," Journal of Financial Markets, Elsevier, vol. 69(C).
    • Handle: RePEc:eee:finmar:v:69:y:2024:i:c:s1386418124000260
    DOI: 10.1016/j.finmar.2024.100908
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    as
    1. Huang, Yun & Luk, Paul, 2020. "Measuring economic policy uncertainty in China," China Economic Review, Elsevier, vol. 59(C).
    2. N. Bloom, 2016. "Fluctuations in uncertainty," Voprosy Ekonomiki, NP Voprosy Ekonomiki, issue 4.
    3. Harrison Hong & Jeremy C. Stein, 2003. "Differences of Opinion, Short-Sales Constraints, and Market Crashes," The Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 487-525.
    4. Jin, Li & Myers, Stewart C., 2006. "R2 around the world: New theory and new tests," Journal of Financial Economics, Elsevier, vol. 79(2), pages 257-292, February.
    5. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2001. "Forecasting crashes: trading volume, past returns, and conditional skewness in stock prices," Journal of Financial Economics, Elsevier, vol. 61(3), pages 345-381, September.
    6. Ni, Xiaoran & Zhu, Weikang, 2016. "Short-sales and stock price crash risk: Evidence from an emerging market," Economics Letters, Elsevier, vol. 144(C), pages 22-24.
    7. Xu, Nianhang & Li, Xiaorong & Yuan, Qingbo & Chan, Kam C., 2014. "Excess perks and stock price crash risk: Evidence from China," Journal of Corporate Finance, Elsevier, vol. 25(C), pages 419-434.
    8. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    9. G Andrew Karolyi & Stijn Van Nieuwerburgh, 2020. "New Methods for the Cross-Section of Returns," Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 1879-1890.
    10. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    11. Kent Daniel & Sheridan Titman, 2006. "Market Reactions to Tangible and Intangible Information," Journal of Finance, American Finance Association, vol. 61(4), pages 1605-1643, August.
    12. Wei Zhu, 2016. "Accruals and price crashes," Review of Accounting Studies, Springer, vol. 21(2), pages 349-399, June.
    13. Maury, Benjamin & Pajuste, Anete, 2005. "Multiple large shareholders and firm value," Journal of Banking & Finance, Elsevier, vol. 29(7), pages 1813-1834, July.
    14. Eden, Benjamin & Jovanovic, Boyan, 1994. "Asymmetric Information and the Excess Volatility of Stock Prices," Economic Inquiry, Western Economic Association International, vol. 32(2), pages 228-235, April.
    15. Hutton, Amy P. & Marcus, Alan J. & Tehranian, Hassan, 2009. "Opaque financial reports, R2, and crash risk," Journal of Financial Economics, Elsevier, vol. 94(1), pages 67-86, October.
    16. 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.
    17. Hameed, Allaudeen & Mian, G. Mujtaba, 2015. "Industries and Stock Return Reversals," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 50(1-2), pages 89-117, April.
    18. Jingjing Xu & Yan Zhang & Yizhe Xie, 2020. "Controlling Shareholder’s Share Pledging and Firm’s Auditor Choice," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(4), pages 750-770, March.
    19. Panayiotis C. Andreou & Christodoulos Louca & Andreas P. Petrou, 2017. "CEO Age and Stock Price Crash Risk," Review of Finance, European Finance Association, vol. 21(3), pages 1287-1325.
    20. 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.
    21. Roychowdhury, Sugata, 2006. "Earnings management through real activities manipulation," Journal of Accounting and Economics, Elsevier, vol. 42(3), pages 335-370, December.
    22. Kewei Hou & Chen Xue & Lu Zhang, 2020. "Replicating Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2019-2133.
    23. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    24. Jiang, Fuxiu & Cai, Wenjing & Wang, Xue & Zhu, Bing, 2018. "Multiple large shareholders and corporate investment: Evidence from China," Journal of Corporate Finance, Elsevier, vol. 50(C), pages 66-83.
    25. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2010. "Out-of-Sample Equity Premium Prediction: Combination Forecasts and Links to the Real Economy," The Review of Financial Studies, Society for Financial Studies, vol. 23(2), pages 821-862, February.
    26. Campbell R. Harvey & Akhtar Siddique, 2000. "Conditional Skewness in Asset Pricing Tests," Journal of Finance, American Finance Association, vol. 55(3), pages 1263-1295, June.
    27. Barlevy, Gadi & Veronesi, Pietro, 2003. "Rational panics and stock market crashes," Journal of Economic Theory, Elsevier, vol. 110(2), pages 234-263, June.
    28. Bergstresser, Daniel & Philippon, Thomas, 2006. "CEO incentives and earnings management," Journal of Financial Economics, Elsevier, vol. 80(3), pages 511-529, June.
    29. 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.
    30. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    31. Kim, Jeong-Bon & Li, Yinghua & Zhang, Liandong, 2011. "CFOs versus CEOs: Equity incentives and crashes," Journal of Financial Economics, Elsevier, vol. 101(3), pages 713-730, September.
    32. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    33. Joseph D. Piotroski & T. J. Wong & Tianyu Zhang, 2015. "Political Incentives to Suppress Negative Information: Evidence from Chinese Listed Firms," Journal of Accounting Research, Wiley Blackwell, vol. 53(2), pages 405-459, May.
    34. Boubaker, Sabri & Mansali, Hatem & Rjiba, Hatem, 2014. "Large controlling shareholders and stock price synchronicity," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 80-96.
    35. Lin, Justin Yifu & Cai, Fang & Li, Zhou, 1998. "Competition, Policy Burdens, and State-Owned Enterprise Reform," American Economic Review, American Economic Association, vol. 88(2), pages 422-427, May.
    36. 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.
    37. H. Henry Cao & Joshua D. Coval & David Hirshleifer, 2002. "Sidelined Investors, Trading-Generated News, and Security Returns," The Review of Financial Studies, Society for Financial Studies, vol. 15(2), pages 615-648, March.
    38. Chong-En Bai & Jiangyong Lu & Zhigang Tao, 2006. "The Multitask Theory of State Enterprise Reform: Empirical Evidence from China," American Economic Review, American Economic Association, vol. 96(2), pages 353-357, May.
    39. Evgeny Lyandres & Le Sun & Lu Zhang, 2008. "The New Issues Puzzle: Testing the Investment-Based Explanation," The Review of Financial Studies, Society for Financial Studies, vol. 21(6), pages 2825-2855, November.
    40. Fuxiu Jiang & Kenneth A Kim, 2020. "Corporate Governance in China: A Survey [The role of boards of directors in corporate governance: a conceptual framework and survey]," Review of Finance, European Finance Association, vol. 24(4), pages 733-772.
    41. Armstrong, Christopher S. & Larcker, David F. & Ormazabal, Gaizka & Taylor, Daniel J., 2013. "The relation between equity incentives and misreporting: The role of risk-taking incentives," Journal of Financial Economics, Elsevier, vol. 109(2), pages 327-350.
    42. Li, Wanli & Zhou, Jingting & Yan, Ziqiao & Zhang, He, 2020. "Controlling shareholder share pledging and firm cash dividends," Emerging Markets Review, Elsevier, vol. 42(C).
    43. Duffee, Gregory R., 1995. "Stock returns and volatility A firm-level analysis," Journal of Financial Economics, Elsevier, vol. 37(3), pages 399-420, March.
    44. He, Lerong & Wan, Hong & Zhou, Xin, 2014. "How are political connections valued in China? Evidence from market reaction to CEO succession," International Review of Financial Analysis, Elsevier, vol. 36(C), pages 141-152.
    45. Jeong†Bon Kim & Zheng Wang & Liandong Zhang, 2016. "CEO Overconfidence and Stock Price Crash Risk," Contemporary Accounting Research, John Wiley & Sons, vol. 33(4), pages 1720-1749, December.
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    More about this item

    Keywords

    Crash risk; Machine learning; Fundamental characteristics; Big data;
    All these keywords.

    JEL classification:

    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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