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Investor sentiment and optimizing traditional quantitative investments

Author

Listed:
  • Chen, Zheng
  • Li, Wenlin
  • Huang, Jia

Abstract

Recent research highlights the interplay between investor sentiment and stock market dynamics. This study introduces an innovative approach to quantitative trading by integrating technical and fundamental analysis via textual data analysis and machine learning. Specifically, we propose a refined Moving Average Convergence Divergence (MACD) indicator by incorporating a customized investor sentiment trend factor. To assess the efficacy of this integrated methodology, we conducted an empirical analysis, focusing on the Shanghai Stock Exchange Composite Index, which has demonstrated notable short-term volatility over the past year. A rigorous comparative evaluation of trading strategies was undertaken, contrasting performance metrics before and after the integration of the sentiment-enhanced MACD. Our findings reveal that the strategies developed in this study yield substantial improvements in both profitability and the stability of quantitative stock market trading. By offering investors a novel and sophisticated approach to quantitative trading, this study contributes valuable insights and methodologies to the field of financial economics, with potential implications for both academic research and practical investment strategies.

Suggested Citation

  • Chen, Zheng & Li, Wenlin & Huang, Jia, 2025. "Investor sentiment and optimizing traditional quantitative investments," International Review of Economics & Finance, Elsevier, vol. 101(C).
    • Handle: RePEc:eee:reveco:v:101:y:2025:i:c:s1059056025003909
    DOI: 10.1016/j.iref.2025.104227
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Foster, F Douglas & Viswanathan, S, 1990. "A Theory of the Interday Variations in Volume, Variance, and Trading Costs in Securities Markets," The Review of Financial Studies, Society for Financial Studies, vol. 3(4), pages 593-624.
    3. Jiang, Fuwei & Lee, Joshua & Martin, Xiumin & Zhou, Guofu, 2019. "Manager sentiment and stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 126-149.
    4. Juvenal José Duarte & Sahudy Montenegro González & José César Cruz, 2021. "Predicting Stock Price Falls Using News Data: Evidence from the Brazilian Market," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 311-340, January.
    5. Haigang Zhou & John Geppert & Dongmin Kong, 2010. "An Anatomy of Trading Strategies: Evidence from China," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 46(2), pages 66-79, March.
    6. Neely, Christopher & Weller, Paul & Dittmar, Rob, 1997. "Is Technical Analysis in the Foreign Exchange Market Profitable? A Genetic Programming Approach," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(4), pages 405-426, December.
    7. Dolaeva, Aishat & Beliaeva, Uliana & Grigoriev, Dmitry & Semenov, Alexander & Rysz, Maciej, 2025. "Analyzing and forecasting P/E ratios using investor sentiment in panel data regression and LSTM models," International Review of Economics & Finance, Elsevier, vol. 98(C).
    8. Christopher J. Neely, 1997. "Technical analysis in the foreign exchange market: a layman's guide," Review, Federal Reserve Bank of St. Louis, issue Sep, pages 23-38.
    9. Meir Statman & Steven Thorley & Keith Vorkink, 2006. "Investor Overconfidence and Trading Volume," The Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1531-1565.
    10. R. Rosillo & D. de la Fuente & J. A. L. Brugos, 2013. "Technical analysis and the Spanish stock exchange: testing the RSI, MACD, momentum and stochastic rules using Spanish market companies," Applied Economics, Taylor & Francis Journals, vol. 45(12), pages 1541-1550, April.
    11. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    12. Zhi Da & Joseph Engelberg & Pengjie Gao, 2015. "Editor's Choice The Sum of All FEARS Investor Sentiment and Asset Prices," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 1-32.
    13. Schadner, Wolfgang, 2021. "On the persistence of market sentiment: A multifractal fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    14. Chung-Han Hsieh, 2023. "On Data-Driven Drawdown Control with Restart Mechanism in Trading," Papers 2303.02613, arXiv.org.
    15. M. J. Fields, 1931. "Stock Prices: A Problem in Verification," The Journal of Business, University of Chicago Press, vol. 4, pages 415-415.
    16. Gao, Yang & Zhao, Chengjie & Wang, Yaojun, 2024. "Investor sentiment and stock returns: New evidence from Chinese carbon-neutral stock markets based on multi-source data," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 438-450.
    17. Taylor, Mark P. & Allen, Helen, 1992. "The use of technical analysis in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 11(3), pages 304-314, June.
    18. Shiller, Robert J, 1981. "Do Stock Prices Move Too Much to be Justified by Subsequent Changes in Dividends?," American Economic Review, American Economic Association, vol. 71(3), pages 421-436, June.
    19. Nicholas Barberis & Ming Huang & Tano Santos, 2001. "Prospect Theory and Asset Prices," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 1-53.
    20. Ki-Yeol Kwon & Richard Kish, 2002. "Technical trading strategies and return predictability: NYSE," Applied Financial Economics, Taylor & Francis Journals, vol. 12(9), pages 639-653.
    21. Stanislaus Maier-Paape, 2015. "Automatic one two three," Quantitative Finance, Taylor & Francis Journals, vol. 15(2), pages 247-260, February.
    22. 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.
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    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G40 - Financial Economics - - Behavioral Finance - - - General

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