Author(s)

Zihao Fan ¹

Affiliation(s)

¹ School of Economics, Beijing Technology and Business University, Beijing, China

Corresponding Author

Zihao Fan

ABSTRACT

This study explores the impact of investor sentiment on futures pricing efficiency and employs dual machine learning (DML) and generalized random forest (GRF) methods for causal inference analysis. By constructing an investor sentiment index and combining it with pricing efficiency indicators for the futures market, empirical results demonstrate that sentiment has a significant positive impact on futures pricing efficiency, particularly in contexts of high market volatility, where the impact of sentiment fluctuations on pricing bias is more pronounced. Furthermore, the study reveals the heterogeneity of sentiment effects across different market phases, with the impact of sentiment on pricing efficiency being more pronounced in bull markets and relatively weaker in bear and volatile markets. This study provides new empirical evidence for understanding the relationship between investor sentiment and futures market pricing efficiency and offers theoretical support for future market regulation and policymaking.

KEYWORDS

Investor Sentiment, Futures Pricing Efficiency, Dual Machine Learning, Generalized Random Forest, Causal Inference

CITE THIS PAPER

Zihao Fan, Study on the Nonlinear Causal Impact of Investor Sentiment on Futures Pricing Efficiency: Based on Generalized Random Forest and Dual Machine Learning Methods. Advances in Computer, Signals and Systems (2025) Vol. 9: 130-139. DOI: http://dx.doi.org/10.23977/acss.2025.090316.

REFERENCES

[1] A. Elnagar, L. Lulu, and O. Einea, "An annotated huge dataset for standard and colloquial arabic reviews for subjective sentiment analysis," Arab. Comput. Linguist., vol. 142, pp. 182–189, Jan. 2018, doi: 10.1016/j.procs. 2018. 10. 474.
[2] J. Wang and X. He, "An optimal multi-scale and multi-factor two-stage integration paradigm coupled with investor sentiment for carbon price prediction," Inf. Process. Manage., vol. 62, no. 1, p. 103953, Jan. 2025, doi: 10.1016/j.ipm. 2024. 103953.
[3] Y. Deng, M. Wei, and L. Wei, "Does sentiment of investor protection information disclosures affect credit risk premium? Evidence from China," 11th Int. Conf. Inf. Technol. Quant. Manag. (ITQM 2024), vol. 242, pp. 781–788, Jan. 2024, doi: 10.1016/j.procs.2024.08.194.
[4] Y. Zhang, H. Li, and G. Ren, “Estimating heterogeneous treatment effects in road safety analysis using generalized random forests," Accid. Anal. Prev., vol. 165, p. 106507, Feb. 2022, doi: 10.1016/j.aap.2021.106507.
[5] Y. Seetharam and K. Nyakurukwa, "Financial textual sentiment connectedness: evidence from alternative data," Int. J. Inf. Manage. Data Insights, vol. 5, no. 1, p. 100337, Jun. 2025, doi: 10.1016/j.jjimei.2025.100337.
[6] Y. Seetharam and K. Nyakurukwa, "Headlines or hashtags? The battle in social media for investor sentiment in the stock market," Int. J. Inf. Manage. Data Insights, vol. 4, no. 2, p. 100273, Nov. 2024, doi: 10.1016/j.jjimei.2024.100273.
[7] S. Z. Zaidi, X. Wang, Y. Azati, J. Li, T. Fan, and M. Quddus, "Heterogeneous and differential treatment effect analysis of safety improvements on freeways using causal inference," Accid. Anal. Prev., vol. 220, p. 108173, Sep. 2025, doi: 10. 1016/j. aap.2025.108173.
[8] J. Wang, Z. Li, Y. Chen, S. Han, and L. Kong, "Hybrid causal inference framework for long-chain drought propagation networks: combining convergent cross-mapping and generalized random forest," Ecol. Indic., vol. 178, p. 113939, Sep. 2025, doi: 10.1016/j.ecolind.2025.113939.
[9] Y. Xu, B. Wu, J. L. Nicolau, R. Law, and S. Xiang, "Impact of smart door locks on traveler satisfaction on accommodation-sharing platform: an empirical investigation based on generalized random forests," Int. J. Hosp. Manag., vol. 131, p. 104288, Oct. 2025, doi: 10.1016/j.ijhm.2025.104288.
[10] F. Obster, J. Brand, M. Ciolacu, and A. Humpe, "Improving boosted generalized additive models with random forests: a zoo visitor case study for smart tourism," 4th Int. Conf. Ind. 4.0 Smart Manuf., vol. 217, pp. 187–197, Jan. 2023, doi: 10.1016/j.procs.2022.12.214.
[11] M. Birjali, A. Beni-Hssane, and M. Erritali, "Machine learning and semantic sentiment analysis based algorithms for suicide sentiment prediction in social networks," 8th Int. Conf. Emerg. Ubiquitous Syst. Pervasive Netw. (EUSPN 2017) / 7th Int. Conf. Curr. Future Trends Inf. Commun. Technol. Healthc. (ICTH-2017) / Affil. Workshops, vol. 113, pp. 65–72, Jan. 2017, doi: 10.1016/j.procs.2017.08.290.
[12] R. Buse, K. Görgen, and M. Schienle, "Predicting value at risk for cryptocurrencies with generalized random forests," Int. J. Forecasting, vol. 41, no. 3, pp. 1199–1222, Jul. 2025, doi: 10.1016/j.ijforecast.2024.12.002.
[13] A. Bhardwaj, Y. Narayan, Vanraj, Pawan, and M. Dutta, "Sentiment analysis for indian stock market prediction using sensex and nifty," Proc. 4th Int. Conf. Eco-friendly Comput. Commun. Syst., vol. 70, pp. 85–91, Jan. 2015, doi:10.1016/j.procs.2015.10.043.
[14] I. Ghazouani, I. Ghazouani, and A. Omri, "Virtual influence, real impact: deciphering social media sentiment and its effects on cryptocurrency market dynamics," Blockchain: Res. Appl., p. 100375, Aug. 2025, doi: 10.1016/j. bcra. 2025. 100375.
[15] G. Fang and X. Zhou, "Web semantic analysis of investor sentiment, short trading, and stock market volatility," Int. J. Semant. Web Inf. Syst., vol. 20, no. 1, Jan. 2024, doi: 10.4018/IJSWIS.353903.

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