Phản ứng của thị trường chứng khoán trước các bản tin kinh tế vĩ mô

Authors

  • Đạt Huỳnh Tấn University of Technology Sydney Author
  • Phúc Từ Hà Trường Đại học Kinh tế - Luật, Đại học Quốc gia Thành phố Hồ Chí Minh Author
  • Như Đặng Anh Trường Đại học Kinh tế - Luật, Đại học Quốc gia Thành phố Hồ Chí Minh Author

DOI:

https://doi.org/10.24311/jabes/2025.36.11.01

Keywords:

Stock market reaction, Economic news, Sentiment analysis, Large language models, Explainable AI

Abstract

This study examines the VN-Index's response to macroeconomic news through advanced natural language processing (NLP) and machine learning techniques. The authors analyzed 18,253 economic news articles from Cafef.vn, collected from September 1, 2021, to August 31, 2024, to evaluate the impact of 12 key economic factors and overall sentiment. Utilizing Large Language Models (LLMs) such as GPT-4o-mini (for primary sentiment scoring) and Gemini-1.5-flash (for validation with 70% correlation), the authors quantified sentiment and integrated it with VN-Index historical data to build an XGBoost model. The model predicts VN-Index closing prices with an R² of 0.9879, demonstrating superior forecasting accuracy. Explainable AI (XAI) tools like SHAP and LIME were applied to interpret results, identifying “Earnings Reports and Dividends”, “Foreign Investment Policies”, and “Political Stability” as the main drivers of VN-Index volatility. This research confirms the strong impact of macroeconomic news on stock market dynamics, enriches the “noise trader behavior” theory by illustrating category-specific investor reactions, and provides actionable insights for market dynamics in emerging economies like Vietnam, offering investors a transparent AI framework for decision-making.

References

Andersen, T. G., Bollerslev, T., Diebold, F. X., & Vega, C. (2007). Real-time price discovery in global stock, bond and foreign exchange markets. Journal of International Economics, 73(2), 251-277. https://doi.org/10.1016/j.jinteco.2007.02.004

Bhattacharya, U., & Daouk, H. (2002). The world price of insider trading. The Journal of Finance, 57(1), 75-108. http://www.jstor.org/stable/2697834

Biswas, R. (2023). Vietnam GDP growth improves in third quarter of 2023. S&P Global Market Intelligence. https://www.spglobal.com/marketintelligence/en/mi/research-analysis/vietnam-gdp-growth-improves-in-third-quarter-of-2023-oct23.html

Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of Computational Science, 2(1), 1-8. https://doi.org/10.1016/j.jocs.2010.12.007

Boudoukh, J., & Richardson, M. (1993). Stock returns and inflation: A long-horizon perspective. The American Economic Review, 83(5), 1346-1355. http://www.jstor.org/stable/2117566

Boutchkova, M., Doshi, H., Durnev, A., & Molchanov, A. (2012). Precarious politics and return volatility. The Review of Financial Studies, 25(4), 1111-1154. https://doi.org/10.1093/rfs/hhr100

Breiman, L. (2001). Random forests. Machine Learning, 45, 5-32.

Bunjaku, F. (2024). Decoding the stock market and GDP relationship over the long term: Implications for index fund investments. Studies in Business and Economics, 19, 49-59. https://doi.org/10.2478/sbe-2024-0024

Cao, P. T. H., & Vo, D. H. (2025). Market responses to geopolitical risk and economic policy uncertainty: Evidence from Vietnam. Heliyon, 11(4), e42703. https://doi.org/10.1016/j.heliyon.2025.e42703

Chen, C., Dongxing, W., Chunyan, H., & Xiaojie, Y. (2014). Exploiting social media for stock market prediction with factorization machine. 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2, 142-149. https://doi.org/10.1109/WI-IAT.2014.91

Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 13–17 August 2016, 785-794. https://doi.org/10.1145/2939672.2939785

Chen, W., Liu, W., Zheng, J., & Zhang, X. (2025). Leveraging large language model as news sentiment predictor in stock markets: A knowledge-enhanced strategy. Discover Computing, 28(1), 74. https://doi.org/10.1007/s10791-025-09573-7

Chikwira, C., & Mohammed, J. I. (2023). The impact of the stock market on liquidity and economic growth: Evidence of volatile market. Economies, 11(6). https://doi.org/10.3390/economies11060155

Coates, J. (2007). The goals and promise of the Sarbanes-Oxley Act. Journal of Economic Perspectives, 21, 91-116. https://doi.org/10.1257/jep.21.1.91

De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990). Noise trader risk in financial markets. Journal of Political Economy, 98(4), 703-738. https://doi.org/10.1086/261703

Demirgüç-Kunt, A., & Levine, R. (1996). Stock markets, corporate finance, and economic growth: An overview. The World Bank Economic Review, 10(2), 223-239. https://doi.org/10.1093/wber/10.2.223

Dinh, T. S., Bui, T., Bui, T. M. H., & Nguyen, V. B. (2017). Determinants of stock market development: The case of developing countries and Vietnam. Journal of Economic Development, 24, 32-53. https://doi.org/10.24311/jed/2017.24.1.05

Doukas, J., & Lang, H. (2003). Foreign direct investment, diversification and firm performance. Journal of International Business Studies, 34, 153-172. https://doi.org/10.1057/palgrave.jibs.8400014

Downs, T., & Hendershott, P. H. (1987). Tax policy and stock prices. National Tax Journal, 40(2), 183-190. https://doi.org/10.1086/NTJ41788656

Ehrmann, M., & Fratzscher, M. (2005). Equal size, equal role? Interest rate interdependence between the euro area and the United States. The Economic Journal, 115(506), 928-948. http://www.jstor.org/stable/3590356

Fama, E. F., Fisher, L., Jensen, M. C., & Roll, R. (1969). The adjustment of stock prices to new information. International Economic Review, 10(1), 1-21. https://doi.org/10.2307/2525569

Hoi, L. Q., Thu, N. T. H., Hung, N. X., Uyen, P. T., Huong, T. T., Minh, T. T. H., & Anh, H. T. P. (2024). The impact of the global minimum tax on Vietnam’s foreign direct investment attraction. Asia and the Global Economy, 4(2), 100090. https://doi.org/10.1016/j.aglobe.2024.100090

Nguyen, H. D., & Le, V. L. (2024). Impacts of inflation on the Vietnamese stock market in economic turbulence. The VMOST Journal of Social Sciences and Humanities, 66(1), 16-20. https://doi.org/10.31276/VMOSTJOSSH.66(1).16-20

Jensen, M. C., & Ruback, R. S. (1983). The market for corporate control: The scientific evidence. Journal of Financial Economics, 11(1), 5-50. https://doi.org/10.1016/0304-405X(83)90004-1

Khang, P. Q., Kaczmarczyk, K., Tutak, P., Golec, P., Kuziak, K., Depczyński, R., Hernes, M., & Rot, A. (2021). Machine learning for liquidity prediction on Vietnamese stock market. Procedia Computer Science, 192, 3590-3597. https://doi.org/10.1016/j.procs.2021.09.132

Kim, J. (2023). Stock market reaction to US interest rate hike: Evidence from an emerging market. Heliyon, 9(5), e15758. https://doi.org/10.1016/j.heliyon.2023.e15758

Kirtac, K., & Germano, G. (2024). Sentiment trading with large language models. Finance Research Letters, 62, 105227. https://doi.org/10.1016/j.frl.2024.105227

Kwon, B., Park, T., Rungcharoenkitkul, P., & Smets, F. (2025). Parsing the pulse: Decomposing macroeconomic sentiment with LLMs. BIS Working Papers (Issue 1294). Bank for International Settlements. https://EconPapers.repec.org/RePEc:bis:biswps:1294

Lee, B. S. (2010). Stock returns and inflation revisited: An evaluation of the inflation illusion hypothesis. Journal of Banking & Finance, 34(6), 1257-1273. https://doi.org/10.1016/j.jbankfin.2009.11.023

Levine, R. (1997). Financial development and economic growth: Views and agenda. Journal of Economic Literature, 35(2), 688-726. http://www.jstor.org/stable/2729790

Li, X., Wu, P., & Wang, W. (2020). Incorporating stock prices and news sentiments for stock market prediction: A case of Hong Kong. Information Processing & Management, 57(5), 102212. https://doi.org/10.1016/j.ipm.2020.102212

Lundberg, S. M., & Lee, S.-I. (2017). A unified approach to interpreting model predictions. In I. Guyon, U. Von Luxburg, S. Bengio, H. Wallach, R. Fergus, S. Vishwanathan, & R. Garnett (Eds.), Advances in Neural Information Processing Systems (Vol. 30). Curran Associates, Inc. https://proceedings.neurips.cc/paper_files/paper/2017/file/8a20a8621978632d76c43dfd28b67767-Paper.pdf

Moeller, S. B., Schlingemann, F. P., & Stulz, R. M. (2004). Firm size and the gains from acquisitions. Journal of Financial Economics, 73(2), 201-228. https://doi.org/10.1016/j.jfineco.2003.07.002

Ngo, N., Nguyen, H., Nguyen, Y., & Le, S. (2024). How does the Vietnamese stock market react when the Fed gives an announcement in time at the zero lower bound?. Heliyon, 10, e40047. https://doi.org/10.1016/j.heliyon.2024.e40047

Nguyen, H. T. T., Tram, H. T. X., & Nguyen, L. T. T. (2023). Interest rates and systemic risk: Evidence from the Vietnamese economy. The Journal of Economic Asymmetries, 27, e00294. https://doi.org/10.1016/j.jeca.2023.e00294

Nguyen, V. C., & Nguyen, T. T. (2022). Dependence between Chinese stock market and Vietnamese stock market during the Covid-19 pandemic. Heliyon, 8(10), e11090. https://doi.org/10.1016/j.heliyon.2022.e11090

Pástor, Ľ., & Veronesi, P. (2013). Political uncertainty and risk premia. Journal of Financial Economics, 110(3), 520–545. https://doi.org/10.1016/j.jfineco.2013.08.007

Phan, T. K. H., Hoai, N., & Tran. (2019). Dividend policy and stock price volatility in an emerging market: Does ownership structure matter? Cogent Economics & Finance, 7(1), 1637051. https://doi.org/10.1080/23322039.2019.1637051

Phuoc, T., Anh, P. T. K., Tam, P. H., & Nguyen, C. V. (2024). Applying machine learning algorithms to predict the stock price trend in the stock market – The case of Vietnam. Humanities and Social Sciences Communications, 11(1), 393. https://doi.org/10.1057/s41599-024-02807-x

Ónozó, L. R., Arthur, F. V., & Gyires-Tóth, B. (2024). Leveraging LLMs for financial news analysis and macroeconomic indicator nowcasting. IEEE Access, 12, 160529–160547. https://doi.org/10.1109/ACCESS.2024.3488363

Ribeiro, M. T., Singh, S., & Guestrin, C. (2016). “Why should I trust you?”: Explaining the predictions of any classifier. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '16), 1135-1144. Association for Computing Machinery. https://doi.org/10.1145/2939672.2939778

Ritter, J. (2004). Economic growth and equity returns. Pacific-Basin Finance Journal, 13, 489-503. https://doi.org/10.1016/j.pacfin.2005.07.001

Santow, L. J., & Gordon, M. J. (1962). The investment, financing, and valuation of the corporation. https://api.semanticscholar.org/CorpusID:203555679

Su, D. T., Bui, T., Bui, T. M. H., & Nguyen, V. B. (2017). Determinants of stock market development: The case of developing countries and Vietnam. Journal of Economic Development, 24, 32-53.

Tetlock, P. C. (2007). Giving content to investor sentiment: The role of media in the stock market. The Journal of Finance, 62(3), 1139-1168. https://doi.org/10.1111/j.1540-6261.2007.01232.x

Thanh, N. T., & Linh, D. T. (2016). Impacts of monetary policy on Vietnam stock price. Proceedings of the International Conference on Electronics, Mechanics, Culture and Medicine, 136-142. https://doi.org/10.2991/emcm-15.2016.26

Van, C. B., Cao, T. D., Thi, T. N., Dung, H. P., Minh, H. D., An, L. N. H., & Hong, T. P. (2024). Studying the influence of Vietnamese social media on Vietnamese stock market to forecast market trends. In R. Silhavy & P. Silhavy (Eds.), Artificial Intelligence Algorithm Design for Systems (pp. 437-452). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-70518-2_39

Vuong, Q.-H., Tran, T. D., & Nguyen, T. T. H. (2009). M&A market in Vietnam’s transition economy. Corporate Governance & Finance EJournal. https://api.semanticscholar.org/CorpusID:166249757

Wang, S., & Mayes, D. G. (2012). Monetary policy announcements and stock reactions: An international comparison. The North American Journal of Economics and Finance, 23(2), 145-164. https://doi.org/10.1016/j.najef.2012.02.002

Wei, J., Wang, X., Schuurmans, D., Bosma, M., Richter, B., Xia, F., Chi, E., Le, Q. V., & Zhou, D. (2022). Chain-of-thought prompting elicits reasoning in large language models. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), Advances in Neural Information Processing Systems (Vol. 35, pp. 24824-24837). Curran Associates, Inc. https://proceedings.neurips.cc/paper_files/paper/2022/file/9d5609613524ecf4f15af0f7b31abca4-Paper-Conference.pdf

World Bank. (2023). Vietnam’s economy forecast to grow 6.3 percent in 2023. World Bank. https://www.worldbank.org/en/news/press-release/2023/03/13/vietnam-s-economy-forecast-to-grow-by-6-3-in-2023-world-bank-report-says

Published

2025-12-26

Issue

Section

Articles

How to Cite

Huỳnh Tấn, Đ., Từ Hà, P., & Đặng Anh, N. (2025). Phản ứng của thị trường chứng khoán trước các bản tin kinh tế vĩ mô. JOURNAL OF ASIAN BUSINESS AND ECONOMIC STUDIES, 36(11), 04-22. https://doi.org/10.24311/jabes/2025.36.11.01