Phản ứng của thị trường chứng khoán trước các bản tin kinh tế vĩ mô
DOI:
https://doi.org/10.24311/jabes/2025.36.11.01Từ khóa:
Phản ứng thị trường chứng khoán, Tin tức kinh tế, Phân tích cảm xúc, Mô hình ngôn ngữ lớn, AI Giải thíchTóm tắt
Nghiên cứu này khám phá phản ứng của VN-Index trước các tin tức kinh tế vĩ mô bằng cách áp dụng xử lý ngôn ngữ tự nhiên và máy học tiên tiến. Nhóm tác giả phân tích 18.253 bài báo kinh tế từ trang cafef.vn, thu thập từ ngày 01/09/2021 đến 31/08/2024, để đánh giá mức độ tác động của 12 yếu tố kinh tế quan trọng và cảm xúc tổng thể. Sử dụng Mô hình ngôn ngữ lớn như GPT-4o-mini (dùng để đánh giá mức độ tác động chính) và Gemini-1.5-flash (đối chiếu với độ tương đồng 70%), mức độ tác động được định lượng và tích hợp với dữ liệu lịch sử VN-Index để xây dựng mô hình XGBoost. Mô hình dự đoán giá đóng cửa VN-Index với R² đạt 0,9879, thể hiện khả năng dự báo vượt trội. Các công cụ trí tuệ nhân tạo giải thích như SHAP và LIME được sử dụng để phân tích, cho thấy “Báo cáo thu nhập và cổ tức”, “Chính sách đầu tư nước ngoài” và “Ổn định chính trị” là yếu tố chính tác động đến biến động VN-Index. Nghiên cứu xác nhận ảnh hưởng mạnh mẽ của tin tức kinh tế lên thị trường, bổ sung lý thuyết nhà đầu tư bất hợp lý bằng cách chứng minh phản ứng nhà đầu tư thay đổi theo loại tin tức, đồng thời nâng cao hiểu biết về động lực thị trường tại các nước mới nổi như Việt Nam và cung cấp khung AI minh bạch hỗ trợ nhà đầu tư ra quyết định.
Tài liệu tham khảo
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
Tải xuống
Đã Xuất bản
Số
Chuyên mục
Giấy phép
Bản quyền (c) 2025 Tạp chí Nghiên cứu Kinh tế và Kinh doanh Châu Á
Tác phẩm này được cấp phép theo Giấy phép quốc tế Creative Commons Attribution-NonCommercial 4.0 .
Cách trích dẫn
