
Can AI Agent Be the New Assistant to Robo-Advisers?
Yong HE, Yi YANG, Yan CHEN, Mingzhu HU
China Journal of Econometrics ›› 2025, Vol. 5 ›› Issue (3) : 818-841.
Can AI Agent Be the New Assistant to Robo-Advisers?
AI agent / large language models / Robo-advisors / multimodal data {{custom_keyword}} /
陈张杭健, 吴粤, 李世炳, 任飞, (2021). 股吧个体信息交互对股价联动关系的影响研究[J]. 管理科学学报, 24(5): 47-69.
|
Chen Z H J, Wu Y, Li S B, Ren F, (2021). The Impact of Individuals' Information Interaction in Stock Bars on Stock Price Co-movement[J]. Journal of Management Sciences in China, 24(5): 47-69.
|
方思然, 郭明君, 魏云捷, (2023). 加入舆情信息是否可以有效提高汇率预测效果?[J]. 计量经济学报, 3(2): 464-486.
|
Fang S R, Guo M J, Wei Y J, (2023). Is the Inclusion of Public Opinion Information Effective in Improving Exchange Rate Forecasting?[J]. China Journal of Econometrics, 3(2): 464-486.
|
何勇, 李琪琪, 焦丽, 黄文萱, (2023). 另类数据在中国股票市场投资中有用吗?——基于财经短视频、图像、文本数据的探究[J]. 计量经济学报, 3(4): 1008-1031.
|
He Y, Lee Q Q, Jiao L, Huang W X, (2023). Is Alternative Data Useful in Chinese Stock Market Investment?—An Exploration Based on Financial Short Videos, Images, and Text Data[J]. China Journal of Econometrics, 3(4): 1008-1031.
|
何勇, 焦丽, 杨艺, 祝怡菲, (2024). AI 大模型赋能金融市场量化投资? 基于另类数据与传统金融数据的研究[J]. 计量经济学报, 4(3): 761-783.
|
He Y, Jiao L, Yang Y, Zhu Y F, (2024). AI Large Language Model Empowers Quantitative Investment in Financial Markets? Research Based on Alternative Data and Traditional Financial Data[J]. China Journal of Econometrics, 4(3): 761-783.
|
洪永淼, 汪寿阳, (2021). 大数据如何改变经济学研究范式?[J]. 管理世界, 37(10): 40-55.
|
Hong Y M, Wang S Y, (2021). How is Big Data Changing Economic Research Paradigms?[J]. Management World, 37(10): 40-55.
|
洪永淼, 汪寿阳, (2024). ChatGPT与大模型将对经济学研究范式产生什么影响?[J]. 计量经济学报, 4(1): 1-25.
|
Hong Y M, Wang S Y, (2024). How Will ChatGPT and Large Models Influence the Research Paradigm in Economics?[J]. China Journal of Econometrics, 4(1): 1-25.
|
胡楠, 薛付婧, 王昊楠, (2021). 管理者短视主义影响企业长期投资吗?——基于文本分析和机器学习[J]. 管理世界, 37(5): 139-156.
|
Hu N, Xue F J, Wang H N, (2021). Does Managerial Myopia Affect Long-term Investment? Based on Text Analysis and Machine Learning[J]. Management World, 37(5): 139-156.
|
黄栋, (2024). 智能投顾发展与ChatGPT工具的应用[J]. 金融科技时代, 32(3): 75-79.
|
Huang D, (2024). Development of Intelligent Investment and Application of ChatGPT Tool[J]. FinTech Time, 32(3): 75-79.
|
姜富伟, 孟令超, 唐国豪, (2021). 媒体文本情绪与股票回报预测[J]. 经济学(季刊), 21(4): 1323-1344.
|
Jiang F W, Meng L C, Tang G H, (2021). Media Textual Sentiment and Chinese Stock Return Predictability[J]. China Economic Quarterly, 21(4): 1323-1344.
|
姜富伟, 刘雨旻, 孟令超, (2024). 大语言模型、文本情绪与金融市场[J]. 管理世界, 40(8): 42-64.
|
Jiang F W, Liu Y M, Meng L C, (2024). Large Language Model and Textual Sentiment Analysis in Chinese Stock Markets[J]. Management World, 40(8): 42-64.
|
廖理, (2021). 另类数据: 经济增长的新亮点[J]. 人民论坛·学术前沿, (6): 22-27.
|
Liao L, (2021). Alternative Data: A New Area of Economic Growth[J]. People's Forum: Academic Frontier, (6): 22-27.
|
林耀虎, 刘善存, 杨海军, (2022). 一种基于机器学习和蜡烛图的股市投资策略研究[J]. 计量经济学报, 2(1): 126-140.
|
Lin Y H, Liu S C, Yang H J, (2022). A Novel Stock Investment Strategy Using Fusion of Machine Learning Techniques and Candlestick Charting[J]. China Journal of Econometrics, 2(1): 126-140.
|
汪昌云, 武佳薇, (2015). 媒体语气、投资者情绪与IPO 定价[J]. 金融研究, (9): 174-189.
|
Wang C Y, Wu J W, (2015). Media Tone, Investor Sentiment and IPO Pricing[J]. Journal of Financial Research, (9): 174-189.
|
汪寿阳, 李明琛, 杨昆, 林文灿, 姜尚荣, 等, (2023). ChatGPT+ 金融: 八个值得关注的研究方向与问题[J]. 管理评论, 35(4): 3-11.
|
Wang S Y, Li M C, Yang K, Lin W C, Jiang S R, et al. (2023). ChatGPT + Finance: Eight Noteworthy Research Directions and Issues[J]. Management Review, 35(4): 3-11.
|
许雪晨, 田侃, (2021). 一种基于金融文本情感分析的股票指数预测新方法[J]. 数量经济技术经济研究, 38(12): 124-145.
|
Xu X C, Tian K, (2021). A Novel Financial Text Sentiment Analysis-based Approach for Stock Index Prediction[J]. Quantitative Economics and Technical Economics Research, 38(12): 124-145.
|
姚加权, 冯绪, 王赞钧, 纪荣嵘, 张维, (2021). 语调、情绪及市场影响: 基于金融情绪词典[J]. 管理科学学报, 24(5): 26-46.
|
Yao J Q, Feng X, Wang Z J, Ji R R, Zhang W, (2021). Tone, Sentiment and Market Impacts: The Construction of Chinese Sentiment Dictionary in Finance[J]. Journal of Managemenr Sciences in China, 24(5): 26-46.
|
张一帆, 林建浩, 樊嘉诚, (2023). 新闻文本大数据与消费增速实时预测——基于叙事经济学的视角[J]. 金融研究, (5): 152-169.
|
Zhang Y F, Lin J H, Fan J C, (2023). News Data and Real-Time Consumption Growth Projections: A View from Narrative Economics[J]. Journal of Financial Research, (5): 152-169.
|
Abideen Z U I, Ahmed Z, Qiu H, Zhao Y W, (2023). Do Behavioral Biases Affect Investors' Investment Decision Making? Evidence From the Pakistani Equity Market[J]. Risks, 11(6): 109.
|
Chen J, Tang G H, Zhou G F, Zhu W, (2023). ChatGPT, Stock Market Predictability and Links to the Macroeconomy[J]. Olin Business School Center for Finance & AccountingResearch Paper, (2023/18).
|
Cowles A, (1933). Can Stock Market Forecasters Forecast?[J]. Econometrica: Journal of the Econometric Society, 1(3): 309-324.
|
Grossman S J, Stiglitz J E, (1980). On the Impossibility of Informationally Efficient Markets[J]. The American Economic Review, 70(3): 393-408.
|
He K, Zhang X, Ren S, Sun J, (2016). Deep Residual Learning for Image Recognition[C]// Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition: 770-778.
|
Jiang J, Kelly B, Xiu D, (2023). (Re-) Imag (in) Ing Price Trends[J]. The Journal of Finance, 78(6): 3193-3249.
|
Kaelbling L P, Littman M L, Moore A W, (1996). Reinforcement Learning: A Survey[J]. Journal of Artificial Intelligence Research, 4: 237-285.
|
Kim A, Muhn M, Nikolaev V, (2024). Financial Statement Analysis with Large Language Models[J]. arXiv Preprint: 2407.17866.
|
Kipf T N, Welling M, (2016). Semi-supervised Classification with Graph Convolutional Networks[J]. arXiv Preprint: 1609.02907.
|
Liu H, Sferrazza C, Abbeel P, (2023a). Languages are Rewards: Hindsight Finetuning Using Human Feedback[J]. arXiv Preprint: 2302.02676.
|
Liu R, Yang R, Jia C, Zhang G, Zhou D, et al. (2023b). Training Socially Aligned Language Models in Simulated Human Society[J]. arXiv Preprint: 2305.16960. %
|
Lo A W, (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective[J]. Journal of Portfolio Management, Forthcoming.
|
Lopez-Lira A, Tang Y, (2023). Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models[J]. arXiv Preprint: 2304.07619.
|
Mohamed Rida S, Hamza E, Taher Z, (2024). From Technical Indicators to Trading Decisions: A Deep Learning Model Combining CNN and LSTM[J]. International Journal of Advanced Computer Science & Applications, 15(6): 847-855.
|
Noda A, (2021). On the Evolution of Cryptocurrency Market Efficiency[J]. Applied Economics Letters, 28(6): 433-439.
|
Obaid K, Pukthuanthong K, (2022). A Picture is Worth a Thousand Words: Measuring Investor Sentiment by Combining Machine Learning and Photos from News[J]. Journal of Financial Economics, 144(1): 273-297.
|
Omeiza D, Speakman S, Cintas C, Weldermariam K, (2019). Smooth Grad-CAM++: An Enhanced Inference Level Visualization Technique for Deep Convolutional Neural Network Models[J]. arXiv Preprint: 1908.01224.
|
Park J S, O'Brien J, Cai C J, Morris M R, Liang P, et al. (2023). Generative Agents: Interactive Simulacra of Human Behavior[C]// Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology: 1-22. %
|
Radford A, Sutskever I, Kim J W, Krueger G, Agarwal S, (2021). CLIP: Connecting Text and Images[J]. Openai.com.
|
Ribeiro C, (2002). Reinforcement Learning Agents[J]. Artificial Intelligence Review, 17: 223-250.
|
Rossi E, Chamberlain B, Frasca F, et al. (2020). Temporal graph networks for deep learning on dynamic graphs[J]. arXiv preprint arXiv: 2020.10637.
|
Sim H S, Kim H I, Ahn J J, (2019). Is Deep Learning for Image Recognition Applicable to Stock Market Prediction?[J]. Complexity, 2019(1): 4324878.
|
Taylor M E, Stone P, (2009). Transfer Learning for Reinforcement Learning Domains: A Survey[J]. Journal of Machine Learning Research, 10(7): 1633-1685.
|
Tetlock P C, (2007). Giving Content to Investor Sentiment: The Role of Media in the Stock Market[J]. The Journal of finance, 62(3): 1139-1168.
|
Tirinzoni A, Sessa A, Pirotta M, Restelli M, (2018). Importance Weighted Transfer of Samples in Reinforcement Learning[C]// International Conference on Machine Learning, PMLR 80: 4936-4945.
|
Wang Y, Zhong W, Li L, Mi F, Zeng X, et al. (2023a). Aligning Large Language Models with Human: A Survey[J]. arXiv Preprint: 2307.12966.
|
Wang Z, Zhang G, Yang K, Shi N, Zhou W, et al. (2023b). Interactive Natural Language Processing[J]. arXiv Preprint: 2305.13246.
|
Wei J, Wang X, Schuurmans D, Bosma M, Xia F, et al. (2022). Chain-of-thought Prompting Elicits Reasoning in Large Language Models[J]. Advances in Neural Information Processing Systems, 35: 24824-24837.
|
Xi Z, Chen W, Guo X, He W, Ding Y, et al. (2023). The Rise and Potential of Large Language Model Based Agents: A Survey[J]. arXiv Preprint: 2309.07864.
|
Xia Y, Wang R, Liu X, Li M, Yu T, et al. (2024). Beyond Chain-of-thought: A Survey of Chain-of-x Paradigms for Llms[J]. arXiv Preprint: 2404.15676.
|
Yang H, Zhang B, Wang N, Guo C, Zhang X, et al. (2024). Finrobot: An Open-Source AI Agent Platform for Financial Applications Using Large Language Models[J]. arXiv Preprint: 2405.14767.
|
Yang Q, Liu Y, Chen T, Tong Y, (2019). Federated Machine Learning: Concept and Applications[J]. ACM Transactions on Intelligent Systems and Technology (TIST), 10(2): 1-19.
|
Yu Y, Li H, Chen Z, Jiang Y, Li Y, et al. (2024). Finmem: A Performance-enhanced LLM Trading Agent with Layered Memory and Character Design[C]// Proceedings of the AAAI Symposium Series, 3(1): 595-597.
|
Yuan A, Coenen A, Reif E, Ippolito D, (2022). Wordcraft: Story Writing with Large Language Models[C]// Proceedings of the 27th International Conference on Intelligent User Interfaces: 841-852.
|
Zhang W, Zhao L, Xia H, Sun S, Sun J, et al. (2024). A Multimodal Foundation Agent for Financial Trading: Tool-augmented, Diversified, and Generalist[C]// Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining: 4314-4325.
|
Zhu Y, Jiang Z, Li B, (2017). Deep Reinforcement Learning for Portfolio Management[C]// Proceedings of the International Conference on Machine Learning (ICML). Sydney, Australia.
|
Zhu Z, Zhu K, (2024). Enhancement of Price Trend Trading Strategies via Image-induced Importance Weights[J]. arXiv Preprint: 2408.08483.
|
/
〈 |
|
〉 |