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Home Market Research Investing

Self-Driving Portfolio Promise and Pitfalls

by TheAdviserMagazine
2 weeks ago
in Investing
Reading Time: 2 mins read
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Self-Driving Portfolio Promise and Pitfalls
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Ang, A., Azimbayev, N., & Kim, A. (2026). The Self-Driving Portfolio: Agentic Architecture for Institutional Asset Management. arXiv, abs/2604.02279.

Bisconti, P., Galisai, M., Pierucci, F., Bracale, M., & Prandi, M. (2025). Beyond Single-Agent Safety: A Taxonomy of Risks in LLM-to-LLM Interactions. ArXiv, abs/2512.02682.

Cemri, M., et al. (2025). Why Do Multi-Agent LLM Systems Fail? ArXiv, abs/2503.13657.

Darwish, M., Hassanien, E., & Eissa, A. (2025). Stock Market Forecasting: From Traditional Predictive Models to Large Language Models. Computational Economics.

Eswaran, A., et al. (2026). CryptoAnalystBench: Failures in Multi-Tool Long-Form LLM Analysis. ArXiv, abs/2602.11304.

Hajaghaie, A., & Thulasiram, R. (2025). Leveraging Large Language Models and Retrieval-Augmented Generation for Enhanced Multi-Asset Portfolio Construction. IEEE CiFer 2025.

He, C., et al. (2025). Hierarchical AI Multi-Agent Fundamental Investing: Evidence from China’s A-Share Market. ArXiv, abs/2510.21147.

Heng, R., et al. (2025). Leveraging LLMs for Top-Down Sector Allocation in Automated Trading. ArXiv, abs/2503.09647.

Kim, S., & Lee, K. (2025). Multi-Asset Multi-Agent Reinforcement Learning for Portfolio Management. IEEE Access, 13.

Lee, J., Kim, R., Yi, S., & Kang, J. (2020). MAPS: Multi-Agent Reinforcement Learning-based Portfolio Management System. IJCAI 2020.

Raza, S., et al. (2025). TRiSM for Agentic AI. ArXiv, abs/2506.04133.

Reid, A., O’Callaghan, S., Carroll, L., & Caetano, T. (2025). Risk Analysis Techniques for Governed LLM-based Multi-Agent Systems. ArXiv, abs/2508.05687.

Roig, J. (2025). How Do LLMs Fail In Agentic Scenarios? ArXiv, abs/2512.07497.

Tian, C., & Zhang, Y. (2024). Collaboration Dynamics and Reliability Challenges of Multi-Agent LLM Systems.

Tong, X., Wei, L., & Yan, Z. (2026). Reliability Challenges of LLM Agents. Science and Technology of Engineering, Chemistry and Environmental Protection.

Vinay, V. (2025). Failure Modes in LLM Systems. ArXiv, abs/2511.19933.

Voronina, A., et al. (2025). Generative AI-enhanced Sector-based Investment Portfolio Construction. ArXiv, abs/2512.24526.

Vuković, D., Dekpo-Adza, S., & Matović, S. (2025). AI integration in financial services: a systematic review. Humanities and Social Sciences Communications, 12.

Wang, B. (2025). Empirical Evaluation of Large Language Models for Asset-Return Prediction.

Winder, P., Hildebrand, C., & Hartmann, J. (2025). Biased echoes: Large language models reinforce investment biases. PLOS One, 20.

Zhu, K., et al. (2025). Where LLM Agents Fail and How They can Learn From Failures. ArXiv, abs/2509.25370.



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