arXiv AI July 1, 2026 By Ramin Pishehvar

A Three-Phase Foundation Model for Tax-Aware Personalized Portfolio Management

arXiv:2606. 30997v1 Announce Type: new Abstract: We present a three-phase deep reinforcement learning system for personalized portfolio management that addresses three limitations shared by all prior financial RL work: 1) ticker lock-in, 2) monolithic objectives , and 3) static user models.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Aug 7

An Emerging Retail Portfolio Management Application: Personalized, Tax-Aware Reinforcement Learning with Natural Language Goals

arXiv:2608. 05255v1 Announce Type: cross Abstract: Retail investors lack access to the kind of personalized, tax-aware portfolio management that institutional clients take for granted -- existing robo-advisors use static, rule-based allocation, and institutional-grade systems require account minimums and technology stacks unavailable to individual investors.

By Ramin Pishehvar

reinforcement-learning fine-tuning

arXiv AI

Jun 2

Regime-Adaptive Continual Learning for Portfolio Management

arXiv:2606. 00143v1 Announce Type: cross Abstract: Financial markets are inherently non-stationary, exhibiting frequent regime shifts and structural changes that render traditional Portfolio Management (PM) approaches ineffective.

By Chaofan Pan, Lingfei Ren, Linbo Xiong, Yonghao Li, Wei Wei, Xin Yang

agents fine-tuning

arXiv AI

Jun 9

GIFT: LLM-Guided State-Reward Interface for Financial Reinforcement Learning

arXiv:2606. 08450v1 Announce Type: new Abstract: Financial portfolio trading is naturally formulated as a reinforcement learning problem, where an agent sequentially rebalances assets under changing market conditions to balance return, risk, and transaction costs.

By Yanyan Wu, Boyi Zhang, Yanlin Liu, Xinyu Fang, Jining Luan, Meiqi Zhang, Jiacheng Liu, Hao Zeng, Dexu Yu, Chang Liu, Hanwen Du, Yongxin Ni, Youhua Li

llms agents reinforcement-learning

arXiv Machine Learning

1d ago

Self-Supervised Auxiliary Task Discovery for Stable Reinforcement Learning in Stock Trading

arXiv:2608. 15841v1 Announce Type: new Abstract: Reinforcement learning has gained increasing attention as a data-driven approach for stock trading.

By Arishi Orra, Himanshu Choudhary, Manoj Thakur

reinforcement-learning

arXiv Machine Learning

Jul 20

CLaC@FinMMEval 2026 Task 3: Sentiment-Augmented Deep Reinforcement Learning for Active Trading -- An Alpha-Reward Approach

arXiv:2607. 16028v1 Announce Type: new Abstract: This paper presents our system for Task 3 of the CLEF 2026 FinMMEval Lab, which requires daily long, flat, or short trading decisions for Bitcoin (BTC) and Tesla (TSLA) using news and historical market data.

By Andrei Neagu, Eeham Khan, Leila Kosseim

llms agents reinforcement-learning

arXiv AI

Jun 10

A Unified Multi-Modal Framework for Intelligent Financial Systems: Integrating Reinforcement Learning, High-Frequency Trading, and Game-Theoretic Approaches with Cross-Modal Sentiment Analysis

arXiv:2606. 10412v1 Announce Type: new Abstract: The rapid evolution of financial technology demands sophisticated artificial intelligence systems capable of handling diverse challenges across multiple domains simultaneously.

By Fanrong Liu, Zhang Yuwei, Mingni Luo

llms rag nlp reinforcement-learning multimodal benchmarks

Related stories

An Emerging Retail Portfolio Management Application: Personalized, Tax-Aware Reinforcement Learning with Natural Language Goals

Regime-Adaptive Continual Learning for Portfolio Management

GIFT: LLM-Guided State-Reward Interface for Financial Reinforcement Learning

Self-Supervised Auxiliary Task Discovery for Stable Reinforcement Learning in Stock Trading

CLaC@FinMMEval 2026 Task 3: Sentiment-Augmented Deep Reinforcement Learning for Active Trading -- An Alpha-Reward Approach

A Unified Multi-Modal Framework for Intelligent Financial Systems: Integrating Reinforcement Learning, High-Frequency Trading, and Game-Theoretic Approaches with Cross-Modal Sentiment Analysis