Cover Image

A Risk-Aware Reinforcement Learning Reward for Financial Trading

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Srivastava, Uditansh, Aryan, Shivam, Singh, Shaurya
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

News-Aware Direct Reinforcement Trading for Financial Markets
by: Lan, Qing-Yu, et al.
Published: (2025)

Risk-Averse Total-Reward Reinforcement Learning
by: Su, Xihong, et al.
Published: (2025)

Reward-Aware Proto-Representations in Reinforcement Learning
by: Tse, Hon Tik, et al.
Published: (2025)

FineFT: Efficient and Risk-Aware Ensemble Reinforcement Learning for Futures Trading
by: Qin, Molei, et al.
Published: (2025)

Spatiotemporal Wildfire Prediction and Reinforcement Learning for Helitack Suppression
by: Mathur, Shaurya, et al.
Published: (2026)

Binary Reward Labeling: Bridging Offline Preference and Reward-Based Reinforcement Learning
by: Xu, Yinglun, et al.
Published: (2024)

Dissociating Decodability and Causal Use in Bracket-Sequence Transformers
by: Sharma, Aryan, et al.
Published: (2026)

Autotelic Reinforcement Learning: Exploring Intrinsic Motivations for Skill Acquisition in Open-Ended Environments
by: Srivastava, Prakhar, et al.
Published: (2025)

Provably Adaptive Average Reward Reinforcement Learning for Metric Spaces
by: Kar, Avik, et al.
Published: (2024)

Burning RED: Unlocking Subtask-Driven Reinforcement Learning and Risk-Awareness in Average-Reward Markov Decision Processes
by: Rojas, Juan Sebastian, et al.
Published: (2024)

Policy Zooming: Adaptive Discretization-based Infinite-Horizon Average-Reward Reinforcement Learning
by: Kar, Avik, et al.
Published: (2024)

Decomposable Reward Modeling and Realistic Environment Design for Reinforcement Learning-Based Forex Trading
by: Saidd, Nabeel Ahmad
Published: (2026)

A Theory of Diversity for Random Matrices with Applications to In-Context Learning of Schrödinger Equations
by: Cole, Frank, et al.
Published: (2026)

Reward-Conditioned Reinforcement Learning
by: Nauman, Michal, et al.
Published: (2026)

Tackling Length Inflation Without Trade-offs: Group Relative Reward Rescaling for Reinforcement Learning
by: Li, Zichao, et al.
Published: (2026)

Sample-Efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards
by: Metcalf, Katherine, et al.
Published: (2024)

REBEL: Reward Regularization-Based Approach for Robotic Reinforcement Learning from Human Feedback
by: Chakraborty, Souradip, et al.
Published: (2023)

To Distill or Decide? Understanding the Algorithmic Trade-off in Partially Observable Reinforcement Learning
by: Song, Yuda, et al.
Published: (2025)

TACO-RL: Task Aware Prompt Compression Optimization with Reinforcement Learning
by: Shandilya, Shivam, et al.
Published: (2024)

Reward Design for Reinforcement Learning Agents
by: Devidze, Rati
Published: (2025)

Reinforcement Learning from Bagged Reward
by: Tang, Yuting, et al.
Published: (2024)

The Value of Reward Lookahead in Reinforcement Learning
by: Merlis, Nadav, et al.
Published: (2024)

Informativeness of Reward Functions in Reinforcement Learning
by: Devidze, Rati, et al.
Published: (2024)

To the Max: Reinventing Reward in Reinforcement Learning
by: Veviurko, Grigorii, et al.
Published: (2024)

Focal Reward: Balanced Reinforcement Learning under Rubric-Based Rewards
by: Huang, Yu, et al.
Published: (2026)

The Distributional Reward Critic Framework for Reinforcement Learning Under Perturbed Rewards
by: Chen, Xi, et al.
Published: (2024)

Correlated Proxies: A New Definition and Improved Mitigation for Reward Hacking
by: Laidlaw, Cassidy, et al.
Published: (2024)

Trading-R1: Financial Trading with LLM Reasoning via Reinforcement Learning
by: Xiao, Yijia, et al.
Published: (2025)

Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement Learning
by: Schneider, Lukas, et al.
Published: (2023)

SPARK: Stepwise Process-Aware Rewards for Reference-Free Reinforcement Learning
by: Rahman, Salman, et al.
Published: (2025)

Code as Reward: Empowering Reinforcement Learning with VLMs
by: Venuto, David, et al.
Published: (2024)

Effective Reward Specification in Deep Reinforcement Learning
by: Roy, Julien
Published: (2024)

Reward-Preserving Attacks For Robust Reinforcement Learning
by: Schott, Lucas, et al.
Published: (2026)

RDA: Reward Design Agent for Reinforcement Learning
by: Lee, Hojoon, et al.
Published: (2026)

Binary Rewards and Reinforcement Learning: Fundamental Challenges
by: Dymetman, Marc
Published: (2026)

Reward-Zero: Language Embedding Driven Implicit Reward Mechanisms for Reinforcement Learning
by: Zhang, Heng, et al.
Published: (2026)

Evolving Robustness--Exploration Trade-off in Online Reinforcement Learning via Quantile Bayesian Risk MDPs
by: Song, Meichen, et al.
Published: (2026)

LGR2: Language Guided Reward Relabeling for Accelerating Hierarchical Reinforcement Learning
by: Singh, Utsav, et al.
Published: (2024)

On the Generalization of SFT: A Reinforcement Learning Perspective with Reward Rectification
by: Wu, Yongliang, et al.
Published: (2025)

Isometric Neural Machine Translation using Phoneme Count Ratio Reward-based Reinforcement Learning
by: Mhaskar, Shivam Ratnakant, et al.
Published: (2024)