Cover Image

Reinforcement Learning for Stock Transactions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhou, Ziyi, Stern, Nicholas, Laasri, Julien
Format:	Preprint
Published:	2025
Subjects:	Machine Learning 68T05 I.2.6
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RVI-SAC: Average Reward Off-Policy Deep Reinforcement Learning
by: Hisaki, Yukinari, et al.
Published: (2024)

Hard Samples, Bad Labels: Robust Loss Functions That Know When to Back Off
by: Pellegrino, Nicholas, et al.
Published: (2025)

Effects of Initialization Biases on Deep Neural Network Training Dynamics
by: Pellegrino, Nicholas, et al.
Published: (2025)

Transactional Attention: Semantic Sponsorship for KV-Cache Retention
by: Basu, Abhinaba
Published: (2026)

Data-Driven Preference Sampling for Pareto Front Learning
by: Ye, Rongguang, et al.
Published: (2024)

Feature-aware Modulation for Learning from Temporal Tabular Data
by: Cai, Hao-Run, et al.
Published: (2025)

Fine-Tuning Regimes Define Distinct Continual Learning Problems
by: Iordache, Paul-Tiberiu, et al.
Published: (2026)

Temporal Taskification in Streaming Continual Learning: A Source of Evaluation Instability
by: Filat, Nicolae, et al.
Published: (2026)

Contrastive Mutual Information Learning: Toward Robust Representations without Positive-Pair Augmentations
by: Livne, Micha
Published: (2025)

Contrastive MIM: A Contrastive Mutual Information Framework for Unified Generative and Discriminative Representation Learning
by: Livne, Micha
Published: (2025)

Your Data, My Model: Learning Who Really Helps in Federated Learning
by: Abdurakhmanova, Shamsiiat, et al.
Published: (2024)

Understanding the Limits of Deep Tabular Methods with Temporal Shift
by: Cai, Hao-Run, et al.
Published: (2025)

Adaptive Weighting in Knowledge Distillation: An Axiomatic Framework for Multi-Scale Teacher Ensemble Optimization
by: Flouro, Aaron R., et al.
Published: (2026)

When Redundancy Matters: Machine Teaching of Representations
by: Ferri, Cèsar, et al.
Published: (2024)

Data structure > labels? Unsupervised heuristics for SVM hyperparameter estimation
by: Cholewa, Michał, et al.
Published: (2021)

Generative Pretrained Embedding and Hierarchical Irregular Time Series Representation for Daily Living Activity Recognition
by: Bouchabou, Damien, et al.
Published: (2024)

Multi-Teacher Ensemble Distillation: A Mathematical Framework for Probability-Domain Knowledge Aggregation
by: Flouro, Aaron R., et al.
Published: (2026)

Grammar-based evolutionary approach for automated workflow composition with domain-specific operators and ensemble diversity
by: Barbudo, Rafael, et al.
Published: (2024)

Adaptive Exploration for Latent-State Bandits
by: Jin, Jikai, et al.
Published: (2026)

Nonlinear Data Integration via Kernel Methods for Data Collaboration Analysis
by: Suetake, Yamato, et al.
Published: (2026)

Adaptive Bernstein Change Detector for High-Dimensional Data Streams
by: Heyden, Marco, et al.
Published: (2023)

Quantifying First-Order Markov Violations in Noisy Reinforcement Learning: A Causal Discovery Approach
by: Mysore, Naveen
Published: (2025)

An Improved Adaptive PID Optimizer with Enhanced Convergence and Stability for Deep Learning
by: Saini, Saurabh, et al.
Published: (2026)

MAcPNN: Mutual Assisted Learning on Data Streams with Temporal Dependence
by: Giannini, Federico, et al.
Published: (2026)

Dynamical Priors as a Training Objective in Reinforcement Learning
by: Subaharan, Sukesh
Published: (2026)

A Comparison Between Decision Transformers and Traditional Offline Reinforcement Learning Algorithms
by: Caunhye, Ali Murtaza, et al.
Published: (2025)

MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures
by: Zamaraeva, Elena, et al.
Published: (2025)

Human-Aligned Skill Discovery: Balancing Behaviour Exploration and Alignment
by: Hussonnois, Maxence, et al.
Published: (2025)

SafeRL-Lite: A Lightweight, Explainable, and Constrained Reinforcement Learning Library
by: Mishra, Satyam, et al.
Published: (2025)

Correction and Corruption: A Two-Rate View of Error Flow in LLM Protocols
by: Reitich, Fernando
Published: (2026)

Distinguished In Uniform: Self Attention Vs. Virtual Nodes
by: Rosenbluth, Eran, et al.
Published: (2024)

Federated Learning based on Self-Evolving Gaussian Clustering
by: Ožbot, Miha, et al.
Published: (2025)

Step-E: A Differentiable Data Cleaning Framework for Robust Learning with Noisy Labels
by: Du, Wenzhang
Published: (2025)

Evolving machine learning workflows through interactive AutoML
by: Barbudo, Rafael, et al.
Published: (2024)

Territory Paint Wars: Diagnosing and Mitigating Failure Modes in Competitive Multi-Agent PPO
by: Singh, Diyansha
Published: (2026)

Client-Conditional Federated Learning via Local Training Data Statistics
by: Brännvall, Rickard
Published: (2026)

Multi-Scale Graph Learning for Anti-Sparse Downscaling
by: Fan, Yingda, et al.
Published: (2025)

Memory-efficient Continual Learning with Prototypical Exemplar Condensation
by: Nguyen, Minh-Duong, et al.
Published: (2026)

A Practical Guide to Streaming Continual Learning
by: Cossu, Andrea, et al.
Published: (2026)

Don't Look Back in Anger: MAGIC Net for Streaming Continual Learning with Temporal Dependence
by: Giannini, Federico, et al.
Published: (2026)