NEAT Algorithm-based Stock Trading Strategy with Multiple Technical Indicators Resonance
Fuente:
arXiv
Saved in:
| Main Author: | Huang, Li-Chun |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Informer in Algorithmic Investment Strategies on High Frequency Bitcoin Data
by: Stefaniuk, Filip, et al.
Published: (2025)
by: Stefaniuk, Filip, et al.
Published: (2025)
Spiking Neural Network for Cross-Market Portfolio Optimization in Financial Markets: A Neuromorphic Computing Approach
by: Mohan, Amarendra, et al.
Published: (2025)
by: Mohan, Amarendra, et al.
Published: (2025)
Deep Reinforcement Learning Framework for Diversified Portfolio Management Across Global Equity Markets
by: Kashif, Kamil, et al.
Published: (2026)
by: Kashif, Kamil, et al.
Published: (2026)
Stochastic Volatility Modelling with LSTM Networks: A Hybrid Approach for S&P 500 Index Volatility Forecasting
by: Perekhodko, Anna, et al.
Published: (2025)
by: Perekhodko, Anna, et al.
Published: (2025)
AlphaSharpe: LLM-Driven Discovery of Robust Risk-Adjusted Metrics
by: Yuksel, Kamer Ali, et al.
Published: (2025)
by: Yuksel, Kamer Ali, et al.
Published: (2025)
Technical Indicator Networks (TINs): An Interpretable Neural Architecture Modernizing Classic al Technical Analysis for Adaptive Algorithmic Trading
by: Lu, Longfei
Published: (2025)
by: Lu, Longfei
Published: (2025)
QTMRL: An Agent for Quantitative Trading Decision-Making Based on Multi-Indicator Guided Reinforcement Learning
by: Pan, Jingfeng, et al.
Published: (2025)
by: Pan, Jingfeng, et al.
Published: (2025)
Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy
by: Yang, Hongyang, et al.
Published: (2025)
by: Yang, Hongyang, et al.
Published: (2025)
Directly Learning Stock Trading Strategies Through Profit Guided Loss Functions
by: Kar, Devroop, et al.
Published: (2025)
by: Kar, Devroop, et al.
Published: (2025)
Exploring Sectoral Profitability in the Indian Stock Market Using Deep Learning
by: Sen, Jaydip, et al.
Published: (2024)
by: Sen, Jaydip, et al.
Published: (2024)
Fine-Tuning Large Language Models for Stock Return Prediction Using Newsflow
by: Guo, Tian, et al.
Published: (2024)
by: Guo, Tian, et al.
Published: (2024)
On Evaluating Loss Functions for Stock Ranking: An Empirical Analysis With Transformer Model
by: Kwiatkowski, Jan, et al.
Published: (2025)
by: Kwiatkowski, Jan, et al.
Published: (2025)
Increase Alpha: Performance and Risk of an AI-Driven Trading Framework
by: Ghatak, Sid, et al.
Published: (2025)
by: Ghatak, Sid, et al.
Published: (2025)
NEAT and HyperNEAT based Design for Soft Actuator Controllers
by: Alcaraz-Herrera, Hugo, et al.
Published: (2025)
by: Alcaraz-Herrera, Hugo, et al.
Published: (2025)
Large-scale portfolio optimization with variational neural annealing
by: Ranabhat, Nishan, et al.
Published: (2025)
by: Ranabhat, Nishan, et al.
Published: (2025)
Data-Driven Merton's Strategies via Policy Randomization
by: Dai, Min, et al.
Published: (2023)
by: Dai, Min, et al.
Published: (2023)
A Parameter-free Adaptive Resonance Theory-based Topological Clustering Algorithm Capable of Continual Learning
by: Masuyama, Naoki, et al.
Published: (2023)
by: Masuyama, Naoki, et al.
Published: (2023)
A Distillation-based Future-aware Graph Neural Network for Stock Trend Prediction
by: Liu, Zhipeng, et al.
Published: (2025)
by: Liu, Zhipeng, et al.
Published: (2025)
Neuroevolution Neural Architecture Search for Evolving RNNs in Stock Return Prediction and Portfolio Trading
by: Lyu, Zimeng, et al.
Published: (2024)
by: Lyu, Zimeng, et al.
Published: (2024)
Covariance-Aware Simplex Projection for Cardinality-Constrained Portfolio Optimization
by: Iliopoulos, Nikolaos
Published: (2025)
by: Iliopoulos, Nikolaos
Published: (2025)
Uniform Pessimistic Risk and its Optimal Portfolio
by: Hong, Sungchul, et al.
Published: (2023)
by: Hong, Sungchul, et al.
Published: (2023)
PropNEAT -- Efficient GPU-Compatible Backpropagation over NeuroEvolutionary Augmenting Topology Networks
by: Merry, Michael, et al.
Published: (2024)
by: Merry, Michael, et al.
Published: (2024)
Towards Initialization-Agnostic Clustering with Iterative Adaptive Resonance Theory
by: Qu, Xiaozheng, et al.
Published: (2025)
by: Qu, Xiaozheng, et al.
Published: (2025)
Deep Reinforcement Learning for Long-Short Portfolio Optimization
by: Huang, Gang, et al.
Published: (2020)
by: Huang, Gang, et al.
Published: (2020)
Ensembling Portfolio Strategies for Long-Term Investments: A Distribution-Free Preference Framework for Decision-Making and Algorithms
by: Lam, Duy Khanh
Published: (2024)
by: Lam, Duy Khanh
Published: (2024)
Solving dynamic portfolio selection problems via score-based diffusion models
by: Aghapour, Ahmad, et al.
Published: (2025)
by: Aghapour, Ahmad, et al.
Published: (2025)
Combining Transformer based Deep Reinforcement Learning with Black-Litterman Model for Portfolio Optimization
by: Sun, Ruoyu, et al.
Published: (2024)
by: Sun, Ruoyu, et al.
Published: (2024)
A Deep Reinforcement Learning Framework For Financial Portfolio Management
by: Li, Jinyang
Published: (2024)
by: Li, Jinyang
Published: (2024)
AI-Powered Energy Algorithmic Trading: Integrating Hidden Markov Models with Neural Networks
by: Monteiro, Tiago
Published: (2024)
by: Monteiro, Tiago
Published: (2024)
DGDNN: Decoupled Graph Diffusion Neural Network for Stock Movement Prediction
by: You, Zinuo, et al.
Published: (2024)
by: You, Zinuo, et al.
Published: (2024)
RVRAE: A Dynamic Factor Model Based on Variational Recurrent Autoencoder for Stock Returns Prediction
by: Wang, Yilun, et al.
Published: (2024)
by: Wang, Yilun, et al.
Published: (2024)
When Alpha Breaks: Two-Level Uncertainty for Safe Deployment of Cross-Sectional Stock Rankers
by: Sanderink, Ursina
Published: (2026)
by: Sanderink, Ursina
Published: (2026)
Developing A Multi-Agent and Self-Adaptive Framework with Deep Reinforcement Learning for Dynamic Portfolio Risk Management
by: Li, Zhenglong, et al.
Published: (2024)
by: Li, Zhenglong, et al.
Published: (2024)
PAIR: A Novel Large Language Model-Guided Selection Strategy for Evolutionary Algorithms
by: Ali, Shady, et al.
Published: (2025)
by: Ali, Shady, et al.
Published: (2025)
Can Blindfolded LLMs Still Trade? An Anonymization-First Framework for Portfolio Optimization
by: Jeon, Joohyoung, et al.
Published: (2026)
by: Jeon, Joohyoung, et al.
Published: (2026)
Reinforcement Learning with Maskable Stock Representation for Portfolio Management in Customizable Stock Pools
by: Zhang, Wentao, et al.
Published: (2023)
by: Zhang, Wentao, et al.
Published: (2023)
Balanced Resonate-and-Fire Neurons
by: Higuchi, Saya, et al.
Published: (2024)
by: Higuchi, Saya, et al.
Published: (2024)
Automate Strategy Finding with LLM in Quant Investment
by: Kou, Zhizhuo, et al.
Published: (2024)
by: Kou, Zhizhuo, et al.
Published: (2024)
Hopfield Networks for Asset Allocation
by: Nicolini, Carlo, et al.
Published: (2024)
by: Nicolini, Carlo, et al.
Published: (2024)
Application of Deep Learning for Factor Timing in Asset Management
by: Panda, Prabhu Prasad, et al.
Published: (2024)
by: Panda, Prabhu Prasad, et al.
Published: (2024)
Similar Items
-
Informer in Algorithmic Investment Strategies on High Frequency Bitcoin Data
by: Stefaniuk, Filip, et al.
Published: (2025) -
Spiking Neural Network for Cross-Market Portfolio Optimization in Financial Markets: A Neuromorphic Computing Approach
by: Mohan, Amarendra, et al.
Published: (2025) -
Deep Reinforcement Learning Framework for Diversified Portfolio Management Across Global Equity Markets
by: Kashif, Kamil, et al.
Published: (2026) -
Stochastic Volatility Modelling with LSTM Networks: A Hybrid Approach for S&P 500 Index Volatility Forecasting
by: Perekhodko, Anna, et al.
Published: (2025) -
AlphaSharpe: LLM-Driven Discovery of Robust Risk-Adjusted Metrics
by: Yuksel, Kamer Ali, et al.
Published: (2025)