Copertina

Modeling Market States with Clustering and State Machines

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Oliva, Christian, Tinjala, Silviu Gabriel
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computational Engineering, Finance, and Science Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Multi-objective Portfolio Optimization Via Gradient Descent
di: Oliva, Christian, et al.
Pubblicazione: (2025)

UAMM: Price-oracle based Automated Market Maker
di: Im, Daniel Jiwoong, et al.
Pubblicazione: (2023)

Financial Wind Tunnel: A Retrieval-Augmented Market Simulator
di: Cao, Bokai, et al.
Pubblicazione: (2025)

Realistic Market Impact Modeling for Reinforcement Learning Trading Environments
di: Abbade, Lucas Riera, et al.
Pubblicazione: (2026)

Studying the Soupability of Documents in State Space Models
di: Jafari, Yasaman, et al.
Pubblicazione: (2025)

A Cutting Mechanics-based Machine Learning Modeling Method to Discover Governing Equations of Machining Dynamics
di: Ren, Alisa, et al.
Pubblicazione: (2025)

DiffSTOCK: Probabilistic relational Stock Market Predictions using Diffusion Models
di: Daiya, Divyanshu, et al.
Pubblicazione: (2024)

Constrained Sensing and Reliable State Estimation with Shallow Recurrent Decoders on a TRIGA Mark II Reactor
di: Riva, Stefano, et al.
Pubblicazione: (2025)

Multi-objective Combinatorial Methodology for Nuclear Reactor Site Assessment: A Case Study for the United States
di: Erdem, Omer, et al.
Pubblicazione: (2024)

Prediction of Steady-State Flow through Porous Media Using Machine Learning Models
di: Wang, Jinhong, et al.
Pubblicazione: (2026)

Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval
di: Kandimalla, Eshwar Sai, et al.
Pubblicazione: (2026)

A Multi-Layer Machine Learning and Econometric Pipeline for Forecasting Market Risk: Evidence from Cryptoasset Liquidity Spillovers
di: Qiu, Yimeng, et al.
Pubblicazione: (2025)

ABM-UDE: Developing Surrogates for Epidemic Agent-Based Models via Scientific Machine Learning
di: Murgai, Sharv, et al.
Pubblicazione: (2026)

Neural Operators Can Discover Functional Clusters
di: Li, Yicen, et al.
Pubblicazione: (2026)

Gaussian Process Surrogate Models for Efficient Estimation of Structural Response Distributions and Order Statistics
di: Flovik, Vegard, et al.
Pubblicazione: (2025)

A Machine Learning Approach For Bitcoin Forecasting
di: Sossi-Rojas, Stefano, et al.
Pubblicazione: (2025)

Deep Learning Enhanced Multi-Day Turnover Quantitative Trading Algorithm for Chinese A-Share Market
di: Du, Yimin
Pubblicazione: (2025)

Applications of Machine Learning to Optimizing Polyolefin Manufacturing
di: Sharma, Niket, et al.
Pubblicazione: (2024)

Machine Learning based Prediction of Ditching Loads
di: Schwarz, Henning, et al.
Pubblicazione: (2024)

Large Language Model Scaling Laws for Neural Quantum States in Quantum Chemistry
di: Knitter, Oliver, et al.
Pubblicazione: (2025)

CryptoMamba: Leveraging State Space Models for Accurate Bitcoin Price Prediction
di: Sepehri, Mohammad Shahab, et al.
Pubblicazione: (2025)

Multimodal Deep Learning of Word-of-Mouth Text and Demographics to Predict Customer Rating: Handling Consumer Heterogeneity in Marketing
di: Niimi, Junichiro
Pubblicazione: (2024)

Physics-Informed Machine Learning for Smart Additive Manufacturing
di: Sharma, Rahul, et al.
Pubblicazione: (2024)

Machine Learning-Assisted Discovery of Flow Reactor Designs
di: Savage, Tom, et al.
Pubblicazione: (2023)

Physics-Informed Machine Learning for Grade Prediction in Froth Flotation
di: Nasiri, Mahdi, et al.
Pubblicazione: (2024)

Variational Deep Survival Machines: Survival Regression with Censored Outcomes
di: Wang, Qinxin, et al.
Pubblicazione: (2024)

Applied Machine Learning to Anomaly Detection in Enterprise Purchase Processes
di: Herreros-Martínez, A., et al.
Pubblicazione: (2024)

Using Sentiment and Technical Analysis to Predict Bitcoin with Machine Learning
di: Carosia, Arthur Emanuel de Oliveira
Pubblicazione: (2024)

Parametric Nonlinear Volterra Series via Machine Learning: Transonic Aerodynamics
di: Immordino, Gabriele, et al.
Pubblicazione: (2024)

MANA-Net: Mitigating Aggregated Sentiment Homogenization with News Weighting for Enhanced Market Prediction
di: Wang, Mengyu, et al.
Pubblicazione: (2024)

Deep Clustering based Boundary-Decoder Net for Inter and Intra Layer Stress Prediction of Heterogeneous Integrated IC Chip
di: Lim, Kart Leong, et al.
Pubblicazione: (2026)

A User-Tunable Machine Learning Framework for Step-Wise Synthesis Planning
di: Prakash, Shivesh, et al.
Pubblicazione: (2025)

Addressing the Current Challenges of Quantum Machine Learning through Multi-Chip Ensembles
di: Park, Junghoon Justin, et al.
Pubblicazione: (2025)

Physics-Enhanced Machine Learning: a position paper for dynamical systems investigations
di: Cicirello, Alice
Pubblicazione: (2024)

ML-Based Bidding Price Prediction for Pay-As-Bid Ancillary Services Markets: A Use Case in the German Control Reserve Market
di: Bezold, Vincent, et al.
Pubblicazione: (2025)

Toward Developing Machine-Learning-Aided Tools for the Thermomechanical Monitoring of Nuclear Reactor Components
di: Machado, Luiz Aldeia, et al.
Pubblicazione: (2025)

ML4PhySim : Machine Learning for Physical Simulations Challenge (The airfoil design)
di: Yagoubi, Mouadh, et al.
Pubblicazione: (2024)

Physics-Informed Machine Learning Towards A Real-Time Spacecraft Thermal Simulator
di: Oddiraju, Manaswin, et al.
Pubblicazione: (2024)

Towards Efficient Parametric State Estimation in Circulating Fuel Reactors with Shallow Recurrent Decoder Networks
di: Riva, Stefano, et al.
Pubblicazione: (2025)

Free-form Grid Structure Form Finding based on Machine Learning and Multi-objective Optimisation
di: Meng, Yiping, et al.
Pubblicazione: (2024)