Image de couverture de livre

Quantifying Qualitative Insights: Leveraging LLMs to Market Predict

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Lee, Hoyoung, Choi, Youngsoo, Kwon, Yuhee
Format:	Preprint
Publié:	2024
Sujets:	Computational Finance Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Evaluating LLMs in Finance Requires Explicit Bias Consideration
par: Kong, Yaxuan, et autres
Publié: (2026)

Data-Driven, Parameterized Reduced-order Models for Predicting Distortion in Metal 3D Printing
par: Deo, Indu Kant, et autres
Publié: (2024)

Combined Effects of Fat‐Tail and Spread Forecasting on Pairs Trading: A Hybrid Model Based on Integrating VAR With GRU Models
par: Yuhee Kwon, et autres
Publié: (2025)

Leveraging Generative Adversarial Networks for Addressing Data Imbalance in Financial Market Supervision
par: Jiang, Mohan, et autres
Publié: (2024)

Thermodynamically Consistent Latent Dynamics Identification for Parametric Systems
par: He, Xiaolong, et autres
Publié: (2025)

Forecasting Future Language: Context Design for Mention Markets
par: Kim, Sumin, et autres
Publié: (2026)

Physics-informed active learning with simultaneous weak-form latent space dynamics identification
par: He, Xiaolong, et autres
Publié: (2024)

GPLaSDI: Gaussian Process-based Interpretable Latent Space Dynamics Identification through Deep Autoencoder
par: Bonneville, Christophe, et autres
Publié: (2023)

Multimodal Stock Price Prediction: A Case Study of the Russian Securities Market
par: Khubiev, Kasymkhan, et autres
Publié: (2025)

Predictive Accuracy versus Interpretability in Energy Markets: A Copula-Enhanced TVP-SVAR Analysis
par: Pokou, Fredy, et autres
Publié: (2026)

GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets
par: Xu, Zeda, et autres
Publié: (2024)

Quantifying Cryptocurrency Unpredictability: A Comprehensive Study of Complexity and Forecasting
par: Puoti, Francesco, et autres
Publié: (2025)

Mamba Meets Financial Markets: A Graph-Mamba Approach for Stock Price Prediction
par: Mehrabian, Ali, et autres
Publié: (2024)

Integrative Analysis of Financial Market Sentiment Using CNN and GRU for Risk Prediction and Alert Systems
par: Wu, You, et autres
Publié: (2024)

Nonlinear and Heavy-Tailed Predictability in Transition-Energy Financial Markets
par: Gnandi, Kpante Emmanuel, et autres
Publié: (2026)

DiffSTOCK: Probabilistic relational Stock Market Predictions using Diffusion Models
par: Daiya, Divyanshu, et autres
Publié: (2024)

Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval
par: Kandimalla, Eshwar Sai, et autres
Publié: (2026)

MANA-Net: Mitigating Aggregated Sentiment Homogenization with News Weighting for Enhanced Market Prediction
par: Wang, Mengyu, et autres
Publié: (2024)

Leveraging Multi-modal Representations to Predict Protein Melting Temperatures
par: Zhang, Daiheng, et autres
Publié: (2024)

Advancing Exchange Rate Forecasting: Leveraging Machine Learning and AI for Enhanced Accuracy in Global Financial Markets
par: Rahat, Md. Yeasin, et autres
Publié: (2025)

UAMM: Price-oracle based Automated Market Maker
par: Im, Daniel Jiwoong, et autres
Publié: (2023)

Financial Wind Tunnel: A Retrieval-Augmented Market Simulator
par: Cao, Bokai, et autres
Publié: (2025)

Leave-one-out least squares Monte Carlo algorithm for pricing Bermudan options
par: Woo, Jeechul, et autres
Publié: (2018)

Neuro-Symbolic Traders: Assessing the Wisdom of AI Crowds in Markets
par: Stillman, Namid R., et autres
Publié: (2024)

Decision by Supervised Learning with Deep Ensembles: A Practical Framework for Robust Portfolio Optimization
par: Kim, Juhyeong, et autres
Publié: (2025)

PolyBench: Benchmarking LLM Forecasting and Trading Capabilities on Live Prediction Market Data
par: Cheng, Pu, et autres
Publié: (2026)

A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting
par: Liu, Jing, et autres
Publié: (2026)

Deep Learning-Based Electricity Price Forecast for Virtual Bidding in Wholesale Electricity Market
par: Wang, Xuesong, et autres
Publié: (2024)

A Market-Rule-Informed Neural Network for Efficient Imbalance Electricity Price Forecasting
par: Yu, Runyao, et autres
Publié: (2026)

Emoji Driven Crypto Assets Market Reactions
par: Zuo, Xiaorui, et autres
Publié: (2024)

Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns
par: Zhu, Haoren, et autres
Publié: (2024)

Leveraging Time Series Categorization and Temporal Fusion Transformers to Improve Cryptocurrency Price Forecasting
par: Peik, Arash, et autres
Publié: (2024)

Stock Price Prediction and Traditional Models: An Approach to Achieve Short-, Medium- and Long-Term Goals
par: Alamu, Opeyemi Sheu, et autres
Publié: (2024)

MCI-GRU: Stock Prediction Model Based on Multi-Head Cross-Attention and Improved GRU
par: Zhu, Peng, et autres
Publié: (2024)

Dynamic Graph Representation with Contrastive Learning for Financial Market Prediction: Integrating Temporal Evolution and Static Relations
par: Pei, Yunhua, et autres
Publié: (2024)

Exploiting Supply Chain Interdependencies for Stock Return Prediction: A Full-State Graph Convolutional LSTM
par: Liu, Chang
Publié: (2023)

Leveraging Cardiovascular Simulations for In-Vivo Prediction of Cardiac Biomarkers
par: Manduchi, Laura, et autres
Publié: (2024)

Beyond the Black Box: Interpretability of LLMs in Finance
par: Tatsat, Hariom, et autres
Publié: (2025)

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

Enhancing Regime Shift Detection Using Unstructured Data: A Study on the Treasury Market
par: Yi, Mingxuan, et autres
Publié: (2026)