Copertina

Can We Reliably Predict the Fed's Next Move? A Multi-Modal Approach to U.S. Monetary Policy Forecasting

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Jingyi, Fiona Xiao, Liu, Lili
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Portfolio Management Machine Learning Computational Finance
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Data-Driven Merton's Strategies via Policy Randomization
di: Dai, Min, et al.
Pubblicazione: (2023)

Dependency Network-Based Portfolio Design with Forecasting and VaR Constraints
di: Lin, Zihan, et al.
Pubblicazione: (2025)

Fine-Tuning Large Language Models for Stock Return Prediction Using Newsflow
di: Guo, Tian, et al.
Pubblicazione: (2024)

QTMRL: An Agent for Quantitative Trading Decision-Making Based on Multi-Indicator Guided Reinforcement Learning
di: Pan, Jingfeng, et al.
Pubblicazione: (2025)

Stochastic Dominance Constrained Optimization with S-shaped Utilities: Poor-Performance-Region Algorithm and Neural Network
di: Hu, Zeyun, et al.
Pubblicazione: (2025)

Hopfield Networks for Asset Allocation
di: Nicolini, Carlo, et al.
Pubblicazione: (2024)

Deep Reinforcement Learning for Long-Short Portfolio Optimization
di: Huang, Gang, et al.
Pubblicazione: (2020)

Application of Deep Learning for Factor Timing in Asset Management
di: Panda, Prabhu Prasad, et al.
Pubblicazione: (2024)

Explainable Regime Aware Investing
di: Boukardagha, Amine
Pubblicazione: (2026)

Aligning Language Models with Investor and Market Behavior for Financial Recommendations
di: Spadea, Fernando, et al.
Pubblicazione: (2025)

Exploring Sectoral Profitability in the Indian Stock Market Using Deep Learning
di: Sen, Jaydip, et al.
Pubblicazione: (2024)

A Deep Reinforcement Learning Framework For Financial Portfolio Management
di: Li, Jinyang
Pubblicazione: (2024)

Sparse Portfolio Selection via Topological Data Analysis based Clustering
di: Goel, Anubha, et al.
Pubblicazione: (2024)

Decision by Supervised Learning with Deep Ensembles: A Practical Framework for Robust Portfolio Optimization
di: Kim, Juhyeong, et al.
Pubblicazione: (2025)

Can Blindfolded LLMs Still Trade? An Anonymization-First Framework for Portfolio Optimization
di: Jeon, Joohyoung, et al.
Pubblicazione: (2026)

Exploratory Mean-Variance Portfolio Optimization with Regime-Switching Market Dynamics
di: Chen, Yuling Max, et al.
Pubblicazione: (2025)

From Headlines to Holdings: Deep Learning for Smarter Portfolio Decisions
di: Lin, Yun, et al.
Pubblicazione: (2025)

Financial Bond Similarity Search Using Representation Learning
di: Haeri, Amin, et al.
Pubblicazione: (2026)

A Novel approach to portfolio construction
di: Di Matteo, T., et al.
Pubblicazione: (2026)

Bayesian Portfolio Optimization by Predictive Synthesis
di: Kato, Masahiro, et al.
Pubblicazione: (2025)

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

Variable Clustering via Distributionally Robust Nodewise Regression
di: Wang, Kaizheng, et al.
Pubblicazione: (2022)

Maximally Machine-Learnable Portfolios
di: Coulombe, Philippe Goulet, et al.
Pubblicazione: (2023)

Mean-Variance Portfolio Selection in Long-Term Investments with Unknown Distribution: Online Estimation, Risk Aversion under Ambiguity, and Universality of Algorithms
di: Lam, Duy Khanh
Pubblicazione: (2024)

Stochastic Discount Factors with Cross-Asset Spillovers
di: Avramov, Doron, et al.
Pubblicazione: (2026)

AI-Powered Energy Algorithmic Trading: Integrating Hidden Markov Models with Neural Networks
di: Monteiro, Tiago
Pubblicazione: (2024)

A Case Study of Next Portfolio Prediction for Mutual Funds
di: Thomaz, Guilherme, et al.
Pubblicazione: (2024)

The Hybrid Forecast of S&P 500 Volatility ensembled from VIX, GARCH and LSTM models
di: Roszyk, Natalia, et al.
Pubblicazione: (2024)

Breaking the Dimensional Barrier: A Pontryagin-Guided Direct Policy Optimization for Continuous-Time Multi-Asset Portfolio Choice
di: Huh, Jeonggyu, et al.
Pubblicazione: (2025)

Forecasting stock return distributions around the globe with quantile neural networks
di: Barunik, Jozef, et al.
Pubblicazione: (2024)

Liquidity Adjustment in Multivariate Volatility Modeling: Evidence from Portfolios of Cryptocurrencies and US Stocks
di: Deng, Qi
Pubblicazione: (2024)

Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy
di: Yang, Hongyang, et al.
Pubblicazione: (2025)

Deep Learning for Options Trading: An End-To-End Approach
di: Tan, Wee Ling, et al.
Pubblicazione: (2024)

Predictive Power of LLMs in Financial Markets
di: Shi, Jerick, et al.
Pubblicazione: (2024)

RiskLabs: Predicting Financial Risk Using Large Language Model based on Multimodal and Multi-Sources Data
di: Cao, Yupeng, et al.
Pubblicazione: (2024)

Deep Learning, Predictability, and Optimal Portfolio Returns
di: Babiak, Mykola, et al.
Pubblicazione: (2020)

Ensembling Portfolio Strategies for Long-Term Investments: A Distribution-Free Preference Framework for Decision-Making and Algorithms
di: Lam, Duy Khanh
Pubblicazione: (2024)

Beating the Best Constant Rebalancing Portfolio in Long-Term Investment: A Generalization of the Kelly Criterion and Universal Learning Algorithm for Markets with Serial Dependence
di: Lam, Duy Khanh
Pubblicazione: (2025)

Onflow: a model free, online portfolio allocation algorithm robust to transaction fees
di: Turinici, Gabriel, et al.
Pubblicazione: (2023)

Accelerated Portfolio Optimization and Option Pricing with Reinforcement Learning
di: Keramati, Hadi, et al.
Pubblicazione: (2025)