Key papers

• DBLoss: Decomposition-based Loss Function for Time Series Forecasting (2025)
  Xiangfei Qiu et al.
  9.63
• A Model of the Fed's View on Inflation (2020)
  Thomas Hasenzagl et al.
  9.47
• Realised Volatility Forecasting: Machine Learning via Financial Word Embedding (2021)
  Eghbal Rahimikia et al.
  9.41
• FinBERT-BiLSTM: A Deep Learning Model for Predicting Volatile Cryptocurrency Market Prices Using Market Sentiment Dynamics (2024)
  Mabsur Fatin Bin Hossain et al.
  8.75
• fev-bench: A Realistic Benchmark for Time Series Forecasting (2025)
  Oleksandr Shchur et al.
  8.05
• HQNN-FSP: A Hybrid Classical-Quantum Neural Network for Regression-Based Financial Stock Market Prediction (2025)
  Prashant Kumar Choudhary et al.
  7.84
• Multimodal Stock Price Prediction (2025)
  Furkan Karada\c{s} et al.
  7.53
• FinCast: A Foundation Model for Financial Time-Series Forecasting (2025)
  Zhuohang Zhu et al.
  7.06
• A Machine Learning Approach For Bitcoin Forecasting (2025)
  Stefano Sossi-Rojas and Gissel Velarde and Damian Zieba
  6.83
• Smoothing Quantile Regression Averaging: A new approach to probabilistic forecasting of electricity prices (2023)
  Bartosz Uniejewski
  6.39
• Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market (2025)
  Katarzyna Ch\k{e}\'c and Bartosz Uniejewski and Rafa{\l} Weron
  6.36
• ResNLS: An Improved Model for Stock Price Forecasting (2023)
  Yuanzhe Jia et al.
  6.24
• Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models (2023)
  Alejandro Lopez-Lira and Yuehua Tang
  6.12
• Forecasting S&P 500 Using LSTM Models (2025)
  Prashant Pilla and Raji Mekonen
  6.01
• Avocado Price Prediction Using a Hybrid Deep Learning Model: TCN-MLP-Attention Architecture (2025)
  Linwei Zhang et al.
  5.96
• Sensitivity Analysis of Priors in the Bayesian Dirichlet Auto-Regressive Moving Average Model (2025)
  Harrison Katz et al.
  5.70
• Times2D: Multi-Period Decomposition and Derivative Mapping for General Time Series Forecasting (2025)
  Reza Nematirad et al.
  5.59
• Cross-Modal Temporal Fusion for Financial Market Forecasting (2025)
  Yunhua Pei and John Cartlidge and Anandadeep Mandal and Daniel Gold and Enrique Marcilio and Riccardo Mazzon
  5.59
• Transformers with Attentive Federated Aggregation for Time Series Stock Forecasting (2024)
  Chu Myaet Thwal et al.
  5.51
• TimeCAP: Learning to Contextualize, Augment, and Predict Time Series Events with Large Language Model Agents (2025)
  Geon Lee et al.
  5.48
• Forecasting VIX using interpretable Kolmogorov-Arnold networks (2025)
  So-Yoon Cho et al.
  5.13
• Quantifying Cryptocurrency Unpredictability: A Comprehensive Study of Complexity and Forecasting (2025)
  Francesco Puoti et al.
  5.13
• TimeSeriesScientist: A General-Purpose AI Agent for Time Series Analysis (2025)
  Haokun Zhao et al.
  4.78
• Joint Embeddings Go Temporal (2025)
  Sofiane Ennadir et al.
  4.58
• Interpreting Time Series Forecasts with LIME and SHAP: A Case Study on the Air Passengers Dataset (2025)
  Manish Shukla
  4.53
• Forecasting Nigerian Equity Stock Returns Using Long Short-Term Memory Technique (2025)
  Adebola K. Ojo and Ifechukwude Jude Okafor
  4.47
• Comparative analysis of financial data differentiation techniques using LSTM neural network (2025)
  Dominik Stempie\'n and Janusz Gajda
  4.36
• Gradient Boosting Decision Tree with LSTM for Investment Prediction (2025)
  Chang Yu et al.
  4.36
• Extended Deep Adaptive Input Normalization for Preprocessing Time Series Data for Neural Networks (2023)
  Marcus A. K. September et al.
  4.35
• Piercing Gilbreath's Conjecture: From Deep Number Theory Insights to Fintech and Cybersecurity (2026)
  Vincent Granville
  4.33
• Overshooting the Coordinate: Where Factor Corrections Land on Characteristic Axes (2026)
  Useong Shin
  4.33
• When do prophets profit in prediction markets? (2026)
  Anri Gu et al.
  4.33
• YUKTI: From Natural-Language Situations to Robust, Verifiable Decisions An Uncertainty-Typed Proposition IR, Assumption-Robust Pareto Frontiers, and a Regret Certificate (2026)
  Suyash Mishra
  4.33
• Verification of Adaptive Agentic Controllers through Finite Rule Revision (2026)
  Roberto Garrone
  4.33
• Can Agentic Trading Systems Pay for Their Own Intelligence? (2026)
  Qiqi Duan et al.
  4.33
• NextFund: A Unified Performance Tracking Platform for Agentic Portfolio Management (2026)
  Changlun Li et al.
  4.33
• PREF-Gate: Provenance-Constrained Relational Evidence Fusion with Validation-Gated Selection for Graph Fraud Detection (2026)
  Liming Liu et al.
  4.33
• From Neural Network Decisions to Training Cases: An Exact Account via Case-Based Decision Theory (2026)
  Manli Yan et al.
  4.33
• Statistical Properties and Power Analysis of Divergence Measures for Credit Risk Model Monitoring (2026)
  Abdullah Karasan et al.
  4.33
• From Long News to Accurate Forecast: Importance-Aware Fusion and PRM-Guided Reflection for Time Series Forecasting (2026)
  Mingyang Liu et al.
  4.27
• FinStressTS: A Parametric Synthetic Benchmark for Time-Series Forecasting in Finance (2026)
  Jiaze Sun et al.
  4.27
• Harnessing Generalist Agents for Contextualized Time Series (2026)
  Zihao Li et al.
  4.27
• Multiple cyclicity and Wavelet Decomposition with Channel Correlation for Long-term Time Series Forecasting (2026)
  Bin Wang et al.
  4.27
• RAVEN: A Regime-Aware Variable-context Expert Network for Financial Time Series Forecasting (2026)
  Cheng He et al.
  4.27
• Multimodal Stock Price Prediction: A Case Study of the Russian Securities Market (2025)
  Kasymkhan Khubiev and Mikhail Semenov
  4.25
• Game-Theoretic Modeling of Heterogeneous Investor Interactions for Stock Price Forecasting (2026)
  Yong Zhang et al.
  4.22
• Algometrics: Forecasting Under Algorithmic Feedback (2026)
  Marc Schmitt
  4.22
• Assessing the Operational Viability of Foundation Models for Time Series Forecasting (2026)
  Kavin Soni et al.
  4.22
• Deep ZakaiJ: Structured Filtering for Jump-Diffusion Time Series Forecasting (2026)
  Yan Leng et al.
  4.22
• Nonlinear and Heavy-Tailed Predictability in Transition-Energy Financial Markets (2026)
  Kpante Emmanuel Gnandi (INSA Toulouse) et al.
  4.22
• CAMEF: Causal-Augmented Multi-Modality Event-Driven Financial Forecasting by Integrating Time Series Patterns and Salient Macroeconomic Announcements (2025)
  Yang Zhang et al.
  4.19
• Regression and Forecasting of U.S. Stock Returns Based on LSTM (2025)
  Shicheng Zhou et al.
  4.19
• Financial sentiment analysis using FinBERT with application in predicting stock movement (2023)
  Tingsong Jiang et al.
  4.13
• Neural Stochastic Flows: Solver-Free Modelling and Inference for SDE Solutions (2025)
  Naoki Kiyohara et al.
  4.11
• Multi-period Learning for Financial Time Series Forecasting (2025)
  Xu Zhang and Zhengang Huang and Yunzhi Wu and Xun Lu and Erpeng Qi and Yunkai Chen and Zhongya Xue and Qitong Wang and Peng Wang and Wei Wang
  4.03
• Macroeconomic Forecasting and Machine Learning (2025)
  Ta-Chung Chi et al.
  3.97
• Measuring Time Series Forecast Stability for Demand Planning (2025)
  Steven Klee and Yuntian Xia
  3.86
• Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention (2025)
  Sarthak Khanna et al.
  3.86
• Probabilistic Forecasting Cryptocurrencies Volatility: From Point to Quantile Forecasts (2025)
  Grzegorz Dudek et al.
  3.86
• AdaWaveNet: Adaptive Wavelet Network for Time Series Analysis (2024)
  Han Yu et al.
  3.80