arXiv Machine Learning

Deep Learning Based on Generative Adversarial and Convolutional Neural Networks for Financial Time Series Predictions

arXiv:2008. 08041v3 Announce Type: replace-cross Abstract: In the big data era, deep learning and intelligent data mining technique solutions have been applied by researchers in various areas.

arXiv AI

Jun 30

Adaptive Financial Transformer with Regime-Gated Attention for Stock Return Prediction

arXiv:2606. 29347v1 Announce Type: cross Abstract: Adaptive Financial Transformer (AFT) is proposed for stock return prediction under non-stationary financial markets.

By Dishan Sarkar

llms benchmarks safety

arXiv AI

23h ago

MoFE: A Novel Mixture-of-Experts Framework with Fourier Neural Operators for Cryptocurrency Forecasting

arXiv:2608. 17342v1 Announce Type: cross Abstract: Forecasting cryptocurrency prices remains a formidable challenge due to inherent non-stationarity, abrupt regime shifts, and multi-scale stochastic dependencies.

By Bowen Liu, Mingming Sun

benchmarks

arXiv AI

Jul 17

A Comparative Analysis of Machine Learning Models for Long and Short-Term Forecasting of the Egyptian Stock Market: A Focus on EGX30

arXiv:2607. 14391v1 Announce Type: new Abstract: This study concentrates on predicting stock prices in the Egyptian market, focusing on the EGX30, an influential financial hub in the Middle East.

By Muhammed Walid, Ahmed El-Naeimy, Hosam Moubarak, Walid Gomaa

arXiv Machine Learning

Jun 4

Generating Financial Time Series by Matching Random Convolutional Features

arXiv:2606. 05138v1 Announce Type: new Abstract: Generating realistic financial time series is challenging as training data is often limited to a single historical path.

By Konrad J. Mueller, Nikita Zozoulenko, Ben Wood, Thomas Cass, Lukas Gonon

diffusion safety

arXiv Machine Learning

Jun 2

Optimizing accuracy and diversity: a multi-task approach to forecast combinations

arXiv:2310. 20545v3 Announce Type: replace Abstract: We present a multi-task optimization approach based on a deep learning architecture for time series forecasting.

By Giovanni Felici, Antonio M. Sudoso

benchmarks

arXiv Machine Learning

23h ago

Deep Learning for Cross-Border Electricity Price Forecasting: A Comparative Study

arXiv:2608. 17091v1 Announce Type: new Abstract: While publicly available electricity market data presents a valuable resource for forecasting research, the field lacks established benchmark datasets for standardized comparison.

By Hadeer Elashhab, Sai Srijan Papineni, Marvin Dorn, Veit Hagenmeyer, Benjamin Sch\"afer

llms benchmarks

arXiv Machine Learning

Jul 31

FinSMART: Financial Sentiment Analysis for Algorithmic Trading through Market-Aligned Reinforcement Learning

arXiv:2607. 28127v1 Announce Type: cross Abstract: Recent advances in Generative AI have substantially improved financial sentiment analysis through post-trained financial large language models (LLMs).

By Giorgos Iacovides, Wuyang Zhou, Danilo Mandic

llms nlp reinforcement-learning benchmarks

arXiv Machine Learning

Jul 28

Bitcoin Price Direction Prediction via Regime-Aware Multi-Modal Fusion of Social Sentiment and Technical Features

arXiv:2607. 23370v1 Announce Type: new Abstract: Bitcoin price prediction on sub-daily timescales is a hard open problem in computational finance.

By Muhammad Abdullah Haroon

rag multimodal benchmarks

arXiv Machine Learning

6d ago

Regime-Gated Residual Mixture-of-Experts for Cross-Sectional Volatility Forecasting

arXiv:2608. 12251v1 Announce Type: cross Abstract: Financial volatility is regime dependent, yet incorporating regime information into neural networks can also destabilize training.

By Junyi Ye, Gargi Vijay Borde

arXiv AI

Jul 14

Exploratory Analysis of Deep Learning Models for Forecasting Meteorological Parameters in the Agricultural Sector

arXiv:2607. 10208v1 Announce Type: cross Abstract: Accurate meteorological forecasting is essential for agricultural planning, irrigation management, and environmental decision support.

By Piotr Sikora, Sotirios Kontogiannis

arXiv AI

Aug 11

Hybrid Neural-Classical Correction for Frozen Time Series Foundation Models: A Comprehensive Ablation Study on High-Frequency Stock Prediction

arXiv:2608. 08825v1 Announce Type: cross Abstract: Foundation models for time series forecasting demonstrate impressive zero-shot generalization but often underperform on specialized domains such as high-frequency finance.

By Kasun Dewage, Suranadi De Silva, Shankhadeep Mondal

benchmarks

arXiv AI

Jun 30

When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate

arXiv:2512. 03578v3 Announce Type: replace-cross Abstract: Time series extrinsic regression (TSER) refers to the task of predicting a continuous target variable from an input time series.

By Florent Forest, Amaury Wei, Olga Fink

benchmarks safety

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