3 papers
cs.LG2026
HARN: Hierarchical Associative Resonance Network for Event-Driven Multi-Timeframe Forecasting
Nabeel Ahmad Saidd
Financial time series evolve across multiple temporal resolutions, challenging forecasting systems to incorporate newly available information without repeatedly recomputing unchang…
q-fin.GN2026
Decomposable Reward Modeling and Realistic Environment Design for Reinforcement Learning-Based Forex Trading
Nabeel Ahmad Saidd
Applying reinforcement learning (RL) to foreign exchange (Forex) trading remains challenging because realistic environments, well-defined reward functions, and expressive action sp…
q-fin.ST2026
A Controlled Comparison of Deep Learning Architectures for Multi-Horizon Financial Forecasting: Evidence from 918 Experiments
Nabeel Ahmad Saidd
Multi-horizon price forecasting is central to portfolio allocation, risk management, and algorithmic trading, yet deep learning architectures have proliferated faster than rigorous…