3 papers
cs.LG2026
DIVINE: Simple Cross-Market Stock Pretraining via Diverse Indicator Reconstruction
Kuan-Yu Chen, Shu-Cheng Zheng, Yu-Chen Den +2
Financial time-series pretraining typically learns from masked observations, contrastive relations, or future outcomes---yet existing objectives struggle to simultaneously avoid fu…
cs.LG2026
MAPLE: Efficient and Diverse Multi-Alpha Generation for Portfolio Construction
Yu-Chen Den, Kuan-Yu Chen, Kendro Vincent +1
Classical alpha mining achieves strong risk-adjusted returns by combining many low-correlated predictive signals, yet deep learning stock-ranking methods typically produce a single…
cs.LG2026
Integrating Inductive Biases in Transformers via Distillation for Financial Time Series Forecasting
Yu-Chen Den, Kuan-Yu Chen, Kendro Vincent +1
Transformer-based models have been widely adopted for time-series forecasting due to their high representational capacity and architectural flexibility. However, many Transformer v…