5 citations · 6 across the 4 of their papers we have counts for
5 papers
From Economic Explanation to Performance Improvement in Machine-Learning Portfolios
Yunqi Liang, Stefan Zohren, Mihai Cucuringu
To extend conventional model-level feature importance to economically meaningful portfolio outcomes and decisions, we propose a local first-order attribution-propagation framework…
Macro-aware time series forecasting via hierarchical mixed-frequency attention models
Daniel Cunha Oliveira, Kieran Wood, Stefan Zohren +2
Deep learning models show promise in financial forecasting, yet their generalization is often undermined by small datasets, noisy signals, and non-stationarity. While meta-learning…
A Bipartite Graph Approach to U.S.-China Cross-Market Return Forecasting
Jing Liu, Maria Grith, Xiaowen Dong +1
This paper studies cross-market return predictability through a machine learning framework that preserves economic structure. Exploiting the non-overlapping trading hours of the U.…
Symphony in the Latent Space: Provably Integrating High-dimensional Techniques with Non-linear Machine Learning Models
Qiong Wu, Jian Li, Zhenming Liu +2
This paper revisits building machine learning algorithms that involve interactions between entities, such as those between financial assets in an actively managed portfolio, or int…
Equity2Vec: End-to-end Deep Learning Framework for Cross-sectional Asset Pricing
Qiong Wu, Christopher G. Brinton, Zheng Zhang +3
Pricing assets has attracted significant attention from the financial technology community. We observe that the existing solutions overlook the cross-sectional effects and not full…