activity
20192022
most citedAn Integrated Early Warning System for Stock Market Turbulence

5 citations · 11 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2022★ 1 cited

Parallel Hierarchical Transformer with Attention Alignment for Abstractive Multi-Document Summarization

Ye Ma, Lu Zong

In comparison to single-document summarization, abstractive Multi-Document Summarization (MDS) brings challenges on the representation and coverage of its lengthy and linked source…

q-fin.MF2020

Are Crises Predictable? A Review of the Early Warning Systems in Currency and Stock Markets

Peiwan Wang, Lu Zong

The study efforts to explore and extend the crisis predictability by synthetically reviewing and comparing a full mixture of early warning models into two constitutions: crisis ide…

cs.CL2020★ 1 cited

Global-aware Beam Search for Neural Abstractive Summarization

Ye Ma, Zixun Lan, Lu Zong +1

This study develops a calibrated beam-based algorithm with awareness of the global attention distribution for neural abstractive summarization, aiming to improve the local optimali…

cs.CL2020★ 4 cited

A Novel Distributed Representation of News (DRNews) for Stock Market Predictions

Ye Ma, Lu Zong, Peiwan Wang

In this study, a novel Distributed Representation of News (DRNews) model is developed and applied in deep learning-based stock market predictions. With the merit of integrating con…

cs.CL2020

Integrated Node Encoder for Labelled Textual Networks

Ye Ma, Lu Zong

Voluminous works have been implemented to exploit content-enhanced network embedding models, with little focus on the labelled information of nodes. Although TriDNR leverages node…

econ.EM2019★ 5 cited

An Integrated Early Warning System for Stock Market Turbulence

Peiwan Wang, Lu Zong, Ye Ma

This study constructs an integrated early warning system (EWS) that identifies and predicts stock market turbulence. Based on switching ARCH (SWARCH) filtering probabilities of the…