8 citations · 17 across the 6 of their papers we have counts for
7 papers
A Multimodal Embedding-Based Approach to Industry Classification in Financial Markets
Rian Dolphin, Barry Smyth, Ruihai Dong
Industry classification schemes provide a taxonomy for segmenting companies based on their business activities. They are relied upon in industry and academia as an integral compone…
Stock Embeddings: Learning Distributed Representations for Financial Assets
Rian Dolphin, Barry Smyth, Ruihai Dong
Identifying meaningful relationships between the price movements of financial assets is a challenging but important problem in a variety of financial applications. However with rec…
NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-task Financial Forecasting
Linyi Yang, Jiazheng Li, Ruihai Dong +2
Financial forecasting has been an important and active area of machine learning research because of the challenges it presents and the potential rewards that even minor improvement…
Pseudo-labelling Enhanced Media Bias Detection
Qin Ruan, Brian Mac Namee, Ruihai Dong
Leveraging unlabelled data through weak or distant supervision is a compelling approach to developing more effective text classification models. This paper proposes a simple but ef…
Measuring Financial Time Series Similarity With a View to Identifying Profitable Stock Market Opportunities
Rian Dolphin, Barry Smyth, Yang Xu +1
Forecasting stock returns is a challenging problem due to the highly stochastic nature of the market and the vast array of factors and events that can influence trading volume and…
Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification
Linyi Yang, Eoin M. Kenny, Tin Lok James Ng +3
Corporate mergers and acquisitions (M&A) account for billions of dollars of investment globally every year, and offer an interesting and challenging domain for artificial intellige…