11 citations · 46 across the 13 of their papers we have counts for
13 papers
Systemic Risk in DeFi: A Network-Based Fragility Analysis of TVL Dynamics
Shiyu Zhang, Zining Wang, Jin Zheng +1
Systemic risk refers to the overall vulnerability arising from the high degree of interconnectedness and interdependence within the financial system. In the rapidly developing dece…
BondBERT: What we learn when assigning sentiment in the bond market
Toby Barter, Zheng Gao, Eva Christodoulaki +2
Bond markets respond differently to macroeconomic news compared to equity markets, yet most sentiment models are trained primarily on general financial or equity news data. However…
How Wide and How Deep? Mitigating Over-Squashing of GNNs via Channel Capacity Constrained Estimation
Zinuo You, Jin Zheng, John Cartlidge
Existing graph neural networks typically rely on heuristic choices for hidden dimensions and propagation depths, which often lead to severe information loss during propagation, kno…
Capturing Intransitive Dominance in Tennis Forecasting: A Graph Neural Network Approach
Lawrence Clegg, John Cartlidge
Intransitive player dominance, where player A beats B, B beats C, but C beats A, is common in competitive tennis. Yet, there are few known attempts to incorporate it within forecas…
VMDNet: Temporal Leakage-Free Variational Mode Decomposition for Electricity Demand Forecasting
Weibin Feng, Ran Tao, John Cartlidge +1
Accurate electricity demand forecasting is challenging due to the strong multi-periodicity of real-world demand series, which makes effective modeling of recurrent temporal pattern…
Deep Reinforcement Learning for Optimal Asset Allocation Using DDPG with TiDE
Rongwei Liu, Jin Zheng, John Cartlidge
The optimal asset allocation between risky and risk-free assets is a persistent challenge due to the inherent volatility in financial markets. Conventional methods rely on strict d…
Improving Bayesian Optimization for Portfolio Management with an Adaptive Scheduling
Zinuo You, John Cartlidge, Karen Elliott +2
Existing black-box portfolio management systems are prevalent in the financial industry due to commercial and safety constraints, though their performance can fluctuate dramaticall…
Cross-Modal Temporal Fusion for Financial Market Forecasting
Yunhua Pei, John Cartlidge, Anandadeep Mandal +3
Accurate forecasting in financial markets requires integrating diverse data sources, from historical prices to macroeconomic indicators and financial news. However, existing models…
Dynamic Graph Representation with Contrastive Learning for Financial Market Prediction: Integrating Temporal Evolution and Static Relations
Yunhua Pei, Jin Zheng, John Cartlidge
Temporal Graph Learning (TGL) is crucial for capturing the evolving nature of stock markets. Traditional methods often ignore the interplay between dynamic temporal changes and sta…
Artificial Intelligence for Collective Intelligence: A National-Scale Research Strategy
Seth Bullock, Nirav Ajmeri, Mike Batty +15
Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or trans-national scale…
Simulation of Social Media-Driven Bubble Formation in Financial Markets using an Agent-Based Model with Hierarchical Influence Network
Gonzalo Bohorquez, John Cartlidge
We propose that a tree-like hierarchical structure represents a simple and effective way to model the emergent behaviour of financial markets, especially markets where there exists…
Multi-relational Graph Diffusion Neural Network with Parallel Retention for Stock Trends Classification
Zinuo You, Pengju Zhang, Jin Zheng +1
Stock trend classification remains a fundamental yet challenging task, owing to the intricate time-evolving dynamics between and within stocks. To tackle these two challenges, we p…
DGDNN: Decoupled Graph Diffusion Neural Network for Stock Movement Prediction
Zinuo You, Zijian Shi, Hongbo Bo +3
Forecasting future stock trends remains challenging for academia and industry due to stochastic inter-stock dynamics and hierarchical intra-stock dynamics influencing stock prices.…