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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
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Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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portfolio
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publications
Analysing Network Dynamics: The Contagion Effects of SVB’s Collapse on the US Tech Industry
Published in , 2024
2023 was a turbulent year for the banking industry, with several banks announcing bankruptcy within just 2 months. Notably, the bank run at Silicon Valley Bank marked the third-largest bank failure in U.S. history. Considering its strong ties to tech companies, we looked into how the risks may have propagated in the tech industry by estimating a VAR model and network analysis. Find out more details by clicking the link to see whether risk contagion occurred in the tech industry, which companies acted as risk transmitters, and how these companies cluster into communities.
Recommended citation: Wu, F.; Liu, A.; Chen, J.; Li, Y. Analysing Network Dynamics: The Contagion Effects of SVB’s Collapse on the US Tech Industry. J. Risk Financial Manag. 2024, 17, 427. https://doi.org/10.3390/jrfm17100427
Download Paper
Spatial-Temporal Dynamics for Enhanced Temporal Link Prediction in Stock Market Crisis Forecasting
Working paper
This is a joint work with Ruizhi Zhang, Wei Wei, Qiming Wang, Yuhua Li, Jing Chen and Anqi Liu. We proposed a link prediction model by employing a Graph Convolutional Network and leveraging a transformer model. This work is currently under review.
Does one follow the other? A time-varying information spillover network of social media sentiment and news sentiment
Working paper
Paper Overview: Investor sentiment has been studied extensively to have an impact on asset prices and volatilities. In this study, we propose the transfer entropy-based information spillover networks to examine how different sentiment sources can spillover from one asset to another. By capturing the directional and non-linear information flows dynamics, we find that the constructed sentiment spillover networks reveal some unique properties to explain the sentiment spillovers in the financial markets. This work is currently under review.
A novel network risk index
Working paper
Paper Overview: The current risk measure does not consider the interconnectedness of financial markets. To address this limitation, we propose a two-layer information spillover network capturing both volatility and sentiment dynamics. By extracting network-based properties that quantify the intensity of the spillovers, we propose a risk index. Empirical results show the significance of this risk index in signalling the market risk.
talks
Conference Proceeding talk 3 on Relevant Topic in Your Field
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
Analysing network dynamics
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teaching
Graduate Tutor
Undergraduate courses (such as Probability, Financial Mathematics); and MSc dissertation supervision, Cardiff University School of Mathematics, 2022 – present
Lead Tutor
Lead and Tutor secondary school pupils in maths topics that are excluded from the standard school maths, We Solve Problems (Throughout England and Wales), 2023 – present
Statistics Tutor
Maths Support Service (Stats support to all the students across all schools), Cardiff University School of Mathematics, 2023 – present
