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Title: Modelling financial market based on econometric and complex network analysis
Author: Chen, Yanhua
Awarding Body: University of Liverpool
Current Institution: University of Liverpool
Date of Award: 2018
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The complex network theory, especially, the economic and financial networks have offered a new approach that emphasizes the complexities and interdependencies in the financial market. In this thesis, I am interested in combining the complex network theory and econometric measures, namely, cointegration and error correction models (ECM) to reveal the internal connectedness structure of the financial market and their dynamic characteristics evolution over time. The initial Chapters 1–2 present an introduction, background knowledge as well as the methodology has been applied throughout the thesis. Chapters 3–5 introduce corresponding specific problems leading up to their solutions. Specifically, in Chapter 3, we examine the dynamic evolution of short-term correlation, long-term cointegration and ECM-based long-term Granger causality between each pair of US, UK, and Eurozone stock markets from 1980 to 2015 using the rolling-window technique. A comparative analysis of pairwise dynamic integration and causality of stock markets, measured in common and domestic currency terms, is conducted to evaluate comprehensively how exchange rate fluctuations affect the time-varying integration among the S&P 500, FTSE 100 and EURO STOXX 50 indices. Chapter 4 seeks to incorporate the long-run cointegration and short-run error correction mechanisms to build up the financial networks to quantify the connectedness across 46 stock markets worldwide from January 2007 to June 2017. By constructing the static ECM-based global stock market network, the topological structure reflects the regional integrated and segmented stock markets. The dynamic international stock market further reveals the time-varying properties of both error correction effects and long-run equilibrium relations amongst 46 stock markets during periods of financial turmoil and implementation of the QEs in the Fed, BoE, BoJ, and ECB, respectively. In Chapter 5, we analyze the financial effects of Brexit-vote on the stocks traded on the London Stock Exchange (FTSE 100 and FTSE Mid250 Index). Specifically, we construct corresponding British stock networks using the ECM models to investigate the short-run self-correction mechanisms as well as long-run equilibrium amongst stocks from sectoral-level before and after the Brexit-vote. To extract most strongly related interactions from the British stock networks, the minimal spanning tree (MST) and hierarchical clustering analysis are applied for filtering network and to detect the taxonomy and hierarchical topological structure based our proposed Jaccard distance metric. Each chapter is followed by a mini-conclusion. In the end, we summarize our results and conclude the thesis by presenting some research directions based on our findings in Chapter 6.
Supervisor: Pantelous, Athanasios A. ; Zuev, Konstantin M. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral