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- W2545188890 abstract "In analysing the top-level structure of financial markets rough simplifications are often needed due to their high degree of complexity. The framework of complex networks provides a modern way to do this effectively. In this approach, a market is seen as a network, such that the nodes of the network correspond to market participants and the links reflect the dynamic interactions between them. This thesis contributes to the analysis of equity returns from the network point of view. By using empirical data on stock exchanges, we show how the general problem of extracting information from correlated time series can be formulated as a network problem. Then, we apply and develop network methods in order to analyse this problem. The purpose of the research is two folded. On the one hand, the goal is to extract new information on financial markets. On the other hand financial markets are seen as a data-rich test-bed for developing new methods and theories of more general interest. In addition to network methods, correlations between equity returns are analysed on the basis of the spectral properties of the correlation matrix. We show how these two approaches can be combined to study the top-level structure of equity markets, and believe that the results are of very general interest as well. Most emphasis is given to the analysis of the information content of correlation matrices of equity returns." @default.
- W2545188890 created "2016-11-04" @default.
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- W2545188890 date "2009-01-01" @default.
- W2545188890 modified "2023-09-23" @default.
- W2545188890 title "Complex networks and spectral methods : an econophysics approach to equity markets" @default.
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