The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
Aalto

Complex Networks in the Study of Financial and Social Systems

Jukka-Pekka Onnela

Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Department of Electrical and Communications Engineering for public examination and debate in Auditorium E at Helsinki University of Technology (Espoo, Finland) on the 10th of July, 2006, at 12 noon.

Overview in PDF format (ISBN 951-22-8270-4)   [1574 KB]
Dissertation is also available in print (ISBN 951-22-8269-0)

Abstract

Complex systems consist of a large number of interacting elements, giving rise to the emergence of organisation without any external organising principle being applied. Consequently, decomposing the system and studying its subparts in isolation does not contribute to our understanding of how it works. Fortunately, complex systems can be described, analysed, and modelled using complex networks. Here one focuses only on the elements and topology of interactions between them, providing a system-level perspective to the system under study.

This thesis contributes to the network approach to complex systems in two ways. First, using empirical data on the financial market, we show how a general problem dealing with correlated actors can be recast as a network problem. In principle, this simple method is applicable to any complex system with temporal correlations of quantities attached to each element. In the context of social systems we demonstrate how a network model of social actors can be constructed to capture the hypothesised structure of interactions. Using the rate equation approach, we develop a simple phenomenological model intended for future study of processes unfolding on social networks. Second, we develop generalisable methods and measures for network characterisation. These measures are not too application specific so they can be transferred to disparate complex systems. For example, we augment the motif framework to incorporate interaction strengths, enabling us to go beyond topology and account for the heterogeneity of interactions.

The studied complex systems can be classified broadly as financial and social systems. As data rich systems they enable a thorough testing of the developed concepts. In addition, they have numerous applications within the complex systems paradigm, including developing better risk management schemes and enabling in silico testing of different disease immunisation scenarios. The focus of this thesis lies in the universal aspects of these systems; the line of enquiry is to motivate a question in one system, then step back and see if the machinery developed to tackle the problem has relevance to other systems. In addition to conceptual developments, we provide tools for characterising complex networks in practice.

This thesis consists of an overview and of the following 9 publications:

  1. J.-P. Onnela, A. Chakraborti, K. Kaski, and J. Kertész, Dynamic asset trees and portfolio analysis, The European Physical Journal B, 30, 285 (2002). © 2002 EDP Sciences. By permission.
  2. J.-P. Onnela, A. Chakraborti, K. Kaski, and J. Kertész, Dynamic asset trees and Black Monday, Physica A, 324, 247 (2003). © 2003 Elsevier Science. By permission.
  3. J.-P. Onnela, A. Chakraborti, K. Kaski, J. Kertész, and A. Kanto, Asset trees and asset graphs in financial markets, Physica Scripta, T106, 48 (2003). © 2003 The Royal Swedish Academy of Sciences. By permission.
  4. J.-P. Onnela, A. Chakraborti, K. Kaski, J. Kertész, and A. Kanto, Dynamics of market correlations: Taxonomy and portfolio analysis, Physical Review E, 68, 056110 (2003). © 2003 American Physical Society. By permission.
  5. J.-P. Onnela, K. Kaski, and J. Kertész, Clustering and information in correlation based financial networks, The European Physical Journal B, 38, 353 (2004). © 2004 EDP Sciences. By permission.
  6. J.-P. Onnela, J. Saramäki, J. Kertész, and K. Kaski, Intensity and coherence of motifs in weighted complex networks, Physical Review E, 71, 065103(R) (2005). © 2005 American Physical Society. By permission.
  7. J. Saramäki, J.-P. Onnela, J. Kertész, and K. Kaski, Characterizing motifs in weighted complex networks, In: J. F. F. Mendes, et al. (Eds.), Science of Complex Networks, AIP Conference Proceedings, 776, 108 (2005). © 2005 American Institute of Physics. By permission.
  8. J.-P. Onnela, J. Saramäki, K. Kaski, and J. Kertész, Financial market – a network perspective, In: H. Takayasu (Ed.), Practical Fruits of Econophysics, Proceedings of the Third Nikkei Econophysics Symposium, Springer, Tokyo, 302 (2006).
  9. R. Toivonen, J.-P. Onnela, J. Saramäki, J. Hyvönen, and K. Kaski, A model for social networks, Physica A, in press (2006). © 2006 by authors and © 2006 Elsevier Science. By permission.

Keywords: complex systems, complex networks, financial systems, social systems, network models

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© 2006 Helsinki University of Technology

Last update 2011-05-26