Complexity and Networks in Economics and Finance
Begeleiding : Prof. Koen Schoors
(promotor, Faculteit Economie en Bedrijfskunde), Jan Ryckebusch (promotor),
Benjamin Vandermarliere, Andres Belaza, Milan van den Heuvel, Ken Bastiaensen
One of fhe most puzzling things about the financial crisis of
2008 is that it was caused by a relatively small group of financial
products. The subprime exposure, which was often believed to be rather
marginal, gave rise to widespread problems, and started a domino
effect which made the entire financial system to topple. In
the physicist's jargon, this means that a local perturbation affected the
system as a whole. This was possible because over the years, the
financial system grew more and more complex. Thereby, all agents in the financial system are highly
interconnected very by means of unrecognized links. Policy
makers tried to stabilize the system by devising rules for each
individual player. In physics it is well known that "The whole is most
often more than the sum of its parts", and systemic risk is also at
play in the highly interconnected financial system.
The financial calamities of 2008 has boosted a lot research into the complexity of interbank networks in particular, and
in economics and finance in general. This field is highly
interdisciplinary drawing on big data manipulation, advanced statistical analyses, computational sciences, finance, game
theory, network theory and complexity science. We propose two master's thesis subjects in a timely and
very exciting field of interdisciplinary Physics.
Subject 1: Controllability in interbank networks
Coaches and contact persons: Milan Van den Heuvel, Benjamin Vandermarliere, Jan
The application of network theory to interbank systems already
resulted in major advances in our understanding about their topology,
interaction dynamics, and growth. A major issue is the endeavour to
steer the evolution of the banking system in the direction of
optimized control. Thereby, one aims at defining the rules of the operation of the
interbank credit system such that it evolves in a certain direction.
The master's thesis will address the issue of structural
controllability of interbank credit networks under different
conditions. Using principles of network theory one can identify the
nodes which need to be controlled in order to achieve a status whereby
one can drive the network from an initial state to a selected final
state. Thereby, it is essential to possess an effective method or
algorithm to identify the driver nodes at each instant of time.
Controllability in network science is a relatively new theory. After
having mastered the concept of controllablity, the student will study
a version of the CRISIS
agent-based interbank model. She/he will analyse the time series of
the evolution of the interbank system under different scenarios. In
particular, a study will be made of the connection between
controllability and the underlying dynamics of the simulated
network. The concept of control very much hinges on the (non)existence
of a link between different nodes in the network. Traditionally,
interactions between nodes are aggregated into a single network
layer. In practice, interactions can adopt very different forms and
some interactions may be more effective than others to gain control of the nodes.
To this end, one has developed the concepts of multilayer networks ( A
recent paper on the topic of Multilayer Networks
). In the context
of the research for the master's thesis, it will be investigated
whether the theory of Multilayer Networks provides a superior way of
defining the controllability of the system.
Subject 2: Human mobility in a virtual world
Coaches and contact persons: Andres Belaza and Jan
The motion of people at different spatiotemporal scales
play a key role in many fields. An improved knowledge of the patterns
in the motions of people, is key information for the optimization of
public transport routes, or for the design of measures that keep the
propagation of the flu under control. People's motion inside and
between urban areas present different behavior. In an urban
environment, people go to work to industrial areas or the city center
and return home in the evening, presenting daily cycles that are less
common in the motion between cities.
These days, the cell phone network, creates a high-quality
dataset on human mobility. This data, however, is highly personal and
the phone companies protect this data. Video games have been used
before as a proxy for real-world behavior in studies in economy and
In the context of the proposed MSc thesis
subject, the student will analyze the motion of the different players
in a virtual world (EVE online), with similar techniques that are
used for urban mobility and try to figure out which kind of dynamics
play an essential role. For this thesis, strong programming skills
and a knack for data analysis are be highly recommended.
Gallotti, R. Bazzani, A. Rambaldi, S. "Towards a Statistical Physics of Human Mobility".
Simini, F. Gonzalez, MC. Maritan, A, Barabasi Albert-Laszlo. "A universal model for mobility and migration patterns". Nature 484, 96-100.
Szell, M., Sinatra, R., Petri G. Thurner S. Latora, V. "Understanding mobility in a social petri dish". Scientific Reports volume 2, 2012
Subject 3: Structure and evolution of the corporate ownership network
Coach and contact person: Benjamin Vandermarliere
The structure of the control network of transnational corporations
affects global market competition and financial stability. So far,
only static yearly snapshots of this ownership network have been
studied (Ref. ). In this master’s thesis, we will expand to a dynamic
view of this ownership network by leveraging a unique data set
covering a 20-year period.
By using state-of-the-art techniques to capture structures and their
evolution in temporal networks (Ref. ) we will address topical questions
like: “Did the 2008 financial crisis lead to a higher concentration
of corporate control into fewer people hands?” “How do foreign
investors get entangled over time into the companies of a country?”
The topic requires a healthy interest in finance
and economics, data analysis, machine learning, and network theory (statistical physics).
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