332 research outputs found
A Dynamical Thermostat Approach To Financial Asset Price Dynamics
A dynamical price formation model for financial assets is presented. It aims
to capture the essence of speculative trading where mispricings of assets are
used to make profits. It is shown that together with the incorporation of the
concept of risk aversion of agents the model is able to reproduce several key
characteristics of financial price series. The approach is contrasted to the
conventional view of price formation in financial economics.Comment: contribution to the 6th Granada Seminar 2000: Modeling Complex
Systems, 10 pages, eps figure
Nonextensive statistical mechanics and complex scale-free networks
One explanation for the impressive recent boom in network theory might be
that it provides a promising tool for an understanding of complex systems.
Network theory is mainly focusing on discrete large-scale topological
structures rather than on microscopic details of interactions of its elements.
This viewpoint allows to naturally treat collective phenomena which are often
an integral part of complex systems, such as biological or socio-economical
phenomena. Much of the attraction of network theory arises from the discovery
that many networks, natural or man-made, seem to exhibit some sort of
universality, meaning that most of them belong to one of three classes: {\it
random}, {\it scale-free} and {\it small-world} networks. Maybe most important
however for the physics community is, that due to its conceptually intuitive
nature, network theory seems to be within reach of a full and coherent
understanding from first principles ..
Elimination of systemic risk in financial networks by means of a systemic risk transaction tax
Financial markets are exposed to systemic risk (SR), the risk that a major
fraction of the system ceases to function, and collapses. It has recently
become possible to quantify SR in terms of underlying financial networks where
nodes represent financial institutions, and links capture the size and maturity
of assets (loans), liabilities, and other obligations, such as derivatives. We
demonstrate that it is possible to quantify the share of SR that individual
liabilities within a financial network contribute to the overall SR. We use
empirical data of nationwide interbank liabilities to show that the marginal
contribution to overall SR of liabilities for a given size varies by a factor
of a thousand. We propose a tax on individual transactions that is proportional
to their marginal contribution to overall SR. If a transaction does not
increase SR it is tax-free. With an agent-based model (CRISIS macro-financial
model) we demonstrate that the proposed "Systemic Risk Tax" (SRT) leads to a
self-organised restructuring of financial networks that are practically free of
SR. The SRT can be seen as an insurance for the public against costs arising
from cascading failure. ABM predictions are shown to be in remarkable agreement
with the empirical data and can be used to understand the relation of credit
risk and SR.Comment: 18 pages, 7 figure
Hierarchical and mixing properties of static complex networks emerging from the fluctuating classical random graphs
The Erdos-Renyi classical random graph is characterized by a fixed linking
probability for all pairs of vertices. Here, this concept is generalized by
drawing the linking probability from a certain distribution. Such a procedure
is found to lead to a static complex network with an arbitrary connectivity
distribution. In particular, a scale-free network with the hierarchical
organization is constructed without assuming any knowledge about the global
linking structure, in contrast to the preferential attachment rule for a
growing network. The hierarchical and mixing properties of the static
scale-free network thus constructed are studied. The present approach
establishes a bridge between a scalar characterization of individual vertices
and topology of an emerging complex network. The result may offer a clue for
understanding the origin of a few abundance of connectivity distributions in a
wide variety of static real-world networks.Comment: 15 pages and 3 figure
DebtRank-transparency: Controlling systemic risk in financial networks
Banks in the interbank network can not assess the true risks associated with
lending to other banks in the network, unless they have full information on the
riskiness of all the other banks. These risks can be estimated by using network
metrics (for example DebtRank) of the interbank liability network which is
available to Central Banks. With a simple agent based model we show that by
increasing transparency by making the DebtRank of individual nodes (banks)
visible to all nodes, and by imposing a simple incentive scheme, that reduces
interbank borrowing from systemically risky nodes, the systemic risk in the
financial network can be drastically reduced. This incentive scheme is an
effective regulation mechanism, that does not reduce the efficiency of the
financial network, but fosters a more homogeneous distribution of risk within
the system in a self-organized critical way. We show that the reduction of
systemic risk is to a large extent due to the massive reduction of cascading
failures in the transparent system. An implementation of this minimal
regulation scheme in real financial networks should be feasible from a
technical point of view.Comment: 8 pages, 5 figure
Generalized (c,d)-entropy and aging random walks
Complex systems are often inherently non-ergodic and non-Markovian for which
Shannon entropy loses its applicability. In particular accelerating,
path-dependent, and aging random walks offer an intuitive picture for these
non-ergodic and non-Markovian systems. It was shown that the entropy of
non-ergodic systems can still be derived from three of the Shannon-Khinchin
axioms, and by violating the fourth -- the so-called composition axiom. The
corresponding entropy is of the form and depends on two system-specific scaling exponents, and . This
entropy contains many recently proposed entropy functionals as special cases,
including Shannon and Tsallis entropy. It was shown that this entropy is
relevant for a special class of non-Markovian random walks. In this work we
generalize these walks to a much wider class of stochastic systems that can be
characterized as `aging' systems. These are systems whose transition rates
between states are path- and time-dependent. We show that for particular aging
walks is again the correct extensive entropy. Before the central part
of the paper we review the concept of -entropy in a self-contained way.Comment: 8 pages, 5 eps figures. arXiv admin note: substantial text overlap
with arXiv:1104.207
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