414 research outputs found
Limit order placement as an utility maximization problem and the origin of power law distribution of limit order prices
I consider the problem of the optimal limit order price of a financial asset
in the framework of the maximization of the utility function of the investor.
The analytical solution of the problem gives insight on the origin of the
recently empirically observed power law distribution of limit order prices. In
the framework of the model, the most likely proximate cause of this power law
is a power law heterogeneity of traders' investment time horizons .Comment: 7 pages, 2 figure
Corporate payments networks and credit risk rating
Aggregate and systemic risk in complex systems are emergent phenomena
depending on two properties: the idiosyncratic risks of the elements and the
topology of the network of interactions among them. While a significant
attention has been given to aggregate risk assessment and risk propagation once
the above two properties are given, less is known about how the risk is
distributed in the network and its relations with the topology. We study this
problem by investigating a large proprietary dataset of payments among 2.4M
Italian firms, whose credit risk rating is known. We document significant
correlations between local topological properties of a node (firm) and its
risk. Moreover we show the existence of an homophily of risk, i.e. the tendency
of firms with similar risk profile to be statistically more connected among
themselves. This effect is observed when considering both pairs of firms and
communities or hierarchies identified in the network. We leverage this
knowledge to show the predictability of the missing rating of a firm using only
the network properties of the associated node
Ensemble properties of securities traded in the NASDAQ market
We study the price dynamics of stocks traded in the NASDAQ market by
considering the statistical properties of an ensemble of stocks traded
simultaneously. For each trading day of our database, we study the ensemble
return distribution by extracting its first two central moments. According to
previous results obtained for the NYSE market, we find that the second moment
is a long-range correlated variable. We compare time-averaged and
ensemble-averaged price returns and we show that the two averaging procedures
lead to different statistical results.Comment: 7 pages, 3 figures, to appear in the proceedings of NATO ARW on
Application of Physics in Economic Modelling, Prague, 8-10 February 200
The organization of the interbank network and how ECB unconventional measures affected the e-MID overnight market
The topological properties of interbank networks have been discussed widely
in the literature mainly because of their relevance for systemic risk. Here we
propose to use the Stochastic Block Model to investigate and perform a model
selection among several possible two block organizations of the network: these
include bipartite, core-periphery, and modular structures. We apply our method
to the e-MID interbank market in the period 2010-2014 and we show that in
normal conditions the most likely network organization is a bipartite
structure. In exceptional conditions, such as after LTRO, one of the most
important unconventional measures by ECB at the beginning of 2012, the most
likely structure becomes a random one and only in 2014 the e-MID market went
back to a normal bipartite organization. By investigating the strategy of
individual banks, we explore possible explanations and we show that the
disappearance of many lending banks and the strategy switch of a very small set
of banks from borrower to lender is likely at the origin of this structural
change.Comment: 33 pages, 5 figure
Optimal information diffusion in stochastic block models
We use the linear threshold model to study the diffusion of information on a
network generated by the stochastic block model. We focus our analysis on a two
community structure where the initial set of informed nodes lies only in one of
the two communities and we look for optimal network structures, i.e. those
maximizing the asymptotic extent of the diffusion. We find that, constraining
the mean degree and the fraction of initially informed nodes, the optimal
structure can be assortative (modular), core-periphery, or even disassortative.
We then look for minimal cost structures, i.e. those such that a minimal
fraction of initially informed nodes is needed to trigger a global cascade. We
find that the optimal networks are assortative but with a structure very close
to a core-periphery graph, i.e. a very dense community linked to a much more
sparsely connected periphery.Comment: 11 pages, 6 figure
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