1,721,014 research outputs found
Black-Scholes-Schrödinger-Zipf-Mandelbrot model framework for improving a study of the coauthor core score
No full textThe data and findings by Miskiewicz (2013) on the relationship between the number (J) of publications ranked according to their decreasing importance, for some scientist with her/his coauthors (CA), i.e. J α 1/r α, as found in Ausloos (2013), when specific types of publications, i.e. proceedings (in a generalized sense) and peer-review journals, are considered, are reexamined along the Zipf-Mandelbrot law Mandelbrot (1977), i.e. J α 1/(ν+r)ζ. The statistics are much improved. The exponent α and ζ are compared. The m a core value, i.e. the core number of CAs [1] is unaffected, of course. A Black-Scholes-Schrödinger model framework is proposed to describe the findings. © 2014 Elsevier B.V. All rights reserved
Physics of Competition and Conflicts
No full textThe issue gathers the papers delivered at the 1st annual meeting of the COST Action Physics of Competition and Conflicts, held in Rome, 2009
Dall’integrale di Riemann all’integrale di Itô
No full textIl libro è un trattato avanzato che riassume la teoria matematica dell'integrazione partendo dagli integrali di funzioni continue fino ad arrivare all'integrale stocastico. E' utile per i giovani ricercatori e per coloro che si avvicinano alla Finanza proveniendo da altre discipline (Matematica, Fisica).The book is sums up -at an advanced level - the mathematical theory of integration, starting from the integrals of continuous functions, till to the stochastic integral. It is useful for early stage researchers, as well to researchers that approach Finance coming from other disciplines (Mathematics, Physics)
Centrality Measures in Shareholding Networks
No full textThis paper aims to understand the role of most used centrality measures on the specific topics of shareholding networks,
and to propose new measures for describing the emergence of market leaders. Data on companies and shareholdings
are embedded into a weighted network. Both operational research and complex networks approaches are used.
The former provides tools for unveiling paths of ownership and control that could not be evident at a first glance.
The latter proposes the concept of centrality measure and offers a wide set of measures that add knowledge in understanding the relevance of nodes in the network. The combination of both approaches gives hints for understanding phenomena like tunneling, that is relevant for the detection of the response to market fluctuation due to financial instabilities.
The present analysis also considers the response of the system under random and targeted attacks. The Italian Stock Market is examined as a case study
Network of companies: an analysis of market concentration in the Italian stock market
No full textIn this paper we propose an adjustment to the Herfindahl-Hirschman concentration index for explicitly considering the role of the topology of financial economic networks on market concentration. The case study of the Italian stock market serves for outlining the relevance of the shareholding network in the measurement of effective concentration. Moreover, we deepen the analysis of the network comparing network centrality measures, that are a well known method for understanding the relative relevance of network nodes. The correlations among them show their relation, and the fact that none of them can completely substitute the information contained in the size of companies. Such analysis constitutes the base for randomized experiments aiming at understanding to which extent the topology of this financial economic network is constraining the market concentration, so we derive and comment the results on the maximum value of HH {Mathematical expression} under the scale-free constraint. We also show the fragility of the network under random rewiring, both unconstrained and constrained by the network topology. © 2013 Springer Science+Business Media Dordrecht
Network analysis of ownership and control structure in the Italian Stock market
No full textThis work has two targets. First, we gather data on the board of directors of companies traded on the Italian Stock Market,
and we analyze the structure of the related network. second, we measure the overlap among the network of the board of directors
and the shareholding network, and we evaluate the relevance of the board of direcors on control, effective control, and cross-ownership relationships.
In fact, shareholding data, that we have already analyzed in a previous work, capture a part only of the dependence structure, while the companies
that are on the market since many years interact most through social means and common directors. Thus, such approach
is a first step towards the merge of social interaction information into the analysis of ties of companies.
Although we are aware that a complete analysis of social interaction and families would reveal extra complex interactions,
we show how public available information changes the set of controller and controlled companies.
The results point out a cause of structural risk of the market that is not considered by usual econometric models for time serries of returns, and it provides
a basis for the development of new indicators for risk that overcome the standard approaches most based on the time series analysis of raw return time series.
Methods used in the present analysis involve statistical analyses most proper of the field of complex networks and graph flow analysis typical of operations research approach.
The dataset reports the board of directors (CONSOB database), and the shareholdings of nearly 300 companies traded on the Italian Stock Market.
Data, adjourned at May 2009, were retrieved through the Bureau van Dijk databases AIDA, BANKSCOPE and ISIS, and cross-validated through CONSOB and MEDIOBANCA reports
Mutual funds relationships and performance analysis
No full textThe present paper aims at exploring the equity exposure of Italian equity mutual funds as they emerge from their portfolio holdings at the date of December 31st, 2010. The technique adopted in the analysis considers the construction of a bipartite network and the detection of the overlap of portfolios held by mutual funds. The relationship among stocks due to their presence in the same portfolios is analyzed, too. Methods typical of complex networks are then applied. The comparison with several performance measures allows to discuss features of active/passive style management for institutional portfolios. © 2014 Springer Science+Business Media Dordrecht
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