Statistics seminar 2019 - "Complex networks modeling for financial data"

  • Data: 11 aprile 2019 dalle 14:30 alle 16:30

  • Luogo: Dipartimento di Scienze Statistiche - via delle Belle Arti 41 - Aula seminari - I° piano

Giulia Rotundo - Roma La Sapienza


The seminar aims to show some usage of complex networks analysis for modeling financial data. The main focus is going to be on three applications

-A copula approach to cross-ownership of companies
-Herding in mutual funds
-Assessing the impact of incomplete information on the resilience of financial networks

In details:

-The cross-ownership of companies creates not trivial links among them.
Within this respect, the diversification is intended to describe the holdings;
and the integration represents the number of other companies that hold the shares. A high integration allows to spread fluctuations on the other companies, but it reduces the amount of profit to be kept in the company; a high diversification allows to spread the sources of risk, but at the same time it increases the probability to be exposed to fluctuations of other companies.

A copula approach for the detection of the most instable network topologies gives the results for the interaction among integration and diversification. A case study is used to outline the method.

- Herding in mutual funds

Some previous studies were emphasizing that correlations among stocks were loose during expansion periods of the market; and that they were stronger during recessions. Does it hold for mutual funds? We are going to build the network of mutual funds through the correlation network and to insert in the regression of the herding the centrality measures as explanatory variables. The results show that the behavior of mutual funds is just the opposite of the stocks.

- Assessing the impact of incomplete information on the resilience of financial networks
The paper faces the problem of the robustness of the network of interbank exposures against the propagation of failure cascades. The available data are retrieved thorugh the BIS database and report only incomplete information, and show a core-periphery structure. A model of financial contagion is set up to estimate the width and length of the cascades, both in real and simulated data, that insert some percentages of the missing links. Simulations show that the network is far from the worst scenario for the propagation of contagions, and that the detection of the missing links is not trivial in the overall dynamic.



R. Cerqueti, G. Rotundo, M. Ausloos (2018) Investigating the configurations in cross-shareholding: a joint copula, Entropy 2018, 20, 134; doi:10.3390/e20020134 www.mdpi.

A. M. D'Arcangelis, G. Rotundo (2019) Complex networks analysis of herding in mutual funds (preprint)

M. Cinelli, G. Fortunato, A. Iovanella, G. Rotundo, (2019) Assessing the impact of incomplete information on the resilience of financial networks, submitted.

Silvia Romagnoli

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