[Forum SIS] ISBIS Webinar on The social structure of financial networks (1/12/20)

[Fabrizio Ruggeri]

ISBIS (International Society for Business and Industrial Statistics,
https://www.isbis-isi.org/), one of the seven ISI (International 
Statistical Institute) Associations, is starting its webinar activities
with the first of the webinars presented by Leading Women in Business 
and Industrial Statistics (next lecturers include Bonnie Ray, Kathy Ensor
and Nalini Ravishanker). The series of webinars is a contribution to the 
International Year of Women in Statistics and Data Science (see more at
https://www.isi-web.org/events-and-awards/calendar/iywsds).

More information on ISI and ISBIS webinars (including video of past events) 
is available at https://www.isi-web.org/webinars and 
http://www.isbis-isi.org/webinars.html

Fabrizio Ruggeri
ISBIS President
ISI Vice President

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Title:   	The social structure of financial networks
Date:   	December, 1st, 2020
Time:  	        16.00 - 17.00
Time Zone:	(GMT+01:00) Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna

Panelists:

- Antonietta Mira (Universita' della Svizzera Italiana, Switzerland, and 
  Universita' dell'Insubria, Italy)
- Federica Bianchi (University of Glasgow, UK)

Abstract

Financial markets can be considered as networks where nodes are financial 
institutions and edges are cash flows connecting those institutions. We 
study the temporal evolution of dyadic relationships in the European 
interbank market, as induced by monetary transactions registered in the 
electronic market for interbank deposits (e- MID) during a period of 10 
years (2006–2015). In particular, we keep track of how reciprocal exchange 
patterns have varied with macro events and exogenous shocks and with the 
emergence of the Global Financial Crisis in 2008. The approach adopted 
extends the model of Holland and Leinhardt (JASA, 1981) to a longitudinal 
setting where individuals’ temporal trajectories for the tendency to connect 
and reciprocate transactions are explicitly modelled through splines or 
polynomials, and individual-specific parameters. We estimate the model by 
an iterative algorithm that maximizes the log-likelihood for every ordered 
pair of units. The empirical application shows that the methodology proposed 
may be applied to large networks and represents the process of exchange at 
a fine-grained level.

Although the webinar is free for all, registration is required at the 
following link:

https://attendee.gotowebinar.com/register/1421032328477468939
-- 
Fabrizio Ruggeri                    fabrizio AT mi.imati.cnr.it
CNR IMATI                           tel +39 0223699532
Via Bassini 15                      fax +39 0223699538
I-20133 Milano (Italy)              www.mi.imati.cnr.it/fabrizio