Financial networks have been the object of intense quantitative analysis during the last few decades. Their structure and the dynamical processes on top of them are of utmost importance to understand the emergent collective behavior behind economic and financial crises. In this paper, we propose a stylized model to understand the “domino effect” of distress in client–supplier networks. We provide a theoretical analysis of the model, and we apply it to several synthetic networks and a real customer–supplier network, supplied by one of the largest banks in Europe. Besides, the proposed model allows us to investigate possible scenarios for the functioning of the financial distress propagation and to assess the economic health of the full network. The main novelty of this model is the combination of two stochastic terms: an additive noise, accounting by the capability of trading and paying obligations, and a multiplicative noise representing the variations of the market. Both parameters are crucial to determining the maximum default probability and the diffusion process characteristics.

2.
D. M.
Gale
and
S.
Kariv
,
Am. Econ. Rev.
97
,
99
(
2007
).
3.
M.
Timmer
,
E.
Dietzenbacher
,
B.
Los
,
R.
Stehrer
, and
G.
de Vries
,
Rev. Int. Econ.
23
,
575
605
(
2015
).
4.
5.
A.
Barja
,
A.
Martínez
,
A.
Arenas
,
P.
Fleurquin
,
J.
Nin
,
J.
Ramasco
, and
E.
Tomás
,
EPJ Data Sci.
8
,
32
(
2019
).
6.
F.
Schweitzer
,
G.
Fagiolo
,
D.
Sornette
,
F.
Vega-Redondo
,
A.
Vespignani
, and
D.
White
,
Science
325
,
422
(
2009
).
7.
A. H.
AG
and
R.
May
,
Nature
469
,
351
355
(
2011
).
8.
S.
Battiston
,
M.
Puliga
,
R.
Kaushik
,
P.
Tasca
, and
G.
Caldarelli
,
Sci. Rep.
2
,
541
(
2012
).
9.
J.
Nin
and
E.
Tomás
, “Default propagation in customer-supplier networks,”
J. Ambient Intell. Hum. Comput.
(published online
2019
).
10.
M. A.
Serrano
and
M.
Boguñá
,
Phys. Rev. E
68
,
015101
(
2003
).
11.
D.
Garlaschelli
,
S.
Battiston
,
M.
Castri
,
V. D.
Servedio
, and
G.
Caldarelli
,
Physica A
350
,
491
(
2005
).
12.
M. O.
Jackson
and
A.
Watts
,
J. Econ. Theory
106
,
265
(
2002
).
13.
R.
Coelho
,
Z.
Neda
,
J. J.
Ramasco
, and
M. A.
Santos
,
Physica A
353
,
515
(
2005
).
14.
J.-P.
Onnela
,
K.
Kaski
, and
J.
Kertész
,
Eur. Phys. J. B
38
,
353
(
2004
).
15.
M.
Kosfeld
,
Rev. Netw. Econ.
3
,
20
(
2004
).
16.
J.
Lorenz
,
S.
Battiston
, and
F.
Schweitzer
,
Eur. Phys. J. B
71
,
441
(
2009
).
17.
F.
Caccioli
,
P.
Barucca
, and
T.
Kobayashi
,
J. Comput. Soc. Sci.
1
,
81
114
(
2018
).
18.
R.
Burkholz
,
H.
Herrmann
, and
F.
Schweitzer
,
Sci. Rep.
8
,
6878
(
2018
).
19.
G.
Caldarelli
,
S.
Battiston
,
D.
Garlaschelli
, and
M.
Catanzaro
, “Emergence of complexity in financial networks,” in Complex Networks, edited by E. Ben-Naim, H. Frauenfelder, and Z. Toroczkai (Springer, 2004), pp. 399–423.
21.
P.
Gai
and
S.
Kapadia
,
Proc. R. Soc. London, Ser. A
466
,
2401
(
2010
).
22.
S.
Battiston
and
G.
Caldarelli
, “
J. Financ. Manage. Mark. Inst.
2
,
129
(
2013
).
23.
H.
Watanabe
,
H.
Takayasu
, and
M.
Takayasu
,
New J. Phys.
14
,
043034
(
2012
).
24.
H.
Krichene
,
A.
Chakraborty
,
H.
Inoue
, and
Y.
Fujiwara
,
PLoS One
12
,
e0186467
(
2017
).
25.
E.
Letizia
and
F.
Lillo
,
EPJ Data Sci.
8
,
21
(
2019
).
26.
T.
Roukny
,
H.
Bersini
,
H.
Pirotte
,
G.
Caldarelli
, and
S.
Battiston
,
Sci. Rep.
3
,
2759
(
2013
).
27.
M. O.
Jackson
and
A.
van den Nouweland
,
Games Econ. Behav.
51
,
420
(
2005
).
28.
H.
Amini
,
R.
Cont
, and
A.
Minca
,
Math. Finance
26
,
329
(
2013
).
29.
P.
Glasserman
and
H. P.
Young
,
J. Bank. Finance
50
,
383
(
2015
).
30.
M.
Bardoscia
,
S.
Battiston
,
F.
Caccioli
, and
G.
Caldarelli
,
Sci. Rep.
8
,
14416
(
2017
).
31.
F.
Corsi
,
F.
Lillo
,
D.
Pirino
, and
L.
Trapine
,
J. Financ. Stab.
38
,
18
(
2018
).
32.
K. J.
Mizgier
,
S. M.
Wagner
, and
J. A.
Holyst
,
Int. J. Prod. Econ.
135
,
14
23
(
2009
).
33.
P.
Glasserman
and
H.
Young
,
J. Econ. Lit.
54
,
779
831
(
2016
).
34.
L.
Veraart
,
Math. Finance
30
,
705
(
2020
).
35.
J.
Bouchaud
and
M.
Mézard
,
Physica A
282
,
536
545
(
2000
).
36.
C.
Gardiner
,
Stochastic Methods: A Handbook for the Natural and Social Sciences
, 4th ed. (
Springer
,
Berlin
,
2009
).
37.
R.
Toral
and
P.
Colet
,
Stochastic Numerical Methods: An Introduction for Students and Scientists
(
John Wiley & Sons
,
2014
).
38.
G.
Iori
,
S.
Jafarey
, and
F. G.
Padilla
,
J. Econ. Behav. Organ.
61
,
525
(
2006
).
39.
G.
Tedeschi
,
A.
Mazloumian
,
M.
Gallegati
, and
D.
Helbing
,
PLoS One
7
,
e52749
(
2013
).
You do not currently have access to this content.