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from the cds market. Georgetown McDonough School Bus. Res. Paper (3078752) (2017)
2. Almog, A., Shmueli, E.: Structural entropy: Monitoring correlation-based networks over time
with application to financial markets. Sci. Rep. 9(1), 1–13 (2019)
3. Aste, T., Di Matteo, T., Hyde, S.T.: Complex networks on hyperbolic surfaces. Phys. A: Stat.
Mech. Appl. 346(1), 20–26 (2005)
4. Avellaneda, M.: Hierarchical PCA and applications to portfolio management. Revista mexicana de economía y finanzas 15(1), 1–16 (2020)
5. Baitinger, E., Papenbrock, J.: Interconnectedness Risk and Active Portfolio Management
(20160
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information-theoretic perspective (2017)
7. Baltakys, K., Kanniainen, J., Pedreschi, D., Lillo, F., et al.: Clusters of investors around initial
public offering. Tech. Rep. (2019) arXiv. org
8. Baltakys, K., Kanniainen, J., Emmert-Streib, F.: Multilayer aggregation with statistical validation: Application to investor networks. Sci. Rep. 8(1), 8198 (2018)
9. Barbi, A.Q., Prataviera, G.A.: Nonlinear dependencies on brazilian equity network from
mutual information minimum spanning trees (2017). arXiv:1711.06185
10. Barfuss, W., Massara, G.P., Di Matteo, T., Aste, T.: Parsimonious modeling with information
filtering networks. Phys. Rev. E 94(6), 062306 (2016)
11. Battiston, S., Farmer, J.D., Flache, A., Garlaschelli, D., Haldane, A.G., Heesterbeek, H.,
Hommes, C., Jaeger, C., May, R., Scheffer, M.: Complexity theory and financial regulation.
Science 351(6275), 818–819 (2016)
12. Bhattacharjee, B., Shafi, M., Acharjee, A.: Investigating the evolution of linkage dynamics
among equity markets using network models and measures: The case of asian equity market
integration. Data 2(4), 41 (2017)
13. Bhattacharjee, B., Shafi, M., Acharjee, A.: Network mining based elucidation of the dynamics of cross-market clustering and connectedness in asian region: An mst and hierarchical
clustering approach. J. King Saud Univ.-Comput. Inf, Sci (2017)
14. Billio, M., Getmansky, M., Lo, A.W., Pelizzon, L.: Econometric measures of connectedness
and systemic risk in the finance and insurance sectors. J. Financial Econ. 104(3), 535–559
(2012)
15. Bonanno, G., Lillo, F., Mantegna, R.N., et al.: High-frequency cross-correlation in a set of
stocks. Quantitative Finance 1(1), 96–104 (2001)
16. Bonanno, G., Caldarelli, G., Lillo, F., Mantegna, R.N.: Topology of correlation-based minimal
spanning trees in real and model markets. Phys. Rev. E 68(4), 046130 (2003)
17. Borghesi, C., Marsili, M., Miccichè, S.: Emergence of time-horizon invariant correlation
structure in financial returns by subtraction of the market mode. Phys. Rev. E 76(2), 026104
(2007)
18. Borysov, P., Hannig, J., Marron, J.S.: Asymptotics of hierarchical clustering for growing
dimension. J. Mult. Anal. 124, 465–479 (2014)
19. Brechmann, E.C. et al.: Hierarchical Kendall copulas and the modeling of systemic and
operational risk. Ph.D. thesis, Universitätsbibliothek der TU München (2013)
20. Brida, J.G., Risso, W.A.: Multidimensional minimal spanning tree: The dow jones case. Phys.
A: Stat. Mech. Appl. 387(21), 5205–5210 (2008)
21. Bun, J., Allez, R., Bouchaud, J.-P., Potters, M.: Rotational invariant estimator for general
noisy matrices. IEEE Trans. Inf. Theory 62(12), 7475–7490 (2016)
22. Bun, J., Bouchaud, J.-P., Potters, M.: Cleaning large correlation matrices: tools from random
matrix theory. Phys. Rep. 666, 1–109 (2017)
23. Buonocore, R.J., Mantegna, R.N., Di Matteo, T.: On the interplay between multiscaling and
average cross-correlation (2018). arXiv:1802.01113
G. Marti et al.
References
1. Agca, S., Babich, V., Birge, J.R., Wu, J.: Credit risk propagation along supply chains: Evidence
from the cds market. Georgetown McDonough School Bus. Res. Paper (3078752) (2017)
2. Almog, A., Shmueli, E.: Structural entropy: Monitoring correlation-based networks over time
with application to financial markets. Sci. Rep. 9(1), 1–13 (2019)
3. Aste, T., Di Matteo, T., Hyde, S.T.: Complex networks on hyperbolic surfaces. Phys. A: Stat.
Mech. Appl. 346(1), 20–26 (2005)
4. Avellaneda, M.: Hierarchical PCA and applications to portfolio management. Revista mexicana de economía y finanzas 15(1), 1–16 (2020)
5. Baitinger, E., Papenbrock, J.: Interconnectedness Risk and Active Portfolio Management
(20160
6. Baitinger, E., Papenbrock, J.: Interconnectedness risk and active portfolio management: The
information-theoretic perspective (2017)
7. Baltakys, K., Kanniainen, J., Pedreschi, D., Lillo, F., et al.: Clusters of investors around initial
public offering. Tech. Rep. (2019) arXiv. org
8. Baltakys, K., Kanniainen, J., Emmert-Streib, F.: Multilayer aggregation with statistical validation: Application to investor networks. Sci. Rep. 8(1), 8198 (2018)
9. Barbi, A.Q., Prataviera, G.A.: Nonlinear dependencies on brazilian equity network from
mutual information minimum spanning trees (2017). arXiv:1711.06185
10. Barfuss, W., Massara, G.P., Di Matteo, T., Aste, T.: Parsimonious modeling with information
filtering networks. Phys. Rev. E 94(6), 062306 (2016)
11. Battiston, S., Farmer, J.D., Flache, A., Garlaschelli, D., Haldane, A.G., Heesterbeek, H.,
Hommes, C., Jaeger, C., May, R., Scheffer, M.: Complexity theory and financial regulation.
Science 351(6275), 818–819 (2016)
12. Bhattacharjee, B., Shafi, M., Acharjee, A.: Investigating the evolution of linkage dynamics
among equity markets using network models and measures: The case of asian equity market
integration. Data 2(4), 41 (2017)
13. Bhattacharjee, B., Shafi, M., Acharjee, A.: Network mining based elucidation of the dynamics of cross-market clustering and connectedness in asian region: An mst and hierarchical
clustering approach. J. King Saud Univ.-Comput. Inf, Sci (2017)
14. Billio, M., Getmansky, M., Lo, A.W., Pelizzon, L.: Econometric measures of connectedness
and systemic risk in the finance and insurance sectors. J. Financial Econ. 104(3), 535–559
(2012)
15. Bonanno, G., Lillo, F., Mantegna, R.N., et al.: High-frequency cross-correlation in a set of
stocks. Quantitative Finance 1(1), 96–104 (2001)
16. Bonanno, G., Caldarelli, G., Lillo, F., Mantegna, R.N.: Topology of correlation-based minimal
spanning trees in real and model markets. Phys. Rev. E 68(4), 046130 (2003)
17. Borghesi, C., Marsili, M., Miccichè, S.: Emergence of time-horizon invariant correlation
structure in financial returns by subtraction of the market mode. Phys. Rev. E 76(2), 026104
(2007)
18. Borysov, P., Hannig, J., Marron, J.S.: Asymptotics of hierarchical clustering for growing
dimension. J. Mult. Anal. 124, 465–479 (2014)
19. Brechmann, E.C. et al.: Hierarchical Kendall copulas and the modeling of systemic and
operational risk. Ph.D. thesis, Universitätsbibliothek der TU München (2013)
20. Brida, J.G., Risso, W.A.: Multidimensional minimal spanning tree: The dow jones case. Phys.
A: Stat. Mech. Appl. 387(21), 5205–5210 (2008)
21. Bun, J., Allez, R., Bouchaud, J.-P., Potters, M.: Rotational invariant estimator for general
noisy matrices. IEEE Trans. Inf. Theory 62(12), 7475–7490 (2016)
22. Bun, J., Bouchaud, J.-P., Potters, M.: Cleaning large correlation matrices: tools from random
matrix theory. Phys. Rep. 666, 1–109 (2017)
23. Buonocore, R.J., Mantegna, R.N., Di Matteo, T.: On the interplay between multiscaling and
average cross-correlation (2018). arXiv:1802.01113