10 Correlations, Hierarchies, Networks and Clustering
273
128. Sensoy, A., Tabak, B.M.: Dynamic spanning trees in stock market networks: The case of
Asia-Pacific. Phys. A: Stat. Mech. Appl. 414, 387–402 (2014)
129. Smith, R.: The spread of the credit crisis: view from a stock correlation network. J. Korean
Phys. Soc. 54(6), 2460–2463 (2009)
130. Song, D.-M., Tumminello, M., Zhou, W.-X., Mantegna, R.N.: Evolution of worldwide stock
markets, correlation structure, and correlation-based graphs. Phys. Rev. E 84(2), 026108
(2011)
131. Song, W.-M., Di Matteo, T., Aste, T.: Hierarchical information clustering by means of topologically embedded graphs. PLoS One 7(3), e31929 (2012)
132. Song, W.-M., Di Matteo, T., Aste, T.: Nested hierarchies in planar graphs. Discret. Appl.
Math. 159(17), 2135–2146 (2011)
133. Souza, T.T.P., Aste, T.: Predicting future stock market structure by combining social and
financial network information (2018). arXiv:1812.01103
134. Spelta, A.: Financial market predictability with tensor decomposition and links forecast. Appl.
Netw. Sci. 2(1), 7 (2017)
135. Squartini, T., Van Lelyveld, I., Garlaschelli, D.: Early-warning signals of topological collapse
in interbank networks. Sci. Rep. 3, (2013)
136. Stepanov, Y., Rinn, P., Guhr, T., Peinke, J., Schäfer, R.: Stability and hierarchy of quasistationary states: financial markets as an example. J. Stat. Mech.: Theory Exp. 2015(8), P08011
(2015)
137. Takayasu, H.: Practical Fruits of Econophysics. Springer, Berlin (2006)
138. Tang, Y., Xiong, J.J., Jia, Z.-Y., Zhang, Y.-C.: Complexities in financial network topological
dynamics: Modeling of emerging and developed stock markets. Complexity (2018)
139. Tola, V., Lillo, F., Gallegati, M., Mantegna, R.N.: Cluster analysis for portfolio optimization.
J. Econ. Dyn. Control 32(1), 235–258 (2008)
140. Tóth, B., Kertész, J.: Accurate estimator of correlations between asynchronous signals. Phys.
A: Stat. Mech. Appl. 388(8), 1696–1705 (2009)
141. Chengyi, T.: Cointegration-based financial networks study in chinese stock market. Phys. A:
Stat. Mech. Appl. 402, 245–254 (2014)
142. Tumminello, M., Mantegna, R.N., Lillo, F.: Shrinkage and spectral filtering of correlation
matrices: A comparison via the Kullback-Leibler distance. Acta Phys. Polonica. Ser. B 39(1),
4079–4088 (2008)
143. Tumminello, M., Aste, T., Di Matteo, T., Mantegna, R.N.: A tool for filtering information in
complex systems. Proc. Natl. Acad. Sci. U. S. A. 102(30), 10421–10426 (2005)
144. Tumminello, M., Coronnello, C., Lillo, F., Micciche, S., Mantegna, R.N.: Spanning trees and
bootstrap reliability estimation in correlation-based networks. Int. J. Bifurcat. Chaos 17(07),
2319–2329 (2007)
145. Tumminello, M., Di Matteo, T., Aste, T., Mantegna, R.N.: Correlation based networks of
equity returns sampled at different time horizons. Eur. Phys. J. B 55(2), 209–217 (2007)
146. Tumminello, M., Lillo, F., Mantegna, R.N.: Hierarchically nested factor model from multivariate data. EPL (Europhysics Letters) 78(3), 30006 (2007)
147. Tumminello, M., Lillo, F., Mantegna, R.N.: Kullback-leibler distance as a measure of the
information filtered from multivariate data. Phys. Rev. E 76(3), 031123 (2007)
148. Tumminello, M., Lillo, F., Mantegna, R.N.: Correlation, hierarchies, and networks in financial
markets. J. Econ. Beh. Organ. 75(1), 40–58 (2010)
149. Tumminello, M., Miccichè, S., Lillo, F., Piilo, J., Mantegna, R.N.: Statistically validated
networks in bipartite complex systems. PloS One 6(3), e17994 (2011)
150. Vandewalle, N., Brisbois, F., Tordoir, X., et al.: Non-random topology of stock markets.
Quantitative Finance 1(3), 372–374 (2001)
151. V` yrost, T., Lyócsa, V., Baumöhl, E.: Granger causality stock market networks: Temporal
proximity and preferential attachment. Phys. A: Stat. Mech. Appl. 427, 262–276 (2015)
152. Whiteley, N.: Dynamic time series clustering via volatility change-points (2019).
arXiv:1906.10372
153. Wu, L.: Centrality of the Supply Chain Network (2015)
273
128. Sensoy, A., Tabak, B.M.: Dynamic spanning trees in stock market networks: The case of
Asia-Pacific. Phys. A: Stat. Mech. Appl. 414, 387–402 (2014)
129. Smith, R.: The spread of the credit crisis: view from a stock correlation network. J. Korean
Phys. Soc. 54(6), 2460–2463 (2009)
130. Song, D.-M., Tumminello, M., Zhou, W.-X., Mantegna, R.N.: Evolution of worldwide stock
markets, correlation structure, and correlation-based graphs. Phys. Rev. E 84(2), 026108
(2011)
131. Song, W.-M., Di Matteo, T., Aste, T.: Hierarchical information clustering by means of topologically embedded graphs. PLoS One 7(3), e31929 (2012)
132. Song, W.-M., Di Matteo, T., Aste, T.: Nested hierarchies in planar graphs. Discret. Appl.
Math. 159(17), 2135–2146 (2011)
133. Souza, T.T.P., Aste, T.: Predicting future stock market structure by combining social and
financial network information (2018). arXiv:1812.01103
134. Spelta, A.: Financial market predictability with tensor decomposition and links forecast. Appl.
Netw. Sci. 2(1), 7 (2017)
135. Squartini, T., Van Lelyveld, I., Garlaschelli, D.: Early-warning signals of topological collapse
in interbank networks. Sci. Rep. 3, (2013)
136. Stepanov, Y., Rinn, P., Guhr, T., Peinke, J., Schäfer, R.: Stability and hierarchy of quasistationary states: financial markets as an example. J. Stat. Mech.: Theory Exp. 2015(8), P08011
(2015)
137. Takayasu, H.: Practical Fruits of Econophysics. Springer, Berlin (2006)
138. Tang, Y., Xiong, J.J., Jia, Z.-Y., Zhang, Y.-C.: Complexities in financial network topological
dynamics: Modeling of emerging and developed stock markets. Complexity (2018)
139. Tola, V., Lillo, F., Gallegati, M., Mantegna, R.N.: Cluster analysis for portfolio optimization.
J. Econ. Dyn. Control 32(1), 235–258 (2008)
140. Tóth, B., Kertész, J.: Accurate estimator of correlations between asynchronous signals. Phys.
A: Stat. Mech. Appl. 388(8), 1696–1705 (2009)
141. Chengyi, T.: Cointegration-based financial networks study in chinese stock market. Phys. A:
Stat. Mech. Appl. 402, 245–254 (2014)
142. Tumminello, M., Mantegna, R.N., Lillo, F.: Shrinkage and spectral filtering of correlation
matrices: A comparison via the Kullback-Leibler distance. Acta Phys. Polonica. Ser. B 39(1),
4079–4088 (2008)
143. Tumminello, M., Aste, T., Di Matteo, T., Mantegna, R.N.: A tool for filtering information in
complex systems. Proc. Natl. Acad. Sci. U. S. A. 102(30), 10421–10426 (2005)
144. Tumminello, M., Coronnello, C., Lillo, F., Micciche, S., Mantegna, R.N.: Spanning trees and
bootstrap reliability estimation in correlation-based networks. Int. J. Bifurcat. Chaos 17(07),
2319–2329 (2007)
145. Tumminello, M., Di Matteo, T., Aste, T., Mantegna, R.N.: Correlation based networks of
equity returns sampled at different time horizons. Eur. Phys. J. B 55(2), 209–217 (2007)
146. Tumminello, M., Lillo, F., Mantegna, R.N.: Hierarchically nested factor model from multivariate data. EPL (Europhysics Letters) 78(3), 30006 (2007)
147. Tumminello, M., Lillo, F., Mantegna, R.N.: Kullback-leibler distance as a measure of the
information filtered from multivariate data. Phys. Rev. E 76(3), 031123 (2007)
148. Tumminello, M., Lillo, F., Mantegna, R.N.: Correlation, hierarchies, and networks in financial
markets. J. Econ. Beh. Organ. 75(1), 40–58 (2010)
149. Tumminello, M., Miccichè, S., Lillo, F., Piilo, J., Mantegna, R.N.: Statistically validated
networks in bipartite complex systems. PloS One 6(3), e17994 (2011)
150. Vandewalle, N., Brisbois, F., Tordoir, X., et al.: Non-random topology of stock markets.
Quantitative Finance 1(3), 372–374 (2001)
151. V` yrost, T., Lyócsa, V., Baumöhl, E.: Granger causality stock market networks: Temporal
proximity and preferential attachment. Phys. A: Stat. Mech. Appl. 427, 262–276 (2015)
152. Whiteley, N.: Dynamic time series clustering via volatility change-points (2019).
arXiv:1906.10372
153. Wu, L.: Centrality of the Supply Chain Network (2015)