Ripples on financial networks

References

• Acemoglu, D., V. M. Carvalho, A. Ozdaglor, and A. Tahbaz-Salehi. 2012. “The Network Origin of Aggregate Fluctuations.” Econometrica 80: 1977–2016.
   Web of Science ®Google Scholar
• Acemoglu, D., A. Ozdaglar, and A. Tahbaz-Salehi. 2015. “Systemic Risk and Stability in Financial Networks.” American Economic Review 105 (2): 564–608.
   PubMed Web of Science ®Google Scholar
• Acemoglu, D., A. Ozdaglar, and A. Tahbaz-Salehi. 2016. “Networks, shocks, and systemic risk.” In Handbook of Network Economics, ed. Yann Bramoullé, Andrea Galeotti, and Brian Rogers. Oxford University Press.
   Google Scholar
• Banz, R. W.. 1981. “The Relationship Between Return and Market Value of Common Stocks.” Journal of Financial Economics 9 (1): 3–18.
   Web of Science ®Google Scholar
• Barigozzi, M., and M. Hallin. 2017a. “Generalized Dynamic Factor Models and Volatilities: Estimation and Forecasting.” Journal of Econometrics 201 (2): 307–321.
   Web of Science ®Google Scholar
• Barigozzi, M., and M. Hallin. 2017b. “A Network Analysis of The Volatility of High Dimensional Financial Series.” Journal of the Royal Statistical Society: Series C (Applied Statistics) 66 (3): 581–605.
   Web of Science ®Google Scholar
• Benzi, M., and C. Klymko. 2013. “A Matrix Analysis of Different Centrality Measures.” arXiv preprint arXiv:1312.6722, p. 37.
   Google Scholar
• Bonacich, P.. 1987. “Power and Centrality: A Family of Measures.” American Journal of Sociology 92 (5): 1170–1182.
   Web of Science ®Google Scholar
• Bonanno, G., G. Caldarelli, F. Lillo, S. Miccichè, N. Vandewalle, and R. N. Mantegna. 2004. “Networks of Equities in Financial Markets.” European Physical Journal B 38: 363–371.
   Web of Science ®Google Scholar
• Bouchaud, J.-P., and M. Potters. 2003. Theory of Financial Risk and Derivative Pricing: From Statistical Physics to Risk Management. New York: Cambridge university press.
   Google Scholar
• Cohen, L., and A. Frazzini. 2008. “Economic Links and Predictable Returns.” The Journal of Finance 63 (4): 1977–2011.
   Web of Science ®Google Scholar
• Corsi, F., F. Lillo, D. Pirino, and L. Trapin. 2018. “Measuring the Propagation of Financial Distress with Granger–Causality Tail Risk Networks.” Journal of Financial Stability 38: 18–36.
   Web of Science ®Google Scholar
• Demirer, M., F. X. Diebold, L. Liu, and K. Yilmaz. 2017. “Estimating Global Bank Network Connectedness.” Journal of Applied Econometrics 33 (1): 1–15.
   Web of Science ®Google Scholar
• Dessaint, O., T. Foucault, L. Frésard, and A. Matray. 2018. “Noisy Stock Prices and Corporate Investment.” Review of Financial Studies (forthcoming) 32 (7): 2625–2672.
   Web of Science ®Google Scholar
• Diebold, F. X., and K. Yilmaz. 2008. “Macroeconomic Volatility and Stock Market Volatility, Worldwide.” Technical report, National Bureau of Economic Research.
   Google Scholar
• Diebold, F. X., and K. Yılmaz. 2014. “On The Network Topology of Variance Decompositions: Measuring the Connectedness of Financial Firms.” Journal of Econometrics 182 (1): 119–134.
   Web of Science ®Google Scholar
• Diebold, F. X., and K. Yilmaz. 2015a. Financial and Macroeconomic Connectedness: A Network Approach to Measurement and Monitoring. New York: Oxford University Press.
   Google Scholar
• Diebold, F. X., and K. Yilmaz. 2015b. “Trans-Atlantic Equity Volatility Connectedness: US and European Financial Institutions, 2004–2014.” Journal of Financial Econometrics 14 (1): 81–127.
   Web of Science ®Google Scholar
• Dong, Z., H. An, S. Liu, Z. Li, and M. Yuan. 2020. “Research on the Time-Varying Network Structure Evolution of the Stock Indices of the BRICS Countries Based on Fluctuation Correlation, 2004–2014.” International Review of Economics & Finance 69: 63–74.
   Web of Science ®Google Scholar
• Engle, R., and S. Figlewski. 2014. “Modeling the Dynamics of Correlations Among Implied Volatilities.” Review of Finance 19 (3): 991–1018.
   Web of Science ®Google Scholar
• Fama, E. F., and K. R. French. 1992. “The Cross-Section of Expected Stock Returns.” Journal of Finance 47 (2): 427–465.
   Web of Science ®Google Scholar
• Foucault, T., and L. Fresard. 2014. “Learning From Peers' Stock Prices and Corporate Investment.” Journal of Financial Economics 111 (3): 554–577.
   Web of Science ®Google Scholar
• Garman, M. B., and M. J. Klass. 1980. “On the Estimation of Security Price Volatilities From Historical Data.” Journal of Business 53: 67–78.
   Web of Science ®Google Scholar
• Geraci, M. V., and J. -Y. Gnabo. 2018. “Measuring Interconnectedness Between Financial Institutions with Bayesian Time-Varying Vector Autoregressions.” Journal of Financial and Quantitative Analysis 53 (3): 1371–1390.
   Web of Science ®Google Scholar
• Gower, J. C.. 1966. “Some Distance Properties of Latent Root and Vector Methods Used in Multivariate Analysis.” Biometrika 53: 325–338.
   Web of Science ®Google Scholar
• Hameed, A., R. Morck, J. Shen, and B. Yeung. 2015. “Information, Analysts, and Stock Return Comovement.” The Review of Financial Studies 28 (11): 3153–3187.
   Web of Science ®Google Scholar
• Harvey, C. R., Y. Liu, and H. Zhu. 2016. “…and The Cross-Section of Expected Returns.” The Review of Financial Studies 29 (1): 5–68.
   Web of Science ®Google Scholar
• Hsu, N.-J., H.-L. Hung, and Y.-M. Chang. 2008. “Subset Selection for Vector Autoregressive Processes Using Lasso.” Computational Statistics & Data Analysis 52 (7): 3645–3657.
   Web of Science ®Google Scholar
• Hué, S., Y. Lucotte, and S. Tokpavi. 2019. “Measuring Network Systemic Risk Contributions: A Leave-One-Out Approach.” Journal of Economic Dynamics and Control 100: 86–114.
   Web of Science ®Google Scholar
• Hüser, A.-C., G. Hałaj, C. Kok, C. Perales, and A. van der Kraaij. 2018. “The Systemic Implications of Bail-In: A Multi-Layered Network Approach.” Journal of Financial Stability 38: 81–97.
   Web of Science ®Google Scholar
• Kilian, Lutz, and Helmut Lütkepohl. 2017. Structural Vector Autoregressive Analysis. 1st ed. Cambridge: Cambridge University Press.
   Google Scholar
• Kreyszig, E.. 2015. Advanced Engineering Mathematics. 10th ed. Hoboken: Wiley.
   Google Scholar
• Kumar, S., T. Di Matteo, and A. S. Chakrabarti. 2020. “Disentangling Shock Diffusion on Complex Networks: Identification Through Graph Planarity.” Journal of Complex Networks 8 (3): cnaa023.
   Web of Science ®Google Scholar
• Mantegna, R. N.. 1999. “Hierarchical Structure in Financial Markets.” The European Physical Journal B-Condensed Matter and Complex Systems 11 (1): 193–197.
   Google Scholar
• Marčenko, V. A., and L. A. Pastur. 1967. “Distribution of Eigenvalues for Some Sets of Random Matrices.” Mathematics of the USSR-Sbornik 1 (4): 457.
   Google Scholar
• Mullaly, A. R.. 2008. “Examining the State of The Domestic Automobile Industry.” Hearing, United States Senate Committee on Banking, Housing, and Urban Affairs 2: 25.
   Google Scholar
• Novy-Marx, R.. 2013. “The Other Side of Value: The Gross Profitability Premium.” Journal of Financial Economics 108 (1): 1–28.
   Web of Science ®Google Scholar
• Plerou, V., P. Gopikrishnan, B. Rosenow, L. A. N. Amaral, T. Guhr, and H. E. Stanley. 2002. “Random Matrix Approach to Cross Correlations in Financial Data.” Physical Review E 65: 066126.
   Web of Science ®Google Scholar
• Plosser, C. I.. 2009, March. Redesigning financial system regulation. In a speech at the New York University Conference “Restoring Financial Stability: How to Repair a Failed System”.
   Google Scholar
• Pozzi, F., T. Di Matteo, and T. Aste. 2013. “Spread of Risk Across Financial Markets: Better to Invest in The Peripheries.” Scientific Reports 3: 1665.
   PubMed Web of Science ®Google Scholar
• Sharma, K., B. Gopalakrishnan, A. S. Chakrabarti, and A. Chakraborti. 2017. “Financial Fluctuations Anchored to Economic Fundamentals: A Mesoscopic Network Approach.” Scientific Reports 7 (1): 8055.
   PubMedGoogle Scholar
• Tibshirani, R.. 1996. “Regression Shrinkage and Selection Via the Lasso.” Journal of the Royal Statistical Society Series B (Methodological) 58 (1): 267–288.
   Web of Science ®Google Scholar
• Tumminello, M., T. Di Matteo, T. Aste, and R. N. Mantegna. 2007. “Correlation Based Networks of Equity Returns Sampled At Different Time Horizons.” The European Physical Journal B 55 (2): 209–217.
   Web of Science ®Google Scholar
• Tumminello, M., F. Lillo, and R. N. Mantegna. 2010. “Correlation, Hierarchies, and Networks in Financial Markets.” Journal of Economic Behavior & Organization 75 (1): 40–58.
   Web of Science ®Google Scholar
• Vassalou, M., and Y. Xing. 2004. “Default Risk in Equity Returns.” The Journal of Finance 59 (2): 831–868.
   Web of Science ®Google Scholar
• Vidal-Tomás, D., and S. Alfarano. 2020. “An Agent-Based Early Warning Indicator for Financial Market Instability.” Journal of Economic Interaction and Coordination 15 (1): 49–87.
   Web of Science ®Google Scholar
• Zou, H.. 2006. “The Adaptive Lasso and Its Oracle Properties.” Journal of the American Statistical Association 101 (476): 1418–1429.
   Web of Science ®Google Scholar
• Zhang, J., Y. Gao, and S. Cai. 2020. “The Hierarchical Structure of Stock Market in Times of Global Financial Crisis.” Physica A 542: 123542.
   Google Scholar