Acemoglu, D., A. Ozdaglar, and A. Tahbaz-Salehi (2010). Cascades in Networks and Aggregate Volatility. Working Paper 16516, National Bureau of Economic Research.
Acemoglu, D., A. Ozdaglar, and A. Tahbaz-Salehi (2015). Systemic Risk and Stability in Financial Networks. The American Economic Review 105(2), 564–608.
Acharya, V. V., L. H. Pedersen, T. Philippon, and M. Richardson (2017). Measuring Systemic Risk. The Review of Financial Studies 30(1), 2–47.
Acharya, V., R. Engle, and M. Richardson (2012). Capital Shortfall: A New Approach to Ranking and Regulating Systemic Risks. American Economic Review 102(3), 59–64.
Alizadeh, S., M. W. Brandt, and F. X. Diebold (2002). Range-Based Estimation of Stochastic Volatility Models. The Journal of Finance 57(3), 1047–1091.
Allen, F., A. Babus, and E. Carletti (2012). Asset commonality, debt maturity and systemic risk. Journal of Financial Economics 104(3), 519–534.
- Anderson, B. D. and M. Deistler (2008a). Generalized linear dynamic factor models-A structure theory.
Paper not yet in RePEc: Add citation now
- Anderson, B. D. and M. Deistler (2008b). Properties of zero-free transfer function matrices. SICE Journal of Control, Measurement and System Integration 1, 284–292.
Paper not yet in RePEc: Add citation now
Bai, J. and S. Ng (2002). Determining the Number of Factors in Approximate Factor Models. Econometrica 70(1), 191–221.
Balke, N. S. and M. E. Wohar (2002). Low-Frequency Movements in Stock Prices: A State-Space Decomposition. The Review of Economics and Statistics 84(4), 649–667.
- Bandi, F. M. and A. Tamoni (2017). The Horizon of Systematic Risk: A New Beta Representation. SSRN Scholarly Paper ID 2337973, Rochester, NY.
Paper not yet in RePEc: Add citation now
Barigozzi, M. and M. Hallin (2017). 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.
Barigozzi, M., H. Cho, and P. Fryzlewicz (2018). Simultaneous multiple change-point and factor analysis for high-dimensional time series. Journal of Econometrics 206, 187–225.
Barigozzi, M., M. Hallin, and S. Soccorsi (2018). Identification of Global and Local Shocks in International Financial Markets via General Dynamic Factor Models. Journal of Financial Econometrics 33, 625–642.
Barrero, J. M., N. Bloom, and I. Wright (2017). Short and Long Run Uncertainty. Working Paper 23676, National Bureau of Economic Research.
- BarunıÌÂk, J. and T. KřehlıÌÂk (2018). Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk. Journal of Financial Econometrics 16, 271–296.
Paper not yet in RePEc: Add citation now
Bates, B. J., M. Plagborg-Møller, J. H. Stock, and M. W. Watson (2013). Consistent factor estimation in dynamic factor models with structural instability. Journal of Econometrics 177(2), 289–304.
Baxter, M. and R. G. King (1999). Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series. The Review of Economics and Statistics 81(4), 575–593.
Benoit, S., J.-E. Colliard, C. Hurlin, and C. PeÃŒÂrignon (2017). Where the Risks Lie: A Survey on Systemic Risk. Review of Finance 21(1), 109–152.
Billio, M., M. Getmansky, A. W. Lo, and L. Pelizzon (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors. Journal of Financial Economics 104(3), 535–559.
- Brockwell, P. J. and R. A. Davis (1991). Time Series: Theory and Methods (2 ed.). Springer Series in Statistics. New York: Springer-Verlag.
Paper not yet in RePEc: Add citation now
Brownlees, C. and R. F. Engle (2017). SRISK: A Conditional Capital Shortfall Measure of Systemic Risk. The Review of Financial Studies 30(1), 48–79.
Brownlees, C. T. and G. M. Gallo (2010). Comparison of Volatility Measures: a Risk Management Perspective. Journal of Financial Econometrics 8(1), 29–56.
- Dahlhaus, R. (1997). Fitting time series models to nonstationary processes. The Annals of Statistics 25(1), 1–37.
Paper not yet in RePEc: Add citation now
Dahlhaus, R. (2009). Local inference for locally stationary time series based on the empirical spectral measure. Journal of Econometrics 151(2), 101–112.
Del Negro, M. and C. Otrok (2008). Dynamic Factor Models with Time-Varying Parameters: Measuring Changes in International Business Cycles. SSRN Scholarly Paper ID 1136163, Rochester, NY.
Dew-Becker, I. and S. Giglio (2016). Asset Pricing in the Frequency Domain: Theory and Empirics.
Diebold, F. X. and K. Yilmaz (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics 182(1), 119–134.
Eichler, M., G. Motta, and R. von Sachs (2011). Fitting dynamic factor models to non-stationary time series. Journal of Econometrics 163(1), 51–70.
- Engle, R. F. (2010). The Risk that Risk Will Change. SSRN Scholarly Paper ID 1539166, Rochester, NY.
Paper not yet in RePEc: Add citation now
- Fiedler, M. (1973). Algebraic connectivity of graphs. Czechoslovak Mathematical Journal 23(98), 298–305.
Paper not yet in RePEc: Add citation now
Forni, M., A. Giovannelli, M. Lippi, and S. Soccorsi (2018). Dynamic factor model with infinitedimensional factor space: Forecasting. Journal of Applied Econometrics 33(5), 625–642.
Forni, M., D. Giannone, M. Lippi, and L. Reichlin (2009). Opening the black box: Structural factor models with large cross sections. Econometric Theory 25(5), 1319–1347.
Forni, M., M. Hallin, M. Lippi, and L. Reichlin (2000). The generalized dynamic-factor model: Identification and estimation. Review of Economics and Statistics 82(4), 540–554.
Forni, M., M. Hallin, M. Lippi, and P. Zaffaroni (2015). Dynamic factor models with infinitedimensional factor spaces: One-sided representations. Journal of Econometrics 185(2), 359–371.
Forni, M., M. Hallin, M. Lippi, and P. Zaffaroni (2017). Dynamic factor models with infinitedimensional factor spaces: Asymptotic analysis. Journal of Econometrics 199(1), 74–92.
Hallin, M. and M. Lippi (2013). Factor models in high-dimensional time seriesâĂŤA time-domain approach. Stochastic Processes and their Applications 123(7), 2678–2695.
Hallin, M. and R. Liška (2007). Determining the Number of Factors in the General Dynamic Factor Model. Journal of the American Statistical Association 102(478), 603–617.
- In Proceedings of the 47th IEEE Conference on Decision and Control, pp. 1980–1985.
Paper not yet in RePEc: Add citation now
Korobilis, D. and K. Yilmaz (2018). Measuring Dynamic Connectedness with Large Bayesian VAR Models. SSRN Scholarly Paper ID 3099725, Rochester, NY.
- Mikkelsen, J. G., E. Hillebrand, and G. Urga (2018). Consistent estimation of time-varying loadings in high-dimensional factor models. Journal of Econometrics 208(2), 535–562.
Paper not yet in RePEc: Add citation now
Motta, G., C. M. Hafner, and R. von Sachs (2011). Locally stationary factor models: Identification and nonparametric estimation. Econometric Theory 27(6), 1279–1319.
- Neumann, M. H. and R. von Sachs (1997). Wavelet thresholding in anisotropic function classes and application to adaptive estimation of evolutionary spectra. The Annals of Statistics 25(1), 38–76.
Paper not yet in RePEc: Add citation now
- Newman, M. E. (2008). The mathematics of networks. The new palgrave encyclopedia of economics 2(2008), 1–12.
Paper not yet in RePEc: Add citation now
Ortu, F., A. Tamoni, and C. Tebaldi (2013). Long-Run Risk and the Persistence of Consumption Shocks. The Review of Financial Studies 26(11), 2876–2915.
Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. The Journal of Business 53(1), 61–65.
- Pothen, A., H. D. Simon, and K.-P. Liou (1990). Partitioning sparse matrices with eigenvectors of graphs. SIAM journal on matrix analysis and applications 11(3), 430–452.
Paper not yet in RePEc: Add citation now
RodrıÌÂguez-Poo, J. M. and O. Linton (2001). Nonparametric factor analysis of residual time series. Test 10(1), 161–182.
Stock, J. H. and M. W. Watson (2002). Forecasting Using Principal Components From a Large Number of Predictors. Journal of the American Statistical Association 97(460), 1167–1179.
Su, L. and X. Wang (2017). On time-varying factor models: Estimation and testing. Journal of Econometrics 198(1), 84–101.
- Vershynin, R. (2018). High dimensional probability. An introduction with applications in Data Science. Cambridge University Press.
Paper not yet in RePEc: Add citation now
- von Luxburg, U. (2007). A tutorial on spectral clustering. Statistics and Computing 17(4), 395–416.
Paper not yet in RePEc: Add citation now