Alter, A. ; Beyer, A. The dynamics of spillover effects during the European sovereign debt turmoil. 2014 J. Bank. Finance. 42 134-153
- Anderson, B. ; Moore, J.B. Optimal Filtering. 1979 :
Paper not yet in RePEc: Add citation now
Antonakakis, N. ; Chatziantoniou, I. ; Gabauer, D. Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. 2020 J. Risk Financ. Manag.. 13 84-
Bańbura, M. ; Giannone, D. ; Lenza, M. Conditional forecasts and scenario analysis with vector autoregressions for large cross-sections. 2015 Int. J. Forecast.. 31 739-756
Bańbura, M. ; Giannone, D. ; Reichlin, L. Large Bayesian vector auto regressions. 2010 J. Appl. Econom.. 25 71-92
Bazzi, M. ; Blasques, F. ; Koopman, S.J. ; Lucas, A. Time-varying transition probabilities for Markov regime switching models. 2017 J. Time Ser. Anal.. 38 458-478
Belmonte, M.A. ; Koop, G. ; Korobilis, D. Hierarchical shrinkage in time-varying parameter models. 2014 J. Forecast.. 33 80-94
Bitto, A. ; Frühwirth-Schnatter, S. Achieving shrinkage in a time-varying parameter model framework. 2019 J. Econom.. 210 75-97
Blasques, F. ; Koopman, S.J. ; Lucas, A. Information-theoretic optimality of observation-driven time series models for continuous responses. 2015 Biometrika. 102 325-343
Blasques, F. ; Koopman, S.J. ; Lucas, A. ; Schaumburg, J. Spillover dynamics for systemic risk measurement using spatial financial time series models. 2016 J. Econom.. 195 211-223
Blasques, F. ; Koopman, S.J. ; Łasak, K. ; Lucas, A. In-sample confidence bands and out-of-sample forecast bands for time-varying parameters in observation-driven models. 2016 Int. J. Forecast.. 32 875-887
Blasques, F. ; Koopman, S.J. ; Nientker, M. A time-varying parameter model for local explosions. 2022 J. Econom.. 227 65-84
Bloor, C. ; Matheson, T. Analysing shock transmission in a data-rich environment: a large BVAR for New Zealand. 2010 Empir. Econ.. 39 537-558
Bouri, E. ; Cepni, O. ; Gabauer, D. ; Gupta, R. Return connectedness across asset classes around the Covid-19 outbreak. 2021 Int. Rev. Financ. Anal.. 73 -
- Buccheri, G. ; Bormetti, G. ; Corsi, F. ; Lillo, F. Filtering and smoothing with score-driven models. 2021 SSRN Electron. J.. 1-33
Paper not yet in RePEc: Add citation now
- Buccheri, G. ; Corsi, F. HARK the SHARK: realized volatility modeling with measurement errors and nonlinear dependencies. 2017 J. Financ. Econom.. -
Paper not yet in RePEc: Add citation now
Carriero, A. ; Clark, T.E. ; Marcellino, M. Common drifting volatility in large Bayesian VARs. 2016 J. Bus. Econ. Stat.. 34 375-390
Carriero, A. ; Clark, T.E. ; Marcellino, M. Large Bayesian vector autoregressions with stochastic volatility and non-conjugate priors. 2019 J. Econom.. 212 137-154
Carriero, A. ; Kapetanios, G. ; Marcellino, M. Forecasting government bond yields with large Bayesian vector autoregressions. 2012 J. Bank. Finance. 36 2026-2047
Chan, J.C. ; Eisenstat, E. ; Hou, C. ; Koop, G. Composite likelihood methods for large Bayesian VARs with stochastic volatility. 2020 J. Appl. Econom.. 35 692-711
Chan, J.C. ; Eisenstat, E. ; Strachan, R.W. Reducing the state space dimension in a large TVP-VAR. 2020 J. Econom.. 218 105-118
Chan, J.C. ; Yu, X. Fast and accurate variational inference for large Bayesian VARs with stochastic volatility. 2020 :
Chan, J.C.C. Large Bayesian VARs: a flexible Kronecker error covariance structure. 2020 J. Bus. Econ. Stat.. 38 68-79
- Cogley, T. ; Sargent, T.J. Drifts and volatilities: monetary policies and outcomes in the post WWII US. 2005 Rev. Econ. Dyn.. 8 262-302
Paper not yet in RePEc: Add citation now
Creal, D. ; Koopman, S.J. ; Lucas, A. Generalized autoregressive score models with applications. 2013 J. Appl. Econom.. 28 777-795
Creal, D.D. ; Tsay, R.S. High dimensional dynamic stochastic copula models. 2015 J. Econom.. 189 335-345
Demirer, M. ; Diebold, F.X. ; Liu, L. ; Yilmaz, K. Estimating global bank network connectedness. 2018 J. Appl. Econom.. 33 1-15
Diebold, F.X. ; Liu, L. ; Yilmaz, K. Commodity connectedness. 2017 National Bureau of Economic Research:
Diebold, F.X. ; Yilmaz, K. Better to give than to receive: predictive directional measurement of volatility spillovers. 2012 Int. J. Forecast.. 28 57-66
Diebold, F.X. ; Yilmaz, K. Measuring financial asset return and volatility spillovers, with application to global equity markets. 2009 Econ. J.. 119 158-171
Diebold, F.X. ; Yilmaz, K. On the network topology of variance decompositions: measuring the connectedness of financial firms. 2014 J. Econom.. 182 119-134
Durbin, J. ; Koopman, S.J. Time Series Analysis by State Space Methods. 2012 Oxford University Press:
- Gasperoni, F. ; Luati, A. ; Paci, L. ; D'Innocenzo, E. Score-driven modeling of spatio-temporal data. 2021 J. Am. Stat. Assoc.. 1-12
Paper not yet in RePEc: Add citation now
Giannone, D. ; Lenza, M. ; Momferatou, D. ; Onorante, L. Short-term inflation projections: a Bayesian vector autoregressive approach. 2014 Int. J. Forecast.. 30 635-644
- Harvey, A.C. Dynamic Models for Volatility and Heavy Tails: with Applications to Financial and Economic Time Series, vol. 52. 2013 Cambridge University Press:
Paper not yet in RePEc: Add citation now
Harvey, A.C. Forecasting, Structural Time Series Models and the Kalman Filter. 1990 Cambridge University Press:
- Huber, F. ; Koop, G. ; Onorante, L. Inducing sparsity and shrinkage in time-varying parameter models. 2020 J. Bus. Econ. Stat.. 1-15
Paper not yet in RePEc: Add citation now
Kadiyala, K.R. ; Karlsson, S. Numerical methods for estimation and inference in Bayesian VAR-models. 1997 J. Appl. Econom.. 12 99-132
Kapetanios, G. ; Marcellino, M. ; Venditti, F. Large time-varying parameter VARs: a nonparametric approach. 2019 J. Appl. Econom.. 34 1027-1049
Kastner, G. ; Huber, F. Sparse Bayesian vector autoregressions in huge dimensions. 2020 J. Forecast.. 39 1142-1165
Koop, G. Forecasting with medium and large Bayesian VARs. 2013 J. Appl. Econom.. 28 177-203
Koop, G. Using VARs and TVP-VARs with many macroeconomic variables. 2012 Cent. Eur. J. Econ. Model. Econom.. 143-167
Koop, G. ; Korobilis, D. A new index of financial conditions. 2014 Eur. Econ. Rev.. 71 101-116
Koop, G. ; Korobilis, D. Large time-varying parameter VARs. 2013 J. Econom.. 177 185-198
Koop, G. ; Leon-Gonzalez, R. ; Strachan, R.W. On the evolution of the monetary policy transmission mechanism. 2009 J. Econ. Dyn. Control. 33 997-1017
Koopman, S.J. ; Lucas, A. ; Scharth, M. Predicting time-varying parameters with parameter-driven and observation-driven models. 2016 Rev. Econ. Stat.. 98 97-110
Korobilis, D. High-dimensional macroeconomic forecasting using message passing algorithms. 2019 J. Bus. Econ. Stat.. 1-12
Korobilis, D., Yilmaz, K., 2018. Measuring dynamic connectedness with large Bayesian VAR models. Available at SSRN 3099725.
Litterman, R.B. Forecasting with Bayesian vector autoregressions—five years of experience. 1986 J. Bus. Econ. Stat.. 4 25-38
Lucas, A. ; Schwaab, B. ; Zhang, X. Modeling financial sector joint tail risk in the euro area. 2017 J. Appl. Econom.. 32 171-191
Monache, D.D. ; Petrella, I. ; Venditti, F. Price dividend ratio and long-run stock returns: a score-driven state space model. 2021 J. Bus. Econ. Stat.. 39 1054-1065
Nakajima, J. Time-varying parameter VAR model with stochastic volatility: an overview of methodology and empirical applications. 2011 Monet. Econ. Stud.. -
Nonejad, N. An overview of Dynamic Model Averaging techniques in time-series econometrics. 2021 J. Econ. Surv.. 35 566-614
Oh, D.H. ; Patton, A.J. Modeling dependence in high dimensions with factor copulas. 2017 J. Bus. Econ. Stat.. 35 139-154
Oh, D.H. ; Patton, A.J. Time-varying systemic risk: evidence from a dynamic copula model of cds spreads. 2018 J. Bus. Econ. Stat.. 36 181-195
Opschoor, A. ; Lucas, A. ; Barra, I. ; Van Dijk, D. Closed-form multi-factor copula models with observation-driven dynamic factor loadings. 2021 J. Bus. Econ. Stat.. 39 1066-1079
Pakel, C. ; Shephard, N. ; Sheppard, K. ; Engle, R.F. Fitting vast dimensional time-varying covariance models. 2021 J. Bus. Econ. Stat.. 39 652-668
Primiceri, G.E. Time varying structural vector autoregressions and monetary policy. 2005 Rev. Econ. Stud.. 72 821-852
- Raftery, A.E. ; Kárnỳ, M. ; Ettler, P. Online prediction under model uncertainty via dynamic model averaging: application to a cold rolling mill. 2010 Technometrics. 52 52-66
Paper not yet in RePEc: Add citation now
Rizwan, M.S. ; Ahmad, G. ; Ashraf, D. Systemic risk: the impact of Covid-19. 2020 Finance Res. Lett.. 36 -
Rubio-Ramirez, J.F. ; Waggoner, D.F. ; Zha, T. Structural vector autoregressions: theory of identification and algorithms for inference. 2010 Rev. Econ. Stud.. 77 665-696
Sims, C.A. ; Zha, T. Bayesian methods for dynamic multivariate models. 1998 Int. Econ. Rev.. 949-968
Zhang, W. ; Hamori, S. Crude oil market and stock markets during the Covid-19 pandemic: evidence from the US, Japan, and Germany. 2021 Int. Rev. Financ. Anal.. 74 -