Published and forthcoming articles
Financial Linkages and Sectoral Business Cycle Synchronization: Evidence from Europe, with Hannes Boehm and Lena Tonzer. IMF Economic Review, in press. link. Tinbergen Institute Discussion Paper No. 20-008/III, link.
Bank business models at zero interest rates, with André Lucas and Bernd Schwaab, Journal of Business & Economic Statistics, 37(3), 2019, pp. 542-555. link. recent version: ECB Working Paper No 2084: link
Spillover dynamics for systemic risk measurement using spatial financial time series models, with Francisco Blasques, Siem Jan Koopman, and André Lucas, Journal of Econometrics, 195(2), 2016, pp.211–223. link. recent version: pdf, web appendix
Beyond dimension two: A test for higher-order tail risk, with Carsten Bormann and Melanie Schienle, Journal of Financial Econometrics, 14(3), 2016, pp. 552–580. link. recent version: pdf
Winner of the 2019 Engle Prize.
Predicting extreme Value at Risk: Nonparametric quantile regression with refinements from extreme value theory, Computational Statistics & Data Analysis 56(12), 2012, pp. 4081-4096. link. recent version: pdf
Working papers and ongoing work
Do information contagion and business model similarities explain bank credit risk commonalities? with Dieter Wang and Iman van Lelyveld. DNB Working Paper No. 619: link. Tinbergen Institute Discussion Paper No. 18-100/IV: link.
Smooth marginalized particle filters for dynamic network effects models, with Dieter Wang. Tinbergen Institute Discussion Paper No. 20-023/III: link.
Joint modelling and estimation of global and local cross-sectional dependence in large panels, with Quint Wiersma and Siem Jan Koopman. TI Discussion Paper No. 21-008/III: link.
Dynamic nonparametric clustering of multivariate panel data, with Igor Custodio João, André Lucas, and Bernd Schwaab. TI Discussion Paper No. 21-040/III: link.
Vector autoregressions with dynamic factor coefficients and conditionally heteroskedastic errors, with Siem Jan Koopman and Paolo Gorgi. TI Discussion Paper No. 21-056/III: link.
Self-driving neural networks for yield curve modelling, with Marcin Zamojski.