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Main research areas

Econometric Theory

  • Non- and semiparametric methods
  • Generated regressors
  • Nonparametric estimation for nonstationary time series
  • Quantile estimation and model selection techniques
  • High-dimensional econometrics

 

Financial Econometrics

  • Systemic risk measurement
  • Interdependencies of risks
  • Large dimensional extreme risk
  • Methods for high-frequency finance
  • Asset pricing with consumption Euler equations
  • Portfolio selection and estimation

Publications

Nazemi, A.; Fatemipour, F.; Heidenreich, K.; Fabozzi, F. J. (2017). Fuzzy decision fusion approach for loss-given-default modeling. European Journal of Operational Research, Forthcoming [http://www.sciencedirect.com/science/article/pii/S0377221717303417 ]

Betz, F., Hautsch, N., Peltonen, T., Schienle, M. (2016) Systemic Risk Spillovers in the European Banking and Sovereign Network, Journal of Financial Stability, in press [doi:10.1016/j.jfs.2015.10.006] , [working paper version], - [covered in the ECB Financial Stability Review [May 2013] (pages 71-73 (box 6))  and [Nov.2013] (page 74 ,chart 3.15)]

Bormann, C., Schaumburg, J., Schienle, M. (2015+) Beyond dimension two: A test for higher-order tail risk (with Carsten Bormann and Julia Schaumburg), Journal of Financial Econometrics, in press [doi: 10.1093/jjfinec/nbv022], [working paper version]

Mammen, E., Rothe, C., Schienle, M. (2015) Semiparametric Estimation with Generated Covariates, Econometric Theory, in press [doi:10.1017/S0266466615000134] , [working paper version]

Hautsch, N., Schaumburg, J., Schienle, M. (2015)  Financial Network Systemic Risk Contributions, Review of Finance, Vol. 19, No 2, 685-738, [doi:10.1093/rof/rfu010], [working paper version]

Malec, P., Schienle, M. (2014) Nonparametric Kernel Density Estimation Near the Boundary, Computational Statistics and Data Analysis,  Vol. 72, 57-72 [doi:10.1016/j.csda.2013.10.023], [working paper version]

Hautsch, N., Schaumburg, J.,  Schienle, M. (2014) Forecasting systemic impact in financial networks, International Journal of Forcasting, Vol. 30, Issue 3, 781–794 [doi:10.1016/j.ijforecast.2013.09.004], [working paper version]

Hautsch, N., Malec, P.,  Schienle, M. (2013) Capturing the Zero: A New Class of Zero-Augmented Distributions and Multiplicative Error Processes, Journal of Financial Econometrics, Vol. 12 No.1, 89-121 [doi: 10.1093/jjfinec/nbt002] , [working paper version], [webappendix]

Mammen, E., Rothe, C., Schienle, M. (2012) Nonparametric Regression with Nonparametrically Generated Regressors, the Annals of Statistics, Vol. 40, No. 2, 1132-1170 [doi:10.1214/12-AOS995] or via arXiv [pdf]

 

Mammen, E., Park, B. U., Schienle, M. (2014) Additive Models: Extensions and Related Models, in Handbook of Applied Nonparametric and Semiparametric Econometrics and Statistics (editors Racine, Ullah), Oxford University Press  [working paper version]

Mammen, E., Rothe, C., Schienle, M. (2013) Generated Regressors in Nonparametric Estimation: A Short Review,  in Recent Developments in Modeling and Applications in Statistics (editors Oliveira, da GraccaTemido, Henriques and Vichi), Springer 2013 [working paper version]

Grith, M. , Härdle, W.K., Schienle, M. (2012)Nonparametric Estimation of Risk-Neutral Densities, in Handbook of Computational Finance, Springer 2012 [working paper version]

 

Working papers and ongoing work

Conrad, C. , Schienle, M. (2015) A GARCH-MIDAS specification test, submitted

Liang, C., Schienle, M. (2015) One Step Determination of Vector Error Correction Models in Higher Dimensions, submitted

Schienle, M. (2015) Nonparametric Nonstationary Regression with many Covariates, submitted

 

Gätjen, R., Schienle, M. (2015) Measuring Connectedness of Euro Area Sovereign Risk, working paper

Bormann, C., Schienle, M. (2016) Testing Tail Asymmetry in Financial Time Series, working paper

Malec, P., Schienle, M. (2016) A Semiparametric Intraday GARCH-X Model, working paper

Liang, C., Schienle m. (2016) High-Dimensional Cointegration, working paper

Linton, O., Mammen, E., Schienle, M., Yu, K. (2014) Nonparametric Regression with Missing Data

Bodnar, T., Okhrin, O., Paroly, N., Schienle, M. (2015) Estimation of Covariance Matrices for High-Dimensional Time Series