Dr. N. (Nestor) Parolya

Dr. N. (Nestor) Parolya

Contact

Room: 36.HB 06.290

Profile

Short Curriculum

  • 2019 - now   Assistant Professor in Statistics, TU Delft
  • 2017 - 2018  Visiting Professor of Statistics, Heidelberg and Mannheim
  • 2014 - 2019  Assistant Professor of Financial Econometrics, LU Hannover
  • 2013 - 2014  PostDoc (Statistics), Ruhr University Bochum
  • 2010 - 2013  PhD in Economics, Viadrina University, Germany
  • 2005 - 2010  BSc. in Mathematics and MSc. in Statistics, University of Lviv, Ukraine

Research interests

Full publication list and CV are here (homepage)
  • high-dimensional statistics and random matrix theory
  • mathematical and statistical finance
  • financial engineering and operations research
  • statistical machine learning in high dimensions

Selected publications

  • Bodnar, T., Parolya, N., Thorsen, E., (2024), Two is Better Than One: Regularized Shrinkage of Large Minimum Variance Portfolios, Journal of Machine Learning Research (link)
  • Parolya N., Heiny J., Kurowicka D. (2024), Logarithmic law of large random correlation matrices, Bernoulli (link)
  • Bodnar, T., Parolya, N., Thorsen, E., (2023), Dynamic Shrinkage Estimation of the High-Dimensional Minimum-Variance Portfolio, IEEE - Transactions of Signal Processing (link)​​​​​​​
  • Bodnar, T., Okhrin, Y., Parolya, N. (2023) Optimal shrinkage-based portfolio selection in high dimensions, Journal of Business & Economic Statistics (link)
  • Bodnar, T., Dette, H., Parolya, N. (2019), Testing for Independence of large dimensional vectors, Annals of Statistics (link)
  • Bodnar, T., Mazur, S., Parolya, N. (2019), CLTs for functionals of large covariance matrix and mean vector in matrix-variate location mixture of normals, Scandinavian Journal of Statistics, 46, 636-660 (link)
  • Bodnar, T., Gupta, A. K., Parolya, N. (2016), Direct Shrinkage Estimation of Large Dimensional Precision Matrix, Journal of Multivariate Analysis, 146, 223-236 (link)
  • Bodnar, T., Parolya, N., Schmid, W. (2018), Estimation of the global minimum variance portfolio in high dimensions, European Journal of Operational Research, 266, 371-390 (link)​​​​​​​

 

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Research interests

Large random matrices and high-dimensional statistics
Mathematical and statistical finance
Financial engineering and operations research
Statistical machine learning in high dimensions

More research interests

Publications

Courses 2024

Courses 2023

Prizes

  • 2019-9-10

    Wolfgang-Wetzel-Preis

    To promote outstanding young scientists and young scientists of the board of the German Statistical Society writes the Wolfgang Wetzel Award from the DStatG for the year 2019. The award is named after the former chairman of DStatG, which began during his tenure, especially for strengthening the mathematical and statistical methods in society.

    The prize is awarded to young scientists and young researchers up to five years after graduation for an outstanding contribution to the statistical methodology and its application. The Laureate contribution is usually from an already published or at least accepted for publication.
    Statistical Week 2019

    Read more Wolfgang-Wetzel-Preis

Ancillary activities

Contact

Room: 36.HB 06.290