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Leibniz Universität Hannover/Institut für Statistik
Logo Leibniz Universität Hannover
Leibniz Universität Hannover/Institut für Statistik
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Prof. Dr. Nestor Parolya

on leave: this summer term 2018 I'm a stand-in professor for Statistics (W3) at Mannheim University

Curriculum Vitae

Education

  • 2013: PhD in Economics, Dr. rer. pol. with "summa cum laude", European University Viadrina, Frankfurt (Oder); "Multi-Period and High-Dimensional Portfolio Selection Problems", Supervisor: Prof. Dr. W. Schmid
  • 2010: M. Sc. in Mathematical Statistics (with distinction), Ivan Franko University of Lviv, Ukraine
  • 2009: B. Sc. in Mathematics (with distinction), Ivan Franko National University of Lviv, Ukraine

Scientific Activities

  • 02/2018 - 08/2018: Stand-in Professor (W3) for Statistics, Mannheim University
  • 10/2017 - 01/2018: Stand-in Professor (W3) for Econometrics, Heidelberg University
  • Since 04/2014: Assistant Professor (W1, positively evaluated) in Financial Econometrics, Leibniz University Hannover
  • 2013-2014: Research fellow at Department of Statistics and Econometrics, Ruhr University, Bochum
  • 2010-2013: Doctoral studies at Department of Statistics, European University Viadrina, Frankfurt (Oder)

Research interests

  • High-Dimensional Data Analysis and Large Covariance Matrices
  • Random Matrix Theory with Applications in Statistics and Finance
  • Quantitative Risk and Portfolio Management

Publications

2018

  • Bodnar, T., Parolya, N., Schmid, W.: Estimation of the global minimum variance portfolio in high dimensions,European Journal of Operational Research, 266, 04/2018, 371-390 (link)

2017

  • Golosnoy, V., Parolya, N.: "To have what they are having": portfolio choice for mimicking mean-variance savers, Quantitative Finance, 11, 04/2017, 1645-1653 (link)

2016

  • Bodnar, T., Dette, H., Parolya, N.: Spectral analysis of the Moore-Penrose inverse of a large dimensional sample covariance matrix, Journal of Multivariate Analysis, 148, 06/2016, 160-17 (link)
  • Bodnar, T., Gupta, A. K., Parolya, N.: Direct Shrinkage Estimation of Large Dimensional Precision Matrix, Journal of Multivariate Analysis, 146, 04/2016, 223-236 (link)

2015

  • Bodnar, T., Parolya, N., Schmid, W.: On the Exact Solution of the Multi-Period Portfolio Choice Problem for an Exponential Utility under Return Predictability, European Journal of Operational Research, 246, 528-542 (link)
  • Bodnar, T., Parolya, N., Schmid, W.: A Closed-Form Solution of the Multi-Period Portfolio Choice Problem for a Quadratic Utility Function, Annals of Operations Research, 229, 121-158 (link)

2014

  • Bodnar, T., Gupta, A. K., Parolya, N.: On the Strong Convergence of the Optimal Linear Shrinkage Estimator for the Large Dimensional Covariance Matrix, Journal of Multivariate Analysis, 132, 215-228 (link)

2013

  • Bodnar, T., Parolya, N., Schmid, W.: On the Equivalence of Quadratic Optimization Problems Commonly Used in Portfolio Theory, European Journal of Operational Research, 229, 637-644 (link)

Current Working Papers

  • Bodnar, T., Dette, H., Parolya, N.:Testing for Independence of large dimensional vectors (WP)
  • Bodnar, T., Okhrin, Y., Parolya, N.: Optimal shrinkage-based portfolio selection in high dimensions (WP)
  • Bodnar, T., Mazur, S., Parolya, N.: Central limit theorems for functionals of large sample covariance matrix and mean vector in matrix-variate location mixture of normal distributions (WP)
  • Bodnar, T., Okhrin, O., Parolya, N.: Optimal shrinkage estimator for high-dimensional mean vector (WP)
  • Bauder, D., Bodnar, T., Schmid, W., Parolya, N.: Bayesian Inference of the Multi-Period Optimal Portfolio for an Exponential Utility (WP)
  • Bodnar, T., Mazur, S., Ngailo, E., Parolya, N.: Discriminant analysis in small and large dimensions (WP)
  • Bodnar, T., Dmytriv A., Parolya, N., Schmid, W.: Tests for weights of global minimum variance portfolio in a high-dimensional setting (WP)
  • Bodnar, T., Mazur, S., Muhinyuza, S., Parolya, N.: On the product of a singular Wishart matrix and a singular Gaussian vector in high dimension (WP)

Current Teaching

Winter term 2018/19