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Mathematics

D-Index
44
Citations
20510
World Ranking
1523
National Ranking
27

Research.com Recognitions

  • 2013 - Fellow of the American Mathematical Society

Overview

Michael Wolf is affiliated with the University of Zurich in Switzerland and has contributed extensively to the field of Economics, Econometrics, and Finance. Their research encompasses a variety of subfields including Statistics and Probability, Finance, Economics and Econometrics, Management Science and Operations Research, and Signal Processing.

Wolf's recent publications focus mainly on statistical and financial methodologies. Key papers include:

  • "The Romano-Wolf multiple-hypothesis correction in Stata" (2020) published in The Stata Journal Promoting communications on statistics and Stata
  • "Analytical nonlinear shrinkage of large-dimensional covariance matrices" (2020) published in The Annals of Statistics
  • "Quadratic shrinkage for large covariance matrices" (2022) published in Bernoulli
  • "The Power of (Non-)Linear Shrinking: A Review and Guide to Covariance Matrix Estimation" (2020) published in Journal of Financial Econometrics
  • "Large dynamic covariance matrices: Enhancements based on intraday data" (2022) published in Journal of Banking & Finance

The main topics addressed in Wolf's work include:

  • Random Matrices and Applications
  • Complex Systems and Time Series Analysis
  • Financial Risk and Volatility Modeling
  • Financial Markets and Investment Strategies
  • Statistical Methods and Bayesian Inference
  • Stock Market Forecasting Methods
  • Statistical Methods in Clinical Trials

Wolf often collaborates with multiple co-authors, most frequently with Olivier Ledoit, followed by Gianluca De Nard, Elliot Beck, Robert F. Engle, and Damian Clarke.

Their work has been published primarily in venues such as the SSRN Electronic Journal, Zurich Open Repository and Archive (University of Zurich), Journal of Financial Econometrics, The Stata Journal Promoting communications on statistics and Stata, and The Annals of Statistics.

In recognition of their contributions, Michael Wolf was named a Fellow of the American Mathematical Society in 2013.

Best Publications

  • A well-conditioned estimator for large-dimensional covariance matrices

    Olivier Ledoit;Michael Wolf

  • Improved Estimation of the Covariance Matrix of Stock Returns With an Application to Portfolio Selection

    Olivier Ledoit;Olivier Ledoit;Michael Wolf

  • A data locality optimizing algorithm

    Michael E. Wolf;Monica S. Lam

  • Honey, I shrunk the sample covariance matrix

    Olivier Ledoit;Michael Wolf

  • Weak convergence of dependent empirical measures with application to subsampling in function spaces

    Dimitris Politis;Joseph P. Romano;Michael Wolf

  • Stepwise multiple testing as formalized data snooping

    Joseph P. Romano;Michael Wolf

  • Robust Performance Hypothesis Testing with the Sharpe Ratio

    Olivier Ledoit;Michael Wolf

  • A loop transformation theory and an algorithm to maximize parallelism

    M.E. Wolf;M.S. Lam

  • Exact and approximate stepdown methods for multiple hypothesis testing

    Joseph P Romano;Michael Wolf

  • Nonlinear Shrinkage Estimation of Large-Dimensional Covariance Matrices

    Olivier Ledoit;Michael Wolf

  • Nonlinear Shrinkage of the Covariance Matrix for Portfolio Selection: Markowitz Meets Goldilocks

    Olivier Ledoit;Michael Wolf

  • Flexible multivariate GARCH modeling with an application to international stock markets

    Olivier Ledoit;Pedro Santa-Clara;Michael Wolf

  • Efficient computation of adjusted p-values for resampling-based stepdown multiple testing

    Joseph P. Romano;Michael Wolf

  • The Romano–Wolf multiple-hypothesis correction in Stata:

    Damian Clarke;Joseph P. Romano;Michael Wolf

  • Large Dynamic Covariance Matrices

    Robert F. Engle;Olivier Ledoit;Michael Wolf

  • Stepwise Multiple Testing as Formalized Data Snooping

    Michael Wolf;Joseph P. Romano

  • Formalized data snooping based on generalized error rates

    Joseph P. Romano;Azeem M. Shaikh;Michael Wolf

  • Control of generalized error rates in multiple testing

    Joseph P. Romano;Michael Wolf

  • Analytical nonlinear shrinkage of large-dimensional covariance matrices

    Olivier Ledoit;Michael Wolf

  • Control of the False Discovery Rate under Dependence using the Bootstrap and Subsampling

    Joseph P. Romano;Azeem M. Shaikh;Michael Wolf

  • Robust Performance Hypothesis Testing with the Sharpe Ratio

    Michael Wolf

  • Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size

    Olivier Ledoit;Michael Wolf

Frequent Co-Authors

Joseph P. Romano
Joseph P. Romano Stanford University
Dimitris N. Politis
Dimitris N. Politis University of California, San Diego
Monica S. Lam
Monica S. Lam Stanford University
Rebecca Schüle
Rebecca Schüle University of Tübingen
Thomas Klopstock
Thomas Klopstock Ludwig-Maximilians-Universität München
Alfredo Ramirez
Alfredo Ramirez University of Cologne
Stefan Herms
Stefan Herms University of Basel
Patrick F. Chinnery
Patrick F. Chinnery University of Cambridge
Garth A. Nicholson
Garth A. Nicholson University of Sydney
Ludger Schöls
Ludger Schöls University of Tübingen

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