Michael Wolf is Professor of Econometrics and Applied Statistics at UZH – University of Zurich. The research of his team involves the development of new econometric methods in the areas of resampling, estimation of covariance matrices, and multiple testing. Applications give a special focus on finance, including performance evaluation and portfolio selection.
Engle, R.F., Ledoit, O., and Wolf. M. (2018). Large dynamic covariance matrices. Journal of Business & Economic Statistics, forthcoming.
Ledoit, O. and Wolf, M. (2017). Nonlinear shrinkage of the covariance matrix for portfolio selection: Markowitz meets Goldilocks. Review of Financial Studies 30, 4349-4388.
Romano, J.P. and Wolf, M. (2013). Testing for monotonicity in expected asset returns. Journal of Empirical Finance 23, 93-116.
Wolf, M. and Wunderli, D. (2011). Fund-of-funds construction by statistical multiple testing methods. In: Scherer, B. and Winston, K. (eds.), The Oxford Handbook of Quantitative Asset Management, 116-135. Oxford University Press, Oxford.
Ledoit, O. and Wolf, M. (2008). Robust performance hypothesis testing with the Sharpe ratio. Journal of Empirical Finance 15, 850-859.
Professor of Econometrics and Applied Statistics
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