Ashok Kaul & Michael Wolf, 2014. Journal of Time Series Analysis, 39:641{664. Michael Wolf Department of Economics University of Zurich michael.wolf@econ.uzh.ch September 2014 Abstract Linear regression models form the cornerstone of applied research in economics and other scienti c disciplines. Data Protection Statement, Multiple testing of one-sided hypotheses: Combining Bonferroni and the bootstrap. Multiple testing of one-sided hypotheses: Combining Bonferroni and the bootstrap. Journal of Portfolio Management, 30(4):110-119. Sort by citations Sort by year Sort by title. Optimal estimation of a large-dimensional covariance matrix under Stein’s loss. Romano, J.P. and Wolf, M. (2018). M. (2019). (PDF, 159 KB), Control of the false discovery rate under dependence using the bootstrap and subsampling. Verified email at econ.uzh.ch - Homepage. Matlab code (ZIP, 755 KB), Romano, J.P., Shaikh, A.M., and Wolf, M. (2014). Fund-of-funds construction by statistical multiple testing methods. (PDF, 825 KB), Balanced bootstrap joint confidence bands for structural impulse response functions. Journal of Financial Econometrics, forthcoming. (PDF, 108 KB), Stock returns and dividend yields revisited: A new way to look at an old problem. Join Facebook to connect with Michael Wolf and others you may know. Optimal estimation of a large-dimensional covariance matrix under Stein's Loss. (PDF, 267 KB) Annals of Statistics, 38:598-633. Efficient computation of adjusted p-values for resampling-based stepdown multiple testing. Journal of the Royal Statistical Society, Series A, 170:1035-1059. Our research involves the development of new econometric methods in the areas of resampling, estimation of covariance matrices, and multiple testing. Romano, J.P., Shaikh, A.M., and Wolf, M. (2010). Wilmott Magazine, January, 76-81. Efficient sorting: A more powerful test for cross-sectional anomalies. Economics Letters, 73:241-250. a Series of Unfortunate Events 02-Jun-2011. Bittman, R.M., Romano, J.P., Vallarino, C., and Wolf, M. (2009). Cited by. Wilmott Magazine, September, 86-89. A more general Central Limit Theorem for 'm'-dependent random variables with unbounded m. Statistics and Probability Letters, 47:115-124. Michael Wolf. Politis, D.N., Romano, J.P., and Wolf, M. (1997). Dan Wunderli. (PDF, 809 KB), Nonlinear shrinkage estimation of large-dimensional covariance matrices. michael.wolf@econ.uzh.ch January2016 Abstract This paper deals with certain estimation problems involving the covariance matrix in large dimensions. In: Scherer, B. and Winston, K. Publications; Research. Wolf, M. and Wunderli, D. (2011). Correspondence to: Michael Wolf, Department of Economics, University of Zurich, 8032 Zurich, Switzerland. ), Robustness in Econometrics, 135-167. Michael Hediger Stephan Hemri Leila Schuh Bernadetta Tarigan . When considering multiple hypothesis tests simultaneously, standard statistical techniques will lead to over-rejection of null hypotheses unless the multiplicity of the testing framework is explicitly considered. (PDF, 2358 KB). Blume. Review of Economics and Statistics, 85:735-747. Journal of Time Series Analysis, 39:641-664. Journal of Econometrics, 81:281-317. Annals of Statistics, 30:1081-1102. (PDF, 193 KB), Flexible multivariate GARCH modeling with an application to international stock markets. (PDF, 267 KB), Analytical nonlinear shrinkage of large-dimensional covariance matrices. International Journal of Biostatistics, 7, Issue 1, Article 12. Michael Wolff (born August 27, 1953) is an American author, essayist, journalist, and a columnist and contributor to USA Today, The Hollywood Reporter, and the UK edition of GQ. Journal of Business and Economic Statistics, 18:18-30. Journal of Econometrics, 197:1-19. Econometrica, 82:1979-2002. Annals of Statistics, 28:756-778. Name Office Phone (044) E-mail; Dr. Cappelli, Seraina: Y13-H-89: 635 61 08: Guiducci, Ilaria Rita: Y34-J-74: 635 47 64: Liu, Hanlun: Y13-H-30: 635 47 42: Okada, Moeko michael.wolf@econ.uzh.ch Zhao Zhao School of Economics Huazhong University of Science and Technology Wuhan, Hubei, China zhaozhao@hust.edu.cn First version: December 2016 This version: May 2018 Abstract Many researchers seek factors that predict the cross-section of stock returns. (PDF, 871 KB), Robust performance hypothesis testing with the Sharpe ratio. When the matrix dimension is large compared to the sample size, which happens fre- by Michael Wolf Hardcover. '`"ÆÀWiÝVØÞc´Á8oÑIV´¤X±êEyqZÕ¼¬X²oSÆu°{ñÎs=G±¨úîª]7Ô*Ã/ FØßÔöY}È-àÏí½Ìi»4é&Ö*[ÜÓÜsÚcßfÓs4tF½SñSõd\+ ¸R³½÷o%«eûßXíf5©³Ü¾Û*þÜÕnWüùÕޫݤFý³× ö52#8Çh¾*¿ømlåûÖ78-JÀos×ÍÅÑ×Òa\þî¾è¾kkAR:ÔÏpÓÏ
1]. Title. (eds. (PDF, 358 KB), Avoiding data snooping in multilevel and mixed effects models. (PDF, 190 KB), Explicit nonparametric confidence intervals for the variance with guaranteed coverage. Michael Wolf View (2) In [squared brackets], we report p-values for the Romano-Wolf multiple hypothesis correction Wolf, 2005, 2016), implemented with the rwolf package from Clarke et al. Michael Wolf Department of Economics University of Zurich michael.wolf@econ.uzh.ch Abstract. Annual Review of Economics, 2:75-104. Wolf won first prize in the Contemporary Issues category of the 2004 World Press Photo competition for his photographs of workers in several types of factories for an article in Stern. Master's Theses 2020. Bell, D.R., Ledoit, O., and Wolf, M. (2014). (PDF, 129 KB), Finite sample nonparametric inference and large sample efficiency. (PDF, 494 KB), Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. Romano, J.P., Shaikh, A.M., and Wolf, M. (2010). A practical two-step method for testing moment inequalities. M. (2018). Journal of Financial Econometrics, 17:645-686. Econometric Theory, 24:404-447. (PDF, 699 KB), Efficient sorting: A more powerful test for cross-sectional anomalies. O Ledoit, M Wolf. Delgado, M., Rodriguez-Poo, J., and Wolf, M. (2001). Econometrics and Statistics, 10:96-119. Supplementary Material (PDF, 270 KB), Ledoit, O. and Wolf, M. (2017). Journal of Time Series Analysis, 25:251-263. Ledoit, O., Wolf, M., and Zhao Z. michael.wolf@econ.uzh.ch DanWunderli DepartmentofEconomics UniversityofZurich CH-8032Zurich,Switzerland dan.wunderli@econ.uzh.ch February,2012 Abstract Many economic and financial applications require the forecast of a random variable of interest over several periods into the future. Communications in Statististics - Theory and Methods, 31:1231-125 (PDF, 123 KB), On the asymptotic theory of subsampling. Matlab code (ZIP, 5580 KB), Ledoit O. and Wolf, M. (2017). (PDF, 511 KB), Consonance and the closure method in multiple testing. Nonlinear shrinkage of the covariance matrix for portfolio selection: Markowitz meets Goldilocks. In addition, we apply econometric methods to problems of … Annals of Statistics, forthcoming. Journal of Financial Econometrics, forthcoming. Michael Wolf (born June 1, 1967) holds the Chair of Econometrics and Applied Statistics in the Department of Economics at the University of Zurich, Switzerland. Journal of the American Statistical Association, 100:94-108. Annals of Statistics, 35:1378-1408. (PDF, 390 KB), A new portfolio formation approach to mispricing of marketing performance indicators: an application to customer satisfaction. Springer International Publishing. This presentation is open to the public and is officially announced. (PDF, 448 KB), Numerical implementation of the QuEST function. (PDF, 92 KB) © University of Zurich I gratefully acknowledge helpful discussions with Christian Hansen, Tim Conley, Kelly Reeve, Dan Zou, Nicolai Meinshausen, Marloes Maathius, Rahul Mazumder, Ryan Tibshirani, Trevor Hastie, Martin Schonger, Pietro Biroli, Michael Wolf, Lorenzo Casaburi, Hannes Schwandt, Ralph Ossa, Rainer Winkelmann, attendants at the ETH Zürich Seminar für Statistik Research Seminar, attendants … Auf LinkedIn können Sie sich das vollständige Profil ansehen und mehr über die Kontakte von Michael Wolf und Jobs bei ähnlichen Unternehmen erfahren. Bernoulli, 24:3791-3832 (PDF, 759 KB). (Invited Paper with discussion), TEST 17, 417-442. DiCiccio, C.J., Romano, J.P., and Wolf, M. (2019). Search for more papers by this author. (2019). (PDF, 220 KB), Subsampling inference in cube root asymptotics with an application to Manski'smaximum score estimator. Statistics & Probability Letters, 113:38-40. Miguel Ferreira Nova School of Business and Economics: Entrepreneurship and Regional Windfall Gains: Evidence from the Spanish Christmas Lottery Paper (PDF, 434 KB) 15.03. Robert F. Engle Department of Finance, New York University, New York, NY 10012 (rengle@stern.nyu.edu), Olivier Ledoit Department of Economics, University of Zurich, CH-8032 Zurich, Switzerland (olivier.ledoit@econ.uzh.ch); AlphaCrest Capital Management, New York, NY 10036 (olivier.ledoit@alphacrestcapital.com) & Michael Wolf Department of Economics, University of Zurich, … (PDF, 1050 KB), Resurrecting weighted least squares. Journal of Nonparametric Statistics, 18:199-214. (PDF, 192 KB), Stepwise multiple testing as formalized data snooping. (PDF, 354 KB), Honey, I shrunk the sample covariance matrix. Metrika, 50:55-69. Journal of Econometrics, 127:201-224. Ledoit, O., Santa-Clara, P., and Wolf, M. (2003). (PDF, 307 KB), Optimal testing of multiple hypotheses with common effect direction. Statistics & Probability Letters, 113:38-40. Sitemap (PDF, 383 KB), Subsampling, symmetrization, and robust interpolation. R code (ZIP, 40 KB)Matlab code (ZIP, 6 KB), Home 10. Sehen Sie sich das Profil von Michael Wolf im größten Business-Netzwerk der Welt an. Journal of Time Series Analysis, 36:352-376. Journal of Empirical Finance, 10:603-621. (PDF, 311 KB), Optimal estimation of a large-dimensional covariance matrix under Stein's Loss. Politis, D.N., Romano, J.P., and Wolf, M. (2001). Econometrica, 69:1283-1314. Politis, D.N., Romano, J.P., and Wolf, M. (2000). £102.18. Matlab code (ZIP, 1 KB), Engle, R.F., Ledoit, O., and Wolf, M. (2019). Communications in Statististics - Theory and Methods, 29:1741-1758. (PDF, 674 KB), Efficient computation of adjusted p-values for resampling-based stepdown multiple testing. (PDF, 301 KB), Formalized data snooping based on generalized error rates. Michael LINECKER, Surgeon, Coordinator International ALPPS Registry of University of Zurich, Zürich (UZH) | Read 85 publications | Contact Michael LINECKER (PDF, 575 KB), Robust performance hypothesis testing with the variance. oledoit@iew.uzh.ch Michael Wolf∗ Inst. Oxford University Press, Oxford. (PDF, 185 KB), A more general Central Limit Theorem for 'm'-dependent random variables with unbounded m. Statistics and Probability Letters, 47:115-124. In: Kreinovich, V., Sriboonchitta, S., and Huynh, V.-N. Michael Wolf (UZH, NYU Stern, others) Large Dynamic Covariance Matrices: Enhancements Based on Intraday Data, allowing for computationally feasible correlation estimation also for large dimensions of assets (N>1000). Visitors; Adjunct Faculty; Emeriti; Researchers with PhD; Graduate Students; Administrative Staff; Research. ), Predictive Econometrics and Big Data, 78-94. (PDF, 271 KB), Testing for monotonicity in expected asset returns. In: Kreinovich, V., Sriboonchitta, S., and Chakpitak N. Zurich Open Repository and Archive University of Zurich Main Library Strickhofstrasse 39 CH-8057 Zurich www.zora.uzh.ch Year: 2012 An international comparison of … The sequence of individual forecasts, one period at a time, is called a path-forecast, where the … Computational Statistics & Data Analysis, 115:199-223. (PDF, 304 KB), Resampling vs. shrinkage for benchmarked managers. Journal of Multivariate Analysis, 139:360-384. Articles Cited by Co-authors. Sekretariat: E-Mail: Tel. Review of Financial Studies, 30:4349-4388. Balanced bootstrap joint con dence bands for structural impulse response functions. (PDF, 648 KB), Control of generalized error rates in multiple testing. (PDF, 885 KB), Bootstrap joint prediction regions. Econometrica, 73:1237-1282. Customer Needs and Solutions, 1:263-276. Journal of Empirical Finance, 15:850-859. Journal of Statistical Planning and Inference, 79:179-191. 8. Cited by. Annals of Statistics, 48:3043-3065. 9. (PDF, 448 KB) Supplementary Material (PDF, 330 KB), Romano, J.P. and Wolf, M. (2016).