Publications

Books

Politis, D.N., Romano, J.P., and Wolf, M. (1999).
Subsampling. Springer, New York.

Book Chapters

Sterchi, M. and Wolf, M. (2017).
Weighted least squares and adaptive least squares: Further empirical evidence. (PDF, 267 KB)
In: Kreinovich, V., Sriboonchitta, S., and Huynh, V.-N. (eds.), Robustness in Econometrics, 135-167.
Springer International Publishing.
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.

Journal Papers

De Nard, G., Ledoit, O., and Wolf, M. Factor models for portfolio selection in large dimensions: The good, the better and the ugly. Journal of Financial Econometrics, forthcoming.

Ledoit, O., Wolf, M., and Zhao Z. Efficient sorting: A more powerful test for cross-sectional anomalies. Journal of Financial Econometrics, forthcoming.

Engle, R.F., Ledoit, O., and Wolf. M. Large dynamic covariance matrices. Journal of Business & Economic Statistics, forthcoming.
Bruder, S. and Wolf, M. (2018). Balanced bootstrap joint confidence bands for structural impulse response functions. Journal of Time Series Analysis, 39:641-664. (PDF, 311 KB)

Ledoit, O. and Wolf, M. (2018). Optimal estimation of a large-dimensional covariance matrix under Stein's Loss. Bernoulli, 24:3791-3832 (PDF, 759 KB). Supplementary Material (PDF, 270 KB)

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. (PDF, 448 KB) Supplementary Material (PDF, 330 KB)

Ledoit, O. and Wolf. M. (2017). Numerical implementation of the QuEST function. Computational Statistics & Data Analysis, 115:199-223. (PDF, 1050 KB)
Romano, J.P. and Wolf, M. (2017). Resurrecting weighted least squares. Journal of Econometrics, 197:1-19. (PDF, 674 KB)

Romano, J.P. and Wolf, M. (2016). Efficient computation of adjusted p-values for resampling-based stepdown multiple testing. Statistics & Probability Letters, 113:38-40. (PDF, 348 KB)

Ledoit, O. and Wolf, M. (2015). Spectrum estimation: a unified framework for covariance matrix estimation and PCA in large dimensions. Journal of Multivariate Analysis, 139:360-384. (PDF, 885 KB)
Wolf, M. and Wunderli, D. (2015). Bootstrap joint prediction regions. Journal of Time Series Analysis, 36:352-376. (PDF, 390 KB)
Bell, D.R., Ledoit, O., and Wolf, M. (2014). A new portfolio formation approach to mispricing of marketing performance indicators: an application to customer satisfaction. Customer Needs and Solutions, 1:263-276. (PDF, 344 KB)
Romano, J.P., Shaikh, A.M., and Wolf, M. (2014). A practical two-step method for testing moment inequalities. Econometrica, 82:1979-2002. (PDF, 271 KB)Supplement (PDF, 99 KB)
Romano, J.P. and Wolf, M. (2013). Testing for monotonicity in expected asset returns. Journal of Empirical Finance, 23:93-116. (PDF, 809 KB)
Ledoit, O. and Wolf, M. (2012). Nonlinear shrinkage estimation of large-dimensional covariance matrices. Annals of Statistics, 40:1024-1060. (PDF, 575 KB)Supplement. (PDF, 209 KB)
Ledoit, O. and Wolf, M. (2011). Robust performance hypothesis testing with the variance. Wilmott Magazine, September, 86-89. (PDF, 511 KB)
Romano, J.P., Shaikh, A.M., and Wolf, M. (2011). Consonance and the closure method in multiple testing. International Journal of Biostatistics, 7, Issue 1, Article 12. (PDF, 1016 KB)
Romano, J.P., Shaikh, A.M., and Wolf, M. (2010). Hypothesis testing in econometrics. Annual Review of Economics, 2:75-104. (PDF, 697 KB)
Romano, J.P. and Wolf, M. (2010). Balanced control of generalized error rates. Annals of Statistics, 38:598-633. (PDF, 307 KB)
Bittman, R.M., Romano, J.P., Vallarino, C., and Wolf, M. (2009). Optimal testing of multiple hypotheses with common effect direction. Biometrika, 96:399-410. (PDF, 159 KB)
Romano, J.P., Shaikh, A.M., and Wolf, M. (2008). Control of the false discovery rate under dependence using the bootstrap and subsampling. (Invited Paper with discussion), TEST 17, 417-442. (PDF, 871 KB)
Ledoit, O. and Wolf, M. (2008). Robust performance hypothesis testing with the Sharpe ratio. Journal of Empirical Finance, 15:850-859. (PDF, 301 KB)
Romano, J.P., Shaikh, A.M., and Wolf, M. (2008). Formalized data snooping based on generalized error rates. Econometric Theory, 24:404-447. (PDF, 358 KB)
Afshartous, D. and Wolf, M. (2007). Avoiding data snooping in multilevel and mixed effects models. Journal of the Royal Statistical Society, Series A, 170:1035-1059. (PDF, 648 KB)
Romano, J.P. and Wolf, M. (2007). Control of generalized error rates in multiple testing. Annals of Statistics, 35:1378-1408. (PDF, 304 KB)
Wolf, M. (2007). Resampling vs. shrinkage for benchmarked managers. Wilmott Magazine, January, 76-81. (PDF, 99 KB)
Romano, J.P. and Wolf, M. (2006). Improved nonparametric confidence intervals in time series regressions. Journal of Nonparametric Statistics, 18:199-214. (PDF, 192 KB)
Romano, J.P. and Wolf, M. (2005). Stepwise multiple testing as formalized data snooping. Econometrica, 73:1237-1282. (PDF, 308 KB)
Gonzalo, J. and Wolf, M. (2005). Subsampling inference in threshold autoregressive models. Journal of Econometrics, 127:201-224. (PDF, 391 KB)
Romano, J.P. and Wolf, M. (2005). Exact and approximate stepdown methods for multiple hypothesis testing. Journal of the American Statistical Association, 100:94-108. (PDF, 354 KB)
Ledoit, O. and Wolf, M. (2004). Honey, I shrunk the sample covariance matrix. Journal of Portfolio Management, 30(4):110-119. (PDF, 162 KB)
Politis, D.N., Romano, J.P., and Wolf M. (2004). Inference for autocorrelations in the possible presence of a unit root. Journal of Time Series Analysis, 25:251-263. (PDF, 141 KB)
Kokoszka, P. and Wolf, M. (2004). Subsampling the mean of heavy-tailed dependent observations. Journal of Time Series Analysis, 25:217-234. (PDF, 178 KB)
Ledoit, O. and Wolf, M. (2004). A well-conditioned estimator for large-dimensional covariance matrices. Journal of Multivariate Analysis, 88:365-411. (PDF, 494 KB)
Ledoit, O. and Wolf, M. (2003). Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. Journal of Empirical Finance, 10:603-621. (PDF, 193 KB)
Ledoit, O., Santa-Clara, P., and Wolf, M. (2003). Flexible multivariate GARCH modeling with an application to international stock markets. Review of Economics and Statistics, 85:735-747. (PDF, 225 KB)
Ledoit, O. and Wolf, M. (2002). Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size. Annals of Statistics, 30:1081-1102. (PDF, 190 KB)
Romano, J.P. and Wolf, M. (2002). Explicit nonparametric confidence intervals for the variance with guaranteed coverage. Communications in Statististics - Theory and Methods, 31:1231-125 (PDF, 123 KB)
Politis, D.N., Romano, J.P., and Wolf, M. (2001). On the asymptotic theory of subsampling. Statistica Sinica, 11:1105-1124. (PDF, 220 KB)
Delgado, M., Rodriguez-Poo, J., and Wolf, M. (2001). Subsampling inference in cube root asymptotics with an application to Manski'smaximum score estimator. Economics Letters, 73:241-250. (PDF, 72 KB)
Romano, J.P. and Wolf, M. (2001). Subsampling intervals in autoregressive models with linear time trend. Econometrica, 69:1283-1314. (PDF, 383 KB)
Politis, D.N., Romano, J.P., and Wolf, M. (2000). Subsampling, symmetrization, and robust interpolation. Communications in Statististics - Theory and Methods, 29:1741-1758. (PDF, 129 KB)
Romano, J.P. and Wolf, M. (2000). Finite sample nonparametric inference and large sample efficiency. Annals of Statistics, 28:756-778. (PDF, 185 KB)
Romano, J.P. and Wolf, M. (2000). A more general Central Limit Theorem for 'm'-dependent random variables with unbounded m. Statistics and Probability Letters, 47:115-124. (PDF, 108 KB)
Wolf, M. (2000). Stock returns and dividend yields revisited: A new way to look at an old problem. Journal of Business and Economic Statistics, 18:18-30. (PDF, 540 KB)
Romano, J.P. and Wolf, M. (1999). Inference for the mean in the heavy-tailed case. Metrika, 50:55-69. (PDF, 141 KB)
Politis, D.N., Romano, J.P., and Wolf, M. (1999). Weak convergence of dependent empirical measures with application to subsampling and confidence bands. Journal of Statistical Planning and Inference, 79:179-191. (PDF, 100 KB)
Politis, D.N., Romano, J.P., and Wolf, M. (1997). Subsampling for heteroskedastic time series. Journal of Econometrics, 81:281-317. (PDF, 2358 KB)

Programming Code

Ledoit O. and Wolf, M. (2017).
Numerical implementation of the QuEST function.
Computational Statistics & Data Analysis, 115:199-223.
Matlab code (ZIP, 751 KB)

Romano, J.P. and Wolf, M. (2017).
Resurrecting weighted least squares.
Journal of Econometrics, 197:1-19.
R code (ZIP, 426 KB)
Romano, J.P. and Wolf, M. (2016).
Efficient computation of adjusted p-values for resampling-based stepdown multiple testing.
Statistics & Probability Letters, 113:38-40.
R code (ZIP, 10 KB)Matlab code (ZIP, 5 KB)

Romano, J.P., Shaikh, A.M., and Wolf, M. (2014).
A practical two-step method for testing moment inequalities.
Econometrica, 82:1979-2002.
R code (ZIP, 40 KB)Matlab code (ZIP, 6 KB)

Ledoit, O. and Wolf, M. (2011).
Robust performance hypothesis testing with the variance.
Wilmott magazine, September, 86-89.
R code (ZIP, 46 KB)Matlab Code (ZIP, 151 KB)
Ledoit, O. and Wolf, M. (2008).
Robust performance hypothesis testing with the Sharpe ratio.
Journal of Empirical Finance, 15:850-859.
R code (ZIP, 62 KB)Matlab code (ZIP, 31 KB)
Romano, J.P., Shaikh, A.M., and Wolf M. (2008).
Formalized data snooping based on generalized error rates.
Econometric Theory, 24(2):404-447.
R code (ZIP, 4 KB)Matlab code (ZIP, 3055 KB)
Ledoit, O. and Wolf, M. (2004).
Honey, I shrunk the sample covariance matrix.
Journal of Portfolio Management, 30(4):110-119.
Matlab code (ZIP, 1 KB)
Ledoit, O. and Wolf, M. (2004).
A well-conditioned estimator for large-dimensional covariance matrices.
Journal of Multivariate Analysis, 88:365-411.
Matlab code (ZIP, 1 KB)
Ledoit, O. and Wolf, M. (2003).
Improved estimation of the covariance matrix of stock returns with an application to portfolio selection.
Journal of Empirical Finance, 10:603-621.
Matlab code (ZIP, 2 KB)
Ledoit, O., Santa-Clara, P., and Wolf, M. (2003).
Flexible multivariate GARCH modeling with an application to international stock markets.
Review of Economics and Statistics, 85:735-747.
Matlab code (ZIP, 7 KB)

Working Papers