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Department of Economics

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Books

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

Book Chapters

Romano, J.P. and Wolf, M. (2018).
Multiple testing of one-sided hypotheses: Combining Bonferroni and the bootstrap. (PDF, 244 KB)
In: Kreinovich, V., Sriboonchitta, S., and Chakpitak, N. (eds.), Predictive Econometrics and Big Data, 78-94.
Springer International Publishing.

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.

Romano, J.P., Shaikh, A.M., and Wolf, M. (2010).
Multiple testing. (PDF, 92 KB)
In: The New Palgrave Dictionary of Economics, Online Edition. Edited by S.N. Durlauf and L.E. Blume.
Palgrave Macmillan.

Journal Papers

Nguyen, P.A. and Wolf, M. (2026). The permutation test for event studies with a small number of events. Empirical Economics, 70:63. (PDF, 283 KB)

Beck, E. and Wolf, M. (2026). Forecasting inflation with the hedged random forest. Empirical Economics, 70:23. (PDF, 1 MB)
Ledoit, O. and Wolf, M. (2025). Markowitz portfolios under transaction costs. Quarterly Review of Economics and Finance, 100:101962. (PDF, 1 MB)
De Nard, G., Ledoit, O., and Wolf, M. (2025). Improved tracking-error management for active and passive investing. Journal of Portfolio Management, 51:40-62. (PDF, 3 MB)
Nguyen, P.A. and Wolf, M. (2024). Single-firm inference in event studies via the permutation test. Empirical Economics, 66:2435-2450. (PDF, 290 KB)
Bell, D.R., Ledoit, O., and Wolf, M. (2024). A novel estimator of Earth's curvature (Allowing for inference as well). Annals of Applied Statistics, 18:585-599. (PDF, 581 KB)
Hediger, S., Näf, J., and Wolf, M. (2023). R-NL: Covariance matrix estimation for elliptical distributions based on nonlinear shrinkage. IEEE Transactions on Signal Processing, 71:1657-1668. (PDF, 942 KB)
Beck, E., De Nard, G., and Wolf, M. (2023). Improved inference in financial factor models. International Review of Economics and Finance, 86:364-379. (PDF, 1 MB)
Ledoit, O. and Wolf, M. (2022). Quadratic shrinkage for large covariance matrices. Bernoulli, 28:1519-1547. (PDF, 675 KB)
De Nard, G., Engle, R.F., Ledoit, O., and Wolf, M. (2022). Large dynamic covariance matrices: Enhancements based on intraday data. Journal of Banking and Finance, 138:106426. (PDF, 2 MB)
Ledoit, O. and Wolf, M. (2022). The power of (non-)linear shrinking: A review and guide to covariance matrix estimation. Journal of Financial Econometrics, 20:187-218. (PDF, 416 KB)
Ledoit, O. and Wolf, M. (2021). Shrinkage estimation of large covariance matrices: Keep it simple, statistician? Journal of Multivariate Analysis, 186:104796. (PDF, 921 KB)

De Nard, G., Ledoit, O., and Wolf, M. (2021). Factor models for portfolio selection in large dimensions: The good, the better and the ugly. Journal of Financial Econometrics, 19:236-257. (PDF, 249 KB)
Clarke, D., Romano, J.P., and Wolf, M. (2020). The Romano-Wolf multiple-hypothesis correction in Stata. The Stata Journal, 20:812-843. (PDF, 696 KB)
Ledoit, O. and Wolf, M. (2020). Analytical nonlinear shrinkage of large-dimensional covariance matrices. Annals of Statistics, 48:3043-3065. (PDF, 699 KB)

Ledoit, O., Wolf, M., and Zhao Z. (2019). Efficient sorting: A more powerful test for cross-sectional anomalies. Journal of Financial Econometrics, 17:645-686. (PDF, 515 KB)
Engle, R.F., Ledoit, O., and Wolf. M. (2019). Large dynamic covariance matrices. Journal of Business & Economic Statistics, 37:363-375. (PDF, 599 KB)
DiCiccio, C.J., Romano, J.P., and Wolf, M. (2019). Improving weighted least squares inference. Econometrics and Statistics, 10:96-119. (PDF, 825 KB)
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, 1 MB)
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, 30:110-119. (PDF, 1 MB)
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.
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, 2 MB)
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Programming Code

Nguyen, P.A. and Wolf, M. (2024).
Single-firm inference in event studies via the permutation test.
Empirical Economics, 66:2435-2450.
R code (ZIP, 6 KB)
Ledoit, O. and Wolf, M. (2022).
Quadratic shrinkage for large covariance matrices.
Bernoulli, 28:1519-1547.
R code Matlab code Python code

Ledoit, O. and Wolf, M. (2020).
Analytical nonlinear shrinkage of large-dimensional covariance matrices.
Annals of Statistics, 48:3043-3065.
Matlab code (ZIP, 1 KB)

Engle, R.F., Ledoit, O., and Wolf, M. (2019).
Large dynamic covariance matrices.
Journal of Business & Economic Statistics, 37:363-375.
Matlab code (ZIP, 5 MB)

Ledoit O. and Wolf, M. (2017).
Numerical implementation of the QuEST function.
Computational Statistics & Data Analysis, 115:199-223.
Matlab code (ZIP, 755 KB)
Romano, J.P. and Wolf, M. (2017).
Resurrecting weighted least squares.
Journal of Econometrics, 197:1-19.
R code (ZIP, 806 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, 44 KB)Matlab code (ZIP, 7 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, 156 KB) Matlab code (ZIP, 30 KB)
Romano, J.P., Shaikh, A.M., and Wolf M. (2008).
Formalized data snooping based on generalized error rates.
Econometric Theory, 24:404-447.
R code (ZIP, 4 KB)Matlab code (ZIP, 2 MB)
Ledoit, O. and Wolf, M. (2004).
Honey, I shrunk the sample covariance matrix.
Journal of Portfolio Management, 30:110-119.
R code Matlab code Python code
Ledoit, O. and Wolf, M. (2004).
A well-conditioned estimator for large-dimensional covariance matrices.
Journal of Multivariate Analysis, 88:365-411.
R code Matlab code Python code
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.
R code Matlab code Python code
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)
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Working Papers

ZORA Publication List

Publications

Additional Information