Aı̈t-Sahalia, Y. and Xiu, D. (2017). Using principal component analysis to estimate a high dimensional factor model with high-frequency data. Journal of Econometrics 201 384–399.
- Abbe, E. (2017). Community detection and stochastic block models: recent developments. The Journal of Machine Learning Research 18 6446–6531.
Paper not yet in RePEc: Add citation now
- Abbe, E., Fan, J., Wang, K. and Zhong, Y. (2020). Entrywise eigenvector analysis of random matrices with low expected rank. Annals of Statistics 48 1452–1474.
Paper not yet in RePEc: Add citation now
- Agarwal, A., Negahban, S., Wainwright, M. J. et al. (2012). Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions. Annals of Statistics 40 1171–1197.
Paper not yet in RePEc: Add citation now
Ahn, S. and Horenstein, A. (2013). Eigenvalue ratio test for the number of factors.
Ang, A. and Kristensen, D. (2012). Testing conditional factor models. Journal of Financial Economics 106 132–156.
Antoniadis, A. and Fan, J. (2001). Regularized wavelet approximations. Journal of the American Statistical Association 96 939–967.
Athey, S., Bayati, M., Doudchenko, N., Imbens, G. and Khosravi, K. (2018). Matrix completion methods for causal panel data models. Tech. rep., National Bureau of Economic Research.
Bai, J. (2003). Inferential theory for factor models of large dimensions. Econometrica 71 135–171.
- Bai, J. and Li, K. (2012). Statistical analysis of factor models of high dimension. The Annals of Statistics 40 436–465.
Paper not yet in RePEc: Add citation now
Bai, J. and Li, K. (2016). Maximum likelihood estimation and inference for approximate factor models of high dimension. Review of Economics and Statistics 98 298–309.
Bai, J. and Liao, Y. (2016). Efficient estimation of approximate factor models via penalized maximum likelihood. Journal of Econometrics 191 1–18.
Bai, J. and Ng, S. (2002). Determining the number of factors in approximate factor models. Econometrica 70 191–221.
Bai, J. and Ng, S. (2006). Confidence intervals for diffusion index forecasts and inference for factor-augmented regressions. Econometrica 74 1133–1150.
Bai, J. and Ng, S. (2009). Boosting diffusion indices. Journal of Applied Econometrics 24 607–629.
Bai, J. and Ng, S. (2010). Instrumental variable estimation in a data rich environment.
Bai, J. and Ng, S. (2017). Principal components and regularized estimation of factor models. arXiv preprint arXiv:1708.08137 .
- Bai, J. and Ng, S. (2019). Matrix completion, counterfactuals, and factor analysis of missing data. arXiv preprint arXiv:1910.06677 .
Paper not yet in RePEc: Add citation now
Bai, J. and Wang, P. (2016). Econometric analysis of large factor models. Annual Review of Economics 8 53–80.
Baltagi, B. H., Kao, C. and Wang, F. (2017). Identification and estimation of a large factor model with structural instability. Journal of Econometrics 197 87–100.
- Barigozzi, M. and Cho, H. (2018). Consistent estimation of high-dimensional factor models when the factor number is over-estimated. arXiv preprint arXiv:1811.00306 .
Paper not yet in RePEc: Add citation now
Barigozzi, M. and Luciani, M. (2019). Quasi maximum likelihood estimation and inference of large approximate dynamic factor models via the em algorithm. arXiv preprint arXiv:1910.03821 .
Barigozzi, M., Cho, H. and Fryzlewicz, P. (2018). Simultaneous multiple changepoint and factor analysis for high-dimensional time series. Journal of Econometrics 206 187–225.
Barras, L., Scaillet, O. and Wermers, R. (2010). False discoveries in mutual fund performance: Measuring luck in estimated alphas. Journal of Finance 65 179–216.
Belloni, A., Chen, D., Chernozhukov, V. and Hansen, C. (2012). Sparse models and methods for optimal instruments with an application to eminent domain. Econometrica 80 2369–2429.
Belloni, A., Chernozhukov, V. and Hansen, C. (2014). Inference on treatment effects after selection among high-dimensional controls. The Review of Economic Studies 81 608–650.
- Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological) 57 289–300.
Paper not yet in RePEc: Add citation now
- Boucheron, S., Lugosi, G. and Massart, P. (2013). Concentration inequalities: A nonasymptotic theory of independence. Oxford university press.
Paper not yet in RePEc: Add citation now
- Brillinger, D. R. (1964). A frequency approach to the techniques of principal components, factor analysis and canonical variates in the case of stationary time series. In Invited Paper, Royal Statistical Society Conference, Cardiff Wales.(Available at http://stat-www. berkeley. edu/users/brill/papers. html).
Paper not yet in RePEc: Add citation now
Bühlmann, P. and Yu, B. (2003). Boosting with the l2 loss: regression and classification. Journal of the American Statistical Association 98 324–339.
Cai, T. and Liu, W. (2011). Adaptive thresholding for sparse covariance matrix estimation. Journal of the American Statistical Association 106 672–684.
Cai, T., Cai, T. T. and Zhang, A. (2016). Structured matrix completion with applications to genomic data integration. Journal of the American Statistical Association 111 621–633.
- Candès, E. J., Li, X., Ma, Y. and Wright, J. (2011). Robust principal component analysis? Journal of the ACM (JACM) 58 1–37.
Paper not yet in RePEc: Add citation now
- Catoni, O. (2012). Challenging the empirical mean and empirical variance: a deviation study. In Annales de l’IHP ProbabiliteÃŒÂs et statistiques, vol. 48.
Paper not yet in RePEc: Add citation now
- Chan, K.-S. (1993). Consistency and limiting distribution of the least squares estimator of a threshold autoregressive model. Annals of Statistics 21 520–533.
Paper not yet in RePEc: Add citation now
- Chen, D., Mykland, P. A. and Zhang, L. (2019a). The five trolls under the bridge: Principal component analysis with asynchronous and noisy high frequency data. Journal of the American Statistical Association 1–18.
Paper not yet in RePEc: Add citation now
- Chen, E. Y., Tsay, R. S. and Chen, R. (2020a). Constrained factor models for highdimensional matrix-variate time series. Journal of the American Statistical Association 115 775–793.
Paper not yet in RePEc: Add citation now
- Chen, Y., Chi, Y., Fan, J., Ma, C. and Yan, Y. (2020b). Noisy matrix completion: Understanding statistical guarantees for convex relaxation via nonconvex optimization. SIAM Journal on Optimization to appear.
Paper not yet in RePEc: Add citation now
- Chen, Y., Fan, J., Ma, C. and Yan, Y. (2019b). Inference and uncertainty quantification for noisy matrix completion. Proceedings of the National Academy of Sciences 116 22931– 22937.
Paper not yet in RePEc: Add citation now
- Chen, Y., Fan, J., Ma, C. and Yan, Y. (2020c). Bridging convex and nonconvex optimization in robust pca: Noise, outliers, and missing data. arXiv preprint arXiv:2001.05484 .
Paper not yet in RePEc: Add citation now
Cheng, X., Liao, Z. and Schorfheide, F. (2016). Shrinkage estimation of highdimensional factor models with structural instabilities. The Review of Economic Studies 83 1511–1543.
Chernozhukov, V., Hansen, C. B., Liao, Y. and Zhu, Y. (2019). Inference for heterogeneous effects using low-rank estimations. Tech. rep., cemmap working paper.
Chudik, A., Pesaran, M. H. and Tosetti, E. (2011). Weak and strong cross-section dependence and estimation of large panels. The Econometrics Journal 14 C45–C90.
Connor, G. and Linton, O. (2007). Semiparametric estimation of a characteristic-based factor model of stock returns. Journal of Empirical Finance 14 694–717.
Connor, G., Matthias, H. and Linton, O. (2012). Efficient semiparametric estimation of the fama-french model and extensions. Econometrica 80 713–754.
Doz, C., Giannone, D. and Reichlin, L. (2011). A two-step estimator for large approximate dynamic factor models based on kalman filtering. Journal of Econometrics 164 188–205.
Doz, C., Giannone, D. and Reichlin, L. (2012). A quasi-maximum likelihood approach for large, approximate dynamic factor models. The Review of Economics and Statistics 94 1014–1024.
Fama, E. F. and French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics 116 1–22.
Fan, J. and Kim, D. (2019). Structured volatility matrix estimation for non-synchronized high-frequency financial data. Journal of Econometrics 209 61–78.
- Fan, J. and Liao, Y. (2020). Learning latent factors from diversified projections and its applications to over-estimated and weak factors. Available at SSRN 3446097 .
Paper not yet in RePEc: Add citation now
Fan, J. and Lv, J. (2008). Sure independence screening for ultrahigh dimensional feature space. Journal of the Royal Statistical Society, Series B 70 849–911.
- Fan, J. and Zhong, Y. (2018). Optimal subspace estimation using overidentifying vectors via generalized method of moments. arXiv preprint arXiv:1805.02826 .
Paper not yet in RePEc: Add citation now
- Fan, J., Han, X. and Gu, W. (2012). Estimating false discovery proportion under arbitrary covariance dependence. Journal of the American Statistical Association 107 1019–1035.
Paper not yet in RePEc: Add citation now
- Fan, J., Ke, Y. and Liao, Y. (2020a). Augmented factor models with applications to validating market risk factors and forecasting bond risk premia. Journal of Econometrics, forthcoming .
Paper not yet in RePEc: Add citation now
Fan, J., Ke, Y. and Wang, K. (2020b). Factor-adjusted regularized model selection. Journal of Econometrics 216 71–85.
Fan, J., Ke, Y., Sun, Q. and Zhou, W.-X. (2019a). Farmtest: Factor-adjusted robust multiple testing with approximate false discovery control. Journal of the American Statistical Association 114 18801893.
Fan, J., Li, Q. and Wang, Y. (2017a). Estimation of high dimensional mean regression in the absence of symmetry and light tail assumptions. Journal of the Royal Statistical Society, Series B. 79 247–265.
- Fan, J., Li, R., Zhang, C.-H. and Zou, H. (2020c). Statistical Foundations of Data Science. CRC Press, Taylor and Francis, FL.
Paper not yet in RePEc: Add citation now
Fan, J., Liao, Y. and Mincheva, M. (2013). Large covariance estimation by thresholding principal orthogonal complements (with discussion). Journal of the Royal Statistical Society, Series B 75 603–680.
- Fan, J., Liao, Y. and Wang, W. (2016). Projected principal component analysis in factor models. Annals of Statistics 44 219–254.
Paper not yet in RePEc: Add citation now
Fan, J., Liao, Y. and Yao, J. (2015). Power enhancement in high dimensional crosssectional tests. Econometrica 83 1497–1541.
- Fan, J., Wang, D., Wang, K. and Zhu, Z. (2019b). Distributed estimation of principal eigenspaces. Annals of statistics 47 3009.
Paper not yet in RePEc: Add citation now
- Fan, J., Wang, W. and Zhong, Y. (2018). An ℓ∞ eigenvector perturbation bound and its application to robust covariance estimation. Journal of Machine Learning Research 18 1–42.
Paper not yet in RePEc: Add citation now
Fan, J., Wang, W. and Zhong, Y. (2019c). Robust covariance estimation for approximate factor models. Journal of econometrics 208 5–22.
Fan, J., Xue, L. and Yao, J. (2017b). Sufficient forecasting using factor models. Journal of Econometrics 201 292–306.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L. (2000). The generalized dynamic factor model: identification and estimation. The Review of Economics and Statistics 82 540–554.
Forni, M., Hallin, M., Lippi, M. and Reichlin, L. (2005). The generalized dynamic factor model: one-sided estimation and forecasting. Journal of the American Statistical Association 100 830–840.
- Freund, Y. and Schapire, R. E. (1997). A decision-theoretic generalization of on-line learning and an application to boosting. Journal of computer and system sciences 55 119–139.
Paper not yet in RePEc: Add citation now
- Friedman, J. H. (2001). Greedy function approximation: a gradient boosting machine.
Paper not yet in RePEc: Add citation now
Gagliardini, P., Ossola, E. and Scaillet, O. (2016). Time-varying risk premium in large cross-sectional equity data sets. Econometrica 84 985–1046.
Gagliardini, P., Ossola, E. and Scaillet, O. (2019). Estimation of large dimensional conditional factor models in finance. Swiss Finance Institute Research Paper .
Giannone, D., Reichlin, L. and Small, D. (2008). Nowcasting: The real-time informational content of macroeconomic data. Journal of Monetary Economics 55 665–676.
- Giglio, S., Liao, Y. and Xiu, D. (2020). Thousands of alpha tests. Review of Financial Studies, forthcoming .
Paper not yet in RePEc: Add citation now
Goncalves, S. and Perron, B. (2018). Bootstrapping factor models with cross sectional dependence .
Hansen, B. E. (2000). Sample splitting and threshold estimation. Econometrica 68 575– 603.
- Hansen, C. and Liao, Y. (2018). The factor-lasso and k-step bootstrap approach for inference in high-dimensional economic applications. Econometric Theory 1–45.
Paper not yet in RePEc: Add citation now
- Harvey, C. R. and Liu, Y. (2018). False (and missed) discoveries in financial economics. Tech. rep., Duke University.
Paper not yet in RePEc: Add citation now
Imbens, G. W. and Rubin, D. B. (2015). Causal inference in statistics, social, and biomedical sciences. Cambridge University Press.
- Jacod, J. and Protter, P. (2011). Discretization of processes, vol. 67. Springer Science & Business Media.
Paper not yet in RePEc: Add citation now
Juodis, A. and Sarafidis, V. (2020). A linear estimator for factoraugmented fixed-t panels with endogenous regressors. Tech. rep., Monash University, Department of Econometrics and Business Statistics.
Karabiyik, H., Urbain, J.-P. and Westerlund, J. (2019). Cce estimation of factoraugmented regression models with more factors than observables. Journal of Applied Econometrics 34 268–284.
- Ke, Z. T., Fan, J. and Wu, Y. (2015). Homogeneity pursuit. Journal of the American Statistical Association 110 175–194.
Paper not yet in RePEc: Add citation now
- Klopp, O., Lounici, K. and Tsybakov, A. B. (2017). Robust matrix completion. Probability Theory and Related Fields 169 523–564.
Paper not yet in RePEc: Add citation now
- Koltchinskii, V., Lounici, K. and Tsybakov, A. B. (2011). Nuclear-norm penalization and optimal rates for noisy low-rank matrix completion. The Annals of Statistics 39 2302– 2329.
Paper not yet in RePEc: Add citation now
Lam, C. and Yao, Q. (2012). Factor modeling for high-dimensional time series: inference for the number of factors. The Annals of Statistics 40 694–726.
- Lawley, D. and Maxwell, A. (1971). Factor analysis as a statistical method. The second edition ed. Butterworths, London.
Paper not yet in RePEc: Add citation now
Lee, S., Liao, Y., Seo, M. and Y., S. (2020). Factor-driven two-regime regression. Annals of Statistics, forthcoming .
Li, H., Li, Q. and Shi, Y. (2017). Determining the number of factors when the number of factors can increase with sample size. Journal of Econometrics 197 76–86.
Li, J., Todorov, V. and Tauchen, G. (2019). Jump factor models in large cross-sections. Quantitative Economics 10 419–456.
- Li, K.-C. (1991). Sliced inverse regression for dimension reduction. Journal of the American Statistical Association 86 316–327.
Paper not yet in RePEc: Add citation now
Liao, Y. and Yang, X. (2018). Uniform inference for characteristic effects of large continuous-time linear models. Available at SSRN 3069985 .
- Ludvigson, S. and Ng, S. (2016). A factor analysis of bond risk premia 313–371.
Paper not yet in RePEc: Add citation now
- Ma, S., Goldfarb, D. and Chen, L. (2011). Fixed point and bregman iterative methods for matrix rank minimization. Mathematical Programming 128 321–353.
Paper not yet in RePEc: Add citation now
Ma, S., Lan, W., Su, L. and Tsai, C.-L. (2020). Testing alphas in conditional timevarying factor models with high-dimensional assets. Journal of Business & Economic Statistics 38 214–227.
Massacci, D. (2017). Least squares estimation of large dimensional threshold factor models. Journal of Econometrics 197 101–129.
McCracken, M. W. and Ng, S. (2016). Fred-md: A monthly database for macroeconomic research. Journal of Business & Economic Statistics 34 574–589.
- Moon, H. R. and Weidner, M. (2018). Nuclear norm regularized estimation of panel regression models. arXiv preprint arXiv:1810.10987 .
Paper not yet in RePEc: Add citation now
- Negahban, S. and Wainwright, M. J. (2011). Estimation of (near) low-rank matrices with noise and high-dimensional scaling. The Annals of Statistics 39 1069–1097.
Paper not yet in RePEc: Add citation now
Onatski, A. (2010). Determining the number of factors from empirical distribution of eigenvalues. The Review of Economics and Statistics 92 1004–1016.
Onatski, A. (2012). Asymptotics of the principal components estimator of large factor models with weakly influential factors. Journal of Econometrics 168 244–258.
Pelger, M. (2019). Large-dimensional factor modeling based on high-frequency observations. Journal of Econometrics 208 23–42.
- Recht, B., Fazel, M. and Parrilo, P. A. (2010). Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization. SIAM review 52 471–501.
Paper not yet in RePEc: Add citation now
Romano, J. P. and Wolf, M. (2007). Control of generalized error rates in multiple testing.
Romano, J. P., Shaikh, A. M. and Wolf, M. (2008). Control of the false discovery rate under dependence using the bootstrap and subsampling. Test 17 417.
- Schott, J. R. (1994). Determining the dimensionality in sliced inverse regression. Journal of the American Statistical Association 89 141–148.
Paper not yet in RePEc: Add citation now
Seo, M. H. and Linton, O. (2007). A smoothed least squares estimator for threshold regression models. Journal of Econometrics 141 704–735.
Stock, J. and Watson, M. (2002a). Forecasting using principal components from a large number of predictors. Journal of the American Statistical Association 97 1167–1179.
Stock, J. and Watson, M. (2002b). Macroeconomic forecasting using diffusion indexes. Journal of Business & Economic Statistics 20 147–162.
Stock, J. H. and Watson, M. W. (2016). Dynamic factor models, factor-augmented vector autoregressions, and structural vector autoregressions in macroeconomics. In Handbook of macroeconomics, vol. 2. Elsevier, 415–525.
Storey, J. D. (2002). A direct approach to false discovery rates. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64 479–498.
Su, L. and Wang, X. (2017). On time-varying factor models: Estimation and testing. Journal of Econometrics 198 84–101.
Su, L., Miao, K. and Jin, S. (2019). On factor models with random missing: Em estimation, inference, and cross validation. SMU Economics and Statistics Working Paper Series, No. 04-2019 .
Wang, D., Liu, X. and Chen, R. (2019a). Factor models for matrix-valued highdimensional time series. Journal of econometrics 208 231–248.
Wang, S., Yang, H. and Yao, C. (2019b). On the penalized maximum likelihood estimation of high-dimensional approximate factor model. Computational Statistics 34 819–846.
Westerlund, J. and Urbain, J.-P. (2013). On the estimation and inference in factoraugmented panel regressions with correlated loadings. Economics Letters 119 247–250.
- Xia, D. and Yuan, M. (2019). Statistical inferences of linear forms for noisy matrix completion. arXiv preprint arXiv:1909.00116 .
Paper not yet in RePEc: Add citation now
Xiong, R. and Pelger, M. (2019). Large dimensional latent factor modeling with missing observations and applications to causal inference. arXiv preprint arXiv:1910.08273 .
- Zhu, Z., Wang, T. and Samworth, R. J. (2019). High-dimensional principal component analysis with heterogeneous missingness. arXiv preprint arXiv:1906.12125 .
Paper not yet in RePEc: Add citation now