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SSRN RANKINGS
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Data Snooping, Multiple Testing, Alpha Testing, Factor Models, Hedge Fund Performance, False Discovery Rate, Machine Learning, Missing Data, Wild-Bootstrap, Matrix Completion
High dimensionality, approximate factor model, unknown factors, principal components, sparse matrix, low-rank matrix, thresholding, cross-sectional correlation
machine learning, factor model, double descent, dense signals
approximate factor model, high dimensionality, sieve approximation, semi-parametric
machine learning, forecast confidence interval, neural networks, factor models, portfolio selection, asymptotic theory
Focused GMM, Sparsity recovery, Endogenous variables, Oracle property, Conditional moment restriction, Estimating equation, Over identification, Global minimization, Semi-parametric efficiency
machine learning explainability, uncertainty, forecast confidence intervals
sparse estimation, thresholding, cross-sectional correlation, common factors, idiosyncratic, seemingly unrelated regression
sparse alternatives, thresholding, large covariance matrix estimation, Wald-test, screening, cross-sectional independence, factor pricing model
Huber loss, Heavy tails, Forecasts, Fama-French factors, Large dimensions
factor models, spiked low rank matrix, matrix completion, unbalanced panel, factor adjustments, robustness, model section, multiple testing, high-dimensional
Large dimensions, random projections, over-estimating the number of factors, principal components, factor-augmented regression
asset pricing, high-frequency data, latent factor model, nonparametric test, PCA, systematic risk
High dimensionality, unknown factors, principal components, sparse matrix, conditional sparse, thresholding, cross-sectional correlation, penalized maximum likelihood, adaptive lasso, heteroskedasticity
fiscal policy, threshold regression, recession
Large dimensions, high-frequency data, cross-sectional bootstrap
partial identification, posterior consistency, concentration rate, support function, two-sided Bayesian credible sets, identified set, coverage probability, moment inequality models
classification, consistency, partial identification, moment condition, EL-posterior
high-dimensional models, penalization, shrinkage, non-sparse signal recovery
High dimensionality, unknown factors, conditional sparsity, thresholding, cross-sectional correlation, heteroskedasticity, optimal weight matrix, interactive effect
large-scale inference, stochastic gradient descent, subgradient
COVID-19, trend filtering, knots, piecewise linear fitting, Hodrick-Prescott filter
asset pricing, high-frequency data, latent factor model, nonparametric test, PCA
Identified region, limited information likelihood, consistent set estimation, maximum posterior, model and moment selection
Identified Region, Limited Information Likelihood, Sieve Approximation, Nonparametric Instrumental Variable, Ill-Posed Problem, Partial Identification, Bayesian Inference
threshold regression, factors, mixed integer optimization, panel data, phase transition, oracle properties, l0-penalization
