Targeting Predictors Via Partial Distance Correlation With Applications to Financial Forecasting
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Publication:6620922
DOI10.1080/07350015.2021.1895812zbMath1547.62977MaRDI QIDQ6620922
Publication date: 17 October 2024
Published in: Journal of Business and Economic Statistics (Search for Journal in Brave)
Cites Work
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- Partial distance correlation with methods for dissimilarities
- Measuring and testing dependence by correlation of distances
- Sufficient forecasting using factor models
- Sure independence screening in generalized linear models with NP-dimensionality
- Regularized estimation in sparse high-dimensional time series models
- The Adaptive Lasso and Its Oracle Properties
- Forecasting economic time series using targeted predictors
- Covariance matrix estimation for stationary time series
- The three-pass regression filter: a new approach to forecasting using many predictors
- Oracle inequalities for high dimensional vector autoregressions
- Asymptotic theory for stationary processes
- An asymptotic theory for sample covariances of Bernoulli shifts
- Some mixing properties of time series models
- Nonparametric independence screening via favored smoothing bandwidth
- Variable screening for high dimensional time series
- The fused Kolmogorov filter: a nonparametric model-free screening method
- Measuring nonlinear dependence in time-series, a distance correlation approach
- Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Additive Models
- Forecasting Using Principal Components From a Large Number of Predictors
- Sure Independence Screening Adjusted for Confounding Covariates with Ultrahigh-dimensional Data
- Regularization after retention in ultrahigh dimensional linear regression models
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Sparse Additive Models
- Feature Screening via Distance Correlation Learning
- MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC VOLATILITY MODELS
- Semiparametric Ultra-High Dimensional Model Averaging of Nonlinear Dynamic Time Series
- Nonparametric Independence Screening in Sparse Ultra-High-Dimensional Varying Coefficient Models
- Modelling Nonlinear Economic Time Series
- Structural Vector Autoregressive Analysis
- Conditional Distance Correlation
- Nonlinear system theory: Another look at dependence
- Model Selection and Estimation in Regression with Grouped Variables
- Prediction by Supervised Principal Components
- Tests of equal forecast accuracy and encompassing for nested models
- Performance bounds for parameter estimates of high-dimensional linear models with correlated errors
- Sharp Threshold Detection Based on Sup-Norm Error Rates in High-Dimensional Models
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