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Found 5 papers, 0 papers with code
Estimation and Testing of Forecast Rationality with Many Moments
We in this paper utilize P-GMM (Cheng and Liao, 2015) moment selection procedure to select valid and relevant moments for estimating and testing forecast rationality under the flexible loss proposed by Elliott et al. (2005).
Combining Forecasts under Structural Breaks Using Graphical LASSO
We visualize forecast errors from different forecasters as a network of interacting entities and generalize network inference in the presence of common factor structure and structural breaks.
Inferential Theory for Granular Instrumental Variables in High Dimensions
The Granular Instrumental Variables (GIV) methodology exploits panels with factor error structures to construct instruments to estimate structural time series models with endogeneity even after controlling for latent factors.
Learning from Forecast Errors: A New Approach to Forecast Combinations
Forecasters often use common information and hence make common mistakes.
Optimal Portfolio Using Factor Graphical Lasso
Graphical models are a powerful tool to estimate a high-dimensional inverse covariance (precision) matrix, which has been applied for a portfolio allocation problem.
