We develop a penalized two-pass regression with time-varying factor loadings. The penalization in the first pass enforces sparsity for the time-variation drivers while also maintaining compatibility with the no arbitrage restrictions by regularizing appropriate groups of coefficients. The second...

We consider inference of predictive regression with multiple predictors. Extant tests for predictability, including those constructed with robustness to unknown persistence and endogeneity of predictors, may perform unsatisfactorily and tend to discover spurious predictability as the number of...

Inference of predictive regression over multiple horizons is challenging because of over- lapping observations. We show that the size of the test based on the popular Hodrick standard errors can approach one if the horizon grows at a faster rate than the rotated norm of short-run predictability...

The predictability of long-term asset returns increases with the time horizon as estimated in regressions of aggregated-forward returns on aggregated-backward predictive variables. This previously established evidence is consistent with the presence of common slow-moving components that are...

Strong consistency of least squares estimators of the slope parameter in simple linear regression models is established for predetermined stochastic regressors. The main result covers a class of models which falls outside the applicability of what is presently available in the literature. An...