Before revision:  We derive a new Fuk-Nagaev inequality for a class of \tau-dependent processes with heavier than Gaussian tails, nesting \alpha-mixing processes as a special case, and establish estimation, prediction, and inferential properties, including convergence rates of the HAC estimator for the long-run variance based on LASSO residuals. An empirical application to nowcasting US GDP growth indicates that the estimator performs favorably compared to other alternatives and that the text data can be a useful addition to more traditional numerical data .
After revision:  We derive a new Fuk-Nagaev inequality for a class of \tau-dependent processes with heavier than Gaussian tails, which is of independent interest .