Research Seminar Series in Statistics and Mathematics
The Institute for Statistics and Mathematics (Department of Finance, Accounting and Statistics) cordially invites everyone interested to attend the talks in our Research Seminar Series, where internationally renowned scholars from leading universities present and discuss their (working) papers.
The list of talks for the winter term 2018/19 is available via the following link: www.wu.ac.at
We propose a new approach to modeling and forecasting with mixed-frequency regressions (MIDAS) in presence of a large number of predictors. Our approach resorts to penalized regressions such as Lasso and Group Lasso, hence addressing the issue of simultaneously estimating and selecting the model, and relies on Bayesian techniques for estimation. In particular, the penalty hyper-parameters driving the model shrinkage are automatically tuned via an adaptive MCMC algorithm. To achieve sparsity and improve variable selection, we also consider a Group Lasso model augmented with a spike-and-slab prior. Simulations show that the proposed models have good in-sample and out-of-sample performance, even when the design matrix presents very high correlation. When applied to a forecasting model of US GDP, the results suggest that high-frequency financial variables may have some, although limited, short-term predictive content.
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