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Report NEP-ETS-2022-02-21
This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Yong Yin issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
Other reports in NEP-ETS
The following items were announced in this report:
- Luke De Clerk & Sergey Savl'ev, 2022, "A machine learning search for optimal GARCH parameters," Papers, arXiv.org, number 2201.03286, Jan.
- Ke-Li Xu & Junjie Guo, 2021, "A New Test for Multiple Predictive Regression," CAEPR Working Papers, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington, number 2022-001 Classification-C, Dec.
- Debasis Kundu, 2021, "Stationary GE-Process and its Application in Analyzing Gold Price Data," Papers, arXiv.org, number 2201.02568, Oct.
- Patrik Guggenberge & Frank Kleibergen & Sophocles Mavroeidis, 2022, "A Test for Kronecker Product Structure Covariance Matrix," Economics Series Working Papers, University of Oxford, Department of Economics, number 962, Jan.
- Chen, Yunxiao & Li, Xiaoou, 2022, "Determining the number of factors in high-dimensional generalized latent factor models," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 111574, Sep.
- Kristoffer Pons Bertelsen, 2022, "The Prior Adaptive Group Lasso and the Factor Zoo," CREATES Research Papers, Department of Economics and Business Economics, Aarhus University, number 2022-05, Jan.
- Kenichi Shimizu, 2022, "Asymptotic properties of Bayesian inference in linear regression with a structural break," Working Papers, Business School - Economics, University of Glasgow, number 2022_05, Feb.
- Chen, Yudong & Wang, Tengyao & Samworth, Richard J., 2022, "High-dimensional, multiscale online changepoint detection," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library, number 113665, Feb.