Report NEP-FOR-2022-06-20

This is the archive for NEP-FOR, a report on new working papers in the area of Forecasting. Rob J Hyndman issued this report. It is usually issued weekly.

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Other reports in NEP-FOR

The following items were announced in this report:

• Udai Nagpal & Krishan Nagpal, 2022. "Cluster-based Regression using Variational Inference and Applications in Financial Forecasting," Papers 2205.00605, arXiv.org, revised Dec 2023.
• Reisenhofer, Rafael & Bayer, Xandro & Hautsch, Nikolaus, 2022. "HARNet: A convolutional neural network for realized volatility forecasting," CFS Working Paper Series 680, Center for Financial Studies (CFS).
• Tae-Hwy Lee & Shahnaz Parsaeian & Aman Ullah, 2022. "Forecasting under Structural Breaks Using Improved Weighted Estimation," Working Papers 202210, University of California at Riverside, Department of Economics.
• James Mitchell & Aubrey Poon & Dan Zhu, 2022. "Constructing Density Forecasts from Quantile Regressions: Multimodality in Macro-Financial Dynamics," Working Papers 22-12R, Federal Reserve Bank of Cleveland, revised 11 Apr 2023.