Report NEP-ETS-2018-03-12

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.

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Other reports in NEP-ETS

The following items were announced in this report:

• Koen Jochmans & Taisuke Otsu, 2018. "Likelihood corrections for two-way models," STICERD - Econometrics Paper Series 598, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
• Javier Hidalgo & Marcia M Schafgans, 2017. "Inference Without Smoothing for Large Panels with Cross- Sectional and Temporal Dependence," STICERD - Econometrics Paper Series 597, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
• Giovanni Angelini & Emanuele Bacchiocchi & Giovanni Caggiano & Luca Fanelli, 2017. "Uncertainty Across Volatility Regimes," CESifo Working Paper Series 6799, CESifo.
• Mark Fisher & Mark J. Jensen, 2018. "Bayesian Inference and Prediction of a Multiple-Change-Point Panel Model with Nonparametric Priors," FRB Atlanta Working Paper 2018-2, Federal Reserve Bank of Atlanta.
• He, Zhongfang, 2018. "A Class of Generalized Dynamic Correlation Models," MPRA Paper 84820, University Library of Munich, Germany.
• Yuzhi Cai & Julian Stander, 2018. "The threshold GARCH model: estimation and density forecasting for financial returns," Working Papers 2018-23, Swansea University, School of Management.
• Yuzhi Cai & Guodong Li, 2018. "A novel approach to modelling the distribution of financial returns," Working Papers 2018-22, Swansea University, School of Management.
• Asai, M. & McAleer, M.J., 2018. "Bayesian Analysis of Realized Matrix-Exponential GARCH Models," Econometric Institute Research Papers 2018-005/III, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
• Leon, Costas, 2018. "An Evaluation of Singular Spectrum Analysis-Based Seasonal Adjustment," MPRA Paper 84594, University Library of Munich, Germany.
• Timmermann, Allan, 2018. "Forecasting Methods in Finance," CEPR Discussion Papers 12692, C.E.P.R. Discussion Papers.
• Chang, Jinyuan & Yao, Qiwei & Zhou, Wen, 2017. "Testing for high-dimensional white noise using maximum cross-correlations," LSE Research Online Documents on Economics 68531, London School of Economics and Political Science, LSE Library.