Report NEP-ETS-2020-10-19

This is the archive for NEP-ETS, a report on new working papers in the area of Econometric Time Series. Jaqueson K. Galimberti 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:

• Lukas Boer & Helmut Lütkepohl, 2020. "A Simple Instrument for Proxy Vector Autoregressive Analysis," Discussion Papers of DIW Berlin 1905, DIW Berlin, German Institute for Economic Research.
• Yayi Yan & Jiti Gao & Bin Peng, 2020. "A Class of Time-Varying Vector Moving Average Models: Nonparametric Kernel Estimation and Application," Papers 2010.01492, arXiv.org.
• Julien Royer, 2020. "Conditional asymmetry in ARCH($\infty$) models," Working Papers 2020-21, Center for Research in Economics and Statistics.
• Item repec:cte:wsrepe:30899 is not listed on IDEAS anymore

• Kasun Chandrarathna & Arman Edalati & AhmadReza Fourozan tabar, 2020. "Forecasting Short-term load using Econometrics time series model with T-student Distribution," Papers 2009.13595, arXiv.org.
• Mukherjee, Paramita & Coondoo, Dipankor & Lahiri, Poulomi, 2019. "Forecasting Hourly Prices in Indian Spot Electricity Market," MPRA Paper 103161, University Library of Munich, Germany.
• Benavides Guillermo, 2020. "Asymmetric Volatility Effects in Risk Management: An Empirical Analysis using a Stock Index Futures," Working Papers 2020-10, Banco de México.
• Janusz Gajda & Rafał Walasek, 2020. "Fractional differentiation and its use in machine learning," Working Papers 2020-32, Faculty of Economic Sciences, University of Warsaw.
• Funke, Michael & Loermann, Julius & Tsang, Andrew, 2020. "Volatility transmission and volatility impulse response functions in the main and the satellite Renminbi exchange rate markets," BOFIT Discussion Papers 22/2020, Bank of Finland, Institute for Economies in Transition.
• Nissilä, Wilma, 2020. "Probit based time series models in recession forecasting – A survey with an empirical illustration for Finland," BoF Economics Review 7/2020, Bank of Finland.