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Report NEP-ETS-2022-01-31
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:
- Filip Stanek, 2021, "Optimal Out-of-Sample Forecast Evaluation under Stationarity," CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague, number wp712, Nov.
- Andras Fulop & Jeremy Heng & Junye Li, 2022, "Efficient Likelihood-based Estimation via Annealing for Dynamic Structural Macrofinance Models," Papers, arXiv.org, number 2201.01094, Jan.
- Mestiri, Sami, 2021, "Modelling the volatility of Bitcoin returns using Nonparametric GARCH models," MPRA Paper, University Library of Munich, Germany, number 111116, Dec.
- Tosin B. Fateye & Oluwaseun D. Ajay & Cyril A. Ajay, 2021, "Modelling of Daily Price Volatility of South Africa Property Stock Market Using GARCH Analysis," AfRES, African Real Estate Society (AfRES), number 2021-013, Sep.
- Vladimir Pyrlik & Pavel Elizarov & Aleksandra Leonova, 2021, "Forecasting Realized Volatility Using Machine Learning and Mixed-Frequency Data (the Case of the Russian Stock Market)," CERGE-EI Working Papers, The Center for Economic Research and Graduate Education - Economics Institute, Prague, number wp713, Nov.
- Justin Dang & Aman Ullah, 2021, "Machine Learning Based Semiparametric Time Series Conditional Variance: Estimation and Forecasting," Working Papers, University of California at Riverside, Department of Economics, number 202204, Jan, revised Jan 2022.
- Edoardo Berton & Lorenzo Mercuri, 2021, "An Efficient Unified Approach for Spread Option Pricing in a Copula Market Model," Papers, arXiv.org, number 2112.11968, Dec, revised Feb 2023.