Report NEP-FOR-2019-09-23

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:

• Fethi Ogunc, 2019. "A Bayesian VAR Approach to Short-Term Inflation Forecasting," Working Papers 1925, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
• Jennifer Castle & Jurgen Doornik & David Hendry, 2018. "Selecting a Model for Forecasting," Economics Series Working Papers 861, University of Oxford, Department of Economics.
• Yi Wu & Sotiris Tsolacos, 2019. "Assessing forecast gains from ‘deep learning’ over time-series methodologies," ERES eres2019_212, European Real Estate Society (ERES).
• Jackson, Emerson Abraham & Tamuke, Edmund, 2019. "Predicting disaggregated tourist arrivals in Sierra Leone using ARIMA model," EconStor Preprints 202547, ZBW - Leibniz Information Centre for Economics.
• Konstantinos Nikolopoulos & Waleed S. Alghassab & Konstantia Litsiou & Stelios Sapountzis, 2019. "Long-Term Economic Forecasting with Structured Analogies and Interaction Groups," Working Papers 19018, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
• Rick Bohte & Luca Rossini, 2019. "Comparing the forecasting of cryptocurrencies by Bayesian time-varying volatility models," Papers 1909.06599, arXiv.org.
• Korobilis, Dimitris, 2019. "High-dimensional macroeconomic forecasting using message passing algorithms," MPRA Paper 96079, University Library of Munich, Germany.
• Jennifer Castle & Takamitsu Kurita, 2019. "Modelling and forecasting the dollar-pound exchange rate in the presence of structural breaks," Economics Series Working Papers 866, University of Oxford, Department of Economics.
• Qiong Wu & Christopher G. Brinton & Zheng Zhang & Andrea Pizzoferrato & Zhenming Liu & Mihai Cucuringu, 2019. "Equity2Vec: End-to-end Deep Learning Framework for Cross-sectional Asset Pricing," Papers 1909.04497, arXiv.org, revised Oct 2021.
• Konstantinos Nikolopoulos & Fotios Petropoulos & Vasco Sanchez Rodrigues & Stephen Pettit & Anthony Beresford, 2019. "A risk-mitigation model driven from the level of forecastability of Black Swans: prepare and respond to major Earthquakes through a dynamic Temporal and Spatial Aggregation forecasting framework," Working Papers 19017, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
• Fernando Borraz & Laura Zacheo, 2018. "Inattention, Disagreement and Internal (In)Consistency of Inflation Forecasts," Documentos de trabajo 2018007, Banco Central del Uruguay.