Report NEP-FOR-2019-03-25

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:

• David Turner & Thomas Chalaux, 2019. "Calibrating GDP fan charts using probit models with a comparison to the approaches of the Bank of England and Riksbank," OECD Economics Department Working Papers 1542, OECD Publishing.
• Bastos, João A., 2019. "Forecasting the capacity of mobile networks," MPRA Paper 92727, University Library of Munich, Germany.
• Qiu, Yue & Xie, Tian & Yu, Jun & Zhou, Qiankun, 2019. "Forecasting Equity Index Volatility by Measuring the Linkage among Component Stocks," Economics and Statistics Working Papers 7-2019, Singapore Management University, School of Economics.
• Ekaterina Abramova & Derek Bunn, 2019. "Estimating Dynamic Conditional Spread Densities to Optimise Daily Storage Trading of Electricity," Papers 1903.06668, arXiv.org.
• Sen Gupta, Abhijit & Iyer, Tara, 2019. "Quarterly Forecasting Model for India’s Economic Growth: Bayesian Vector Autoregression Approach," ADB Economics Working Paper Series 573, Asian Development Bank.
• Sang Il Lee & Seong Joon Yoo, 2019. "Multimodal Deep Learning for Finance: Integrating and Forecasting International Stock Markets," Papers 1903.06478, arXiv.org, revised Sep 2019.
• Alasdair Brown & James Reade & Leighton Vaughan Williams, 2018. "Prediction Markets and Poll Releases: When Are Prices Most Informative?," Economics Discussion Papers em-dp2018-02, Department of Economics, University of Reading.
• Matteo Mogliani & Anna Simoni, 2019. "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers 1903.08025, arXiv.org, revised Jun 2020.