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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.Subscribe to this report: email, RSS, or Mastodon, or Bluesky.
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, OECD Publishing, number 1542, Mar, DOI: 10.1787/c5ca6eb6-en.
- Bastos, João A., 2019, "Forecasting the capacity of mobile networks," MPRA Paper, University Library of Munich, Germany, number 92727, Mar.
- Yue Qiu & Tian Xie & Jun Yu & Qiankun Zhou, 2019, "Forecasting Equity Index Volatility by Measuring the Linkage among Component Stocks," Economics and Statistics Working Papers, Singapore Management University, School of Economics, number 7-2019, Mar.
- Ekaterina Abramova & Derek Bunn, 2019, "Estimating Dynamic Conditional Spread Densities to Optimise Daily Storage Trading of Electricity," Papers, arXiv.org, number 1903.06668, Mar.
- Abhijit Sen Gupta & Tara Iyer, 2019, "Quarterly Forecasting Model for India’s Economic Growth: Bayesian Vector Autoregression Approach," ADB Economics Working Paper Series, Asian Development Bank, number 573, Mar.
- Sang Il Lee & Seong Joon Yoo, 2019, "Multimodal Deep Learning for Finance: Integrating and Forecasting International Stock Markets," Papers, arXiv.org, number 1903.06478, Mar, revised Sep 2019.
- Alasdair Brown & James Reade & Leighton Vaughan Williams, 2018, "Prediction Markets and Poll Releases: When Are Prices Most Informative?," Economics Discussion Papers, Department of Economics, University of Reading, number em-dp2018-02, Mar.
- Matteo Mogliani & Anna Simoni, 2019, "Bayesian MIDAS Penalized Regressions: Estimation, Selection, and Prediction," Papers, arXiv.org, number 1903.08025, Mar, revised Jun 2020.