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Report NEP-FOR-2017-11-19
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:
- Stanislav Anatolyev & Jozef Barunik, 2017, "Forecasting dynamic return distributions based on ordered binary choice," Papers, arXiv.org, number 1711.05681, Nov, revised Jan 2019.
- Goodwin, Thomas & Tian, Jing, 2017, "A state space approach to evaluate multi-horizon forecasts," Working Papers, University of Tasmania, Tasmanian School of Business and Economics, number 2017-15.
- Svetunkov, Ivan & Boylan, John Edward, 2017, "Multiplicative state-space models for intermittent time series," MPRA Paper, University Library of Munich, Germany, number 82487, Nov.
- Item repec:hum:wpaper:sfb649dp2017-025 is not listed on IDEAS anymore
- David Turner, 2017, "Designing fan charts for GDP growth forecasts to better reflect downturn risks," OECD Economics Department Working Papers, OECD Publishing, number 1428, Nov, DOI: 10.1787/e86f1bfc-en.
- Fida Hussain & Asif Mahmood, 2017, "Predicting Inflation and Output in Pakistan: The Role of Yield Spread," SBP Working Paper Series, State Bank of Pakistan, Research Department, number 93, Oct.
- Benjamin R. Auer & Benjamin Mögel, 2016, "How Accurate are Modern Value-at-Risk Estimators Derived from Extreme Value Theory?," CESifo Working Paper Series, CESifo, number 6288.
- Biqing Cai & Jiti Gao, 2017, "A simple nonlinear predictive model for stock returns," Monash Econometrics and Business Statistics Working Papers, Monash University, Department of Econometrics and Business Statistics, number 18/17.