Report NEP-ORE-2018-08-27
This is the archive for NEP-ORE, a report on new working papers in the area of Operations Research. Walter Frisch issued this report. It is usually issued weekly.Subscribe to this report: email, RSS, or Mastodon.
Other reports in NEP-ORE
The following items were announced in this report:
- Joshua C.C. Chan & Eric Eisenstat & Chenghan Hou & Gary Koop, 2018. "Composite Likelihood Methods for Large Bayesian VARs with Stochastic Volatility," Working Paper Series 44, Economics Discipline Group, UTS Business School, University of Technology, Sydney.
- Koop, Gary & Korobilis, Dimitris, 2018. "Variational Bayes inference in high-dimensional time-varying parameter models," MPRA Paper 87972, University Library of Munich, Germany.
- YAMAMOTO, Yohei & 山本, 庸平, 2018. "Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances," Discussion paper series HIAS-E-72, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
- Martin Lettau & Markus Pelger, 2018. "Factors that Fit the Time Series and Cross-Section of Stock Returns," NBER Working Papers 24858, National Bureau of Economic Research, Inc.
- Damir Filipović & Martin Larsson & Francesco Statti, 2017. "Unspanned Stochastic Volatility in the Multi-Factor CIR Model," Swiss Finance Institute Research Paper Series 17-16, Swiss Finance Institute, revised Apr 2018.
- Ian Borg & Germano Ruisi, 2018. "Forecasting using Bayesian VARs: A Benchmark for STREAM," CBM Working Papers WP/04/2018, Central Bank of Malta.
- Costantini, Mauro & Kunst, Robert M., 2018. "On Using Predictive-ability Tests in the Selection of Time-series Prediction Models: A Monte Carlo Evaluation," Economics Series 341, Institute for Advanced Studies.
- Glass, Anthony J. & Kenjegalieva, Karligash & Sickles, Robin C. & Weyman-Jones, Thomas, 2018. "The Spatial Efficiency Multiplier and Common Correlated Effects in a Spatial Autoregressive Stochastic Frontier Model," Working Papers 18-003, Rice University, Department of Economics.
- Barassi, Marco & Horvath, Lajos & Zhao, Yuqian, 2018. "Change Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models," MPRA Paper 87837, University Library of Munich, Germany.