Audrone Virbickaite, PhD

Research interests

  • Bayesian statistics
  • Sequential Monte Carlo Methods, particle flters
  • Bayesian non-parametrics
  • State-space models
  • Financial econometrics, time-varying volatility models

-> Personal web-page

-> CV .pdf Version

Working Papers


  1. Virbickaitė;, A., Ausín, C., Galeano, P., 2015. Bayesian Inference Methods for Univariate and Multivariate GARCH Models: a Survey, Journal of Economic Surveys, 29 (1), 76-96, DOI: 10.1111/joes.12046 arXiv:1402.0346
  2. Virbickaitė, A., Lopes, H.F., Ausín, C., Galeano, P., 2014. Particle Learning for Markov Switching Stochastic Volatility Model, Working Paper, UC3M, Statistics and Econometrics Series 14-19.
  3. Virbickaitė, A., Ausín, C., Galeano, P., 2014. A Bayesian Non-Parametric Approach to Asymmetric Dynamic Conditional Correlation Model With Application to Portfolio Selection, Computational Statistics and Data Analysis, In Press, DOI: 10.1016/j.csda.2014.12.005 arXiv:1301.5129v2


Winter Term 2016/2017:

Winter Term 15/16: