Dr. Roxana Halbleib (née Chiriac)

Research Interests

  • Simulation-based Estimation Methods
  • Financial Econometrics
  • Model Selection
  • Multivariate Volatility Models
  • Methods of Risk Measurement
  • High Frequency Data

-> CV.pdf Version

Peer-reviewed Publications

"Estimating Stable Latent Factor Models by Indirect Inference", forthcoming in Journal of Econometrics (with Giorgio Calzolari)

"Forecasting Covariance Matrices: A Mixed Approach", 2016, Journal of Financial Econometrics, Volume 4, Issue 2, pages 383-417 (with Valeri Voev)

"Estimating GARCH-type Models with Symmetric Stable Innovations: Indirect Inference versus Maximum Likelihood", 2014, Computational Statistics and Data Analysis, Volume 76, pages 158 - 171 (with Giorgio Calzolari and Alessandro Parrini)

"Improving the Value at Risk Forecasts: Theory and Evidence from the Financial Crisis"***, 2012, Journal of Economic Dynamics and Control, Volume 36, Issue 8, Pages 1212-1228 (with Winfried Pohlmeier) ***Previous versions of the paper circulated under the title "How Risky is the Value at Risk?"

"Modelling and Forecasting Multivariate Realized Volatility", 2011, Journal of Applied Econometrics, Volume 26, pages 922-947 (with Valeri Voev)

"Forecasting Multivariate Volatility using the VARFIMA Model on Realized Covariance Cholesky Factors", 2011, Journal of Economics and Statistics (Jahrbücher für Nationalökonomie und Statistik), Vol. 231/1, pages 134-152 (with Valeri Voev), Working Paper Version

Other Publications 

"Messen und Verstehen von Finanzrisiken - Eine Perspektive der Ökonometrie", 2017, Springer, in Messen und Verstehen in der Wissenschaft – Interdisziplinäre Ansätze, Springer Verlag, pages 135-149 (Eds: M. Schweiker, J. Hass, A. Novokhatko and R. Halbleib)

Books

"Messen und Verstehen in der Wissenschaft", 2017, Springer (Eds: M. Schweiker, J. Hass, A. Novokhatko, R. Halbleib)

Working Papers

"A Latent Factor Model for Forecasting Realized Volatilities", 2017, GSDS Working Paper No. 2017-14, (with Giorgio Calzolari and Aygul Zagidullina)

"Estimating Financial Tail Risk Measures by Means of High-Frequency Data: A Scaling Method Approach", 2017, (with Timo Dimitriadis)

"Which Model to Match?", 2015, (with Matteo Barigozzi and David Veredas)

Projects

Heidelberger Akademie der Wissenschaften, WIN-Kolleg - Junior Academy for Young Scholars and Scientists with the topic "Messen und Verstehen der Welt durch die Wissenschaft": Analyzing, Measuring and Forecasting Financial Risks by means of High-Frequency Data

Teaching

Winter Term 2017/2018:

Summer Term 2017:

  • Microeconometrics