Francesco Audrino

Francesco Audrino

Francesco Audrino

Prof. Ph.D.
M+S
Bodanstrasse 6
9000 St. Gallen
Publications Publications of Francesco Audrino
Main Focuses
  • Computational Statistics
  • Financial Econometrics
  • Machine Learning
Fields of research
  • Computational Statistics applied to Economics and Finance
  • Financial Econometrics
  • Volatility Estimation and Forecasting
  • Regime-switching Models
Education
  • Diploma in Mathematics (direction Financial and Insurance Mathematics, special direction Risk Management), ETH of Zurich.
  • Ph. D. in Statistics/Finance, ETH Zürich. Title of the Thesis: Statistical Methods for High-Multivariate Financial Time Series.
  • Diploma di Specialista in contabililità e finanza con attestato professionale federale.
Professional Career
  • September 1997 - March 1999: Teaching Assistant in Mathematics(Analysis), ETH Zürich.
  • April 1999 - March 2002: Head Assistant in Probability/Statistics, ETH Zürich.
  • April 2002 - March 2004: Scientific Researcher (post-doc) in Statistics and Econometrics, Institute of Finance, University ofLugano (USI), Lugano.
  • April 2004 - August 2009: Assistant Professor for Research, Grant of the "Foundation for Research and Development of the University of Lugano", Institute of Finance, USI, Lugano.
  • September 2009 - December 2009: Visiting Professor, USI, Lugano.
  • October 2006 - present: Professor of Statistics, University of St. Gallen.
  • October/November 2013: Visiting Professor, Pontifical Catholic University (PUC), Rio de Janeiro. 
Teaching Activities
  • Bachelor level: Statistics, VWL, University of St. Gallen.
  • Master of Arts in Quantitative  Economics and Finance: Statistics, University of St. Gallen.
  • Master of Arts in Quantitative  Economics and Finance: Advanced Statistics, University of St. Gallen.
  • Master of Arts in Quantitative Economics and Finance, Master in Business and Finance: Financial Volatility, University of St. Gallen.
  • Ph.D. in Economics and Finance: Computational Statistics, University of St. Gallen.
  • Ph.D. in Economics and Finance: Literature Seminar, University of St. Gallen.
  • Ph.D. in Economics and Finance: Ph.D. Seminar, University of St. Gallen.
Projects
  • April 2002 - March 2004: "Multivariate methods for high-dimensional volatility matrices estimation" (project director), part of NCCR FINRISK Project 6 about "Interest Rate and Volatility Risk".
  • April 2004 -  March 2010: Senior participant in the NCCR FINRISK Project 6 about "Interest rate and volatility risk" and Project 8 about "New methods in theoretical and empirical asset pricing".
  • April 2004 - August 2009: "Multivariate FGD techniques for implied volatility surfaces estimation and term structure forecasting" (project director), Grant of the Foundation for Research and Development of the University of Lugano.
  • June 2010 - May 2013: "Applying Recent Developments in Computational Statistics to Behavioral Asset Pricing and Portfolio Selection" (project co-director), SNF Grant.
  • October 2012 - September 2015: "Analysis and models of cross asset dependency structures in high-frequency data" (project co-director), SNF Grant.
  • August 2017 - July 2020: "SentiVol: Sentiment Analysis and Bayesian Model Averaging for Volatility Prediction" (project director), SNF Grant.
  • September 2017 - August 2019: "Causal Analysis with High-dimensional Financial Data" (project co-director), HSG Grant.
Affiliations
  • Computational Financial Econometrics (CFE) Network fellow (since 2008).
  • 2016-2020: Elected Member of the Board of Directors of the European Regional Section of the International Association for Statistical Computing (ERS-IASC).
  • Member of the Society for Financial Econometrics (since 2008).
  • Member of the International Association for Statistical Computing (IASC) (since 2006).

Additional Information

The main codes used for the FGD estimation together with some simple examples can be found on this website.

Consultation hour: By appointment (email).

Alexandria Further information about Francesco Audrino