CRETA Workshop on Advanced Econometrics 18_Prof. Marc Paolella
Activity day:2015-03-02 
Published At:2015-03-02 
Views:170  2017-02-12 updated

 

CRETA is honored to invite Professor Marc Paolella from University of Zurich as a visitor on March 13. During his visit, Prof. Paolella will lecture on Portfolio Selection with Active Risk Monitoring on CRETA Workshop on Advanced Econometrics 18. The workshop is due to take place on March 13 (Friday) at Raphael, GIS NTU Convention Center . All participants are welcomed! Please be sure to register your attendance online (http://www.creta.org.tw/?news_3=175 ) by noon, March 09 (Friday).

 

*Date: March 13 (Friday), 14:00 pm – 16:30 pm

*Venue: Raphael, GIS NTU Convention Center

*Topic:  Portfolio Selection with Active Risk Monitoring

 

[About the Speaker]

Professor Paolella is currently full professor of Department of Banking and Finance, University of Zurich. Professor Paolella’s research interests focus on Time Series Analysis, Computational Statistics, GARCH and Risk Prediction. His research articles have been published in several prestigious journals, such as Journal of Econometrics, Journal of Banking and Finance, Journal of Financial Econometrics, European Journal of Finance and Journal of the American Statistical Association.

 

[Lecture Overview]

The paper proposes a framework for large-scale portfolio optimization which accounts for all the major stylized facts of multivariate financial returns, including volatility clustering, dynamics in the dependency structure, asymmetry, heavy tails, and non-ellipticity. It introduces a so-called risk fear portfolio strategy which combines portfolio optimization with active risk monitoring. The former selects optimal portfolio weights. The later, independently, initiates market exit in case of excessive risks. The strategy agrees with the stylized fact of stock market major sell-off s during the initial stage of market downturns. The advantages of the new framework are illustrated with an extensive empirical study. It leads to superior multivariate density and Value-at-Risk forecasting, and better portfolio performance. The proposed risk fear portfolio strategy outperforms various competing types of optimal portfolios, even in the presence of conservative transaction costs and frequent rebalancing. The risk monitoring of the optimal portfolio can serve as an early warning system against large market risks. In particular, the new strategy avoids all the losses during the 2008 financial crisis, and it profits from the subsequent market recovery.                                                                   

 

[Program]

March 13 (Friday) Raphael, GIS NTU Convention Center 

13:30-14:00: Registration

14:00-15:00: Lecture

15:00-15:20: Coffee Break

15:20-16:30: Lecture and Discussion

*Lecture in English