Prof. Daniel Peña Sanchez De Rivera.

Title of the Talk: Dimension reduction and forecasting in large data sets of time series
Rector of the Carlos III University of Madrid.
Full Professor at Universidad Carlos III de Madrid. Department of Statistics

Daniel Peña was born in Madrid in 1948. He received his PhD in Industrial Engineering from the Polytechnic University of Madrid, Bachelor’s Degrees in Sociology and Statistics from the Complutense University of Madrid and Business Administration ITP from Harvard. President of Carlos III University of Madrid in the period 2007- 2011 and re-elected in March 2011. He was Director of the Management Committee (1993-2000) and Vice Rector of the Carlos III University of Madrid (1992- 1995), where he is Full Professor of the Department of Statistics. He has also been Full Professor at the Polytechnic University of Madrid, the University of Wisconsin- Madison and the University of Chicago. He is Founding Director of the Quantitative Methods Department of the EOI Business School, of the Statistics Laboratory of the ETSII-UPM (the Higher Technical School for Industrial Engineering at the Polytechnic University of Madrid), as well as the Department of Economics and Statistics and Econometrics of the Carlos III University of Madrid. He has been Director of the “Revista Estadística Española” and President of the Spanish Society of Statistics and Operative Research (Sociedad Española de Estadística e Investigación Operativa).

In the same field, he stands out as the Founding President of the Statistical Methods Committee of the Spanish Association for Quality and member of the State High Council of Statistics, Vice President of the Inter-American Institute of Statistics and President of European Courses in Advanced Statistics.

He has published thirteen books and more than 190 research articles on Statistics, Quality and its Applications. He is Associate Editor of several international journals and has received national and international awards for research. In 2006 he received the Youden Award for the best article published in “Technometrics”.

He is an honorary member of prestigious international associations such as the Institute of Mathematical Statistics and the American Statistical Association.

This information is from: Daniel Peña Sanchez De Rivera (UC3M)

Prof. Siem Jan Koopman
Professor of Econometrics at the Vrije Universiteit Amsterdam. Department of Econometrics

SJK is Professor of Econometrics at the Vrije Universiteit Amsterdam and research fellow at the Tinbergen Institute, both since 1999. Furthermore, he is a long-term Visiting Professor at CREATES, University of Aarhus and a Visiting Researcher at the European Central Bank, Financial Research. Since 2013, he is a Journal of Applied Econometrics Distinguished Author. He held positions at the London School of Economics between 1992 and 1997 and at the CentER (Tilburg University) between 1997 and 1999. In 2002 he visited the US Bureau of the Census in Washington DC as an ASA / NSF / US Census / BLS Research Fellow.

Furthermore, he was a Fernand Braudel Senior Fellow at the Department of Economics, European University Institute, Florence, Italy, in 2010. His Ph.D. is from the LSE and dates back to 1992.

The monograph Time Series Analysis by State Space Methods is written by J. Durbin and SJK. The book originally appeared in 2001. The Second Edition is recently published by Oxford University Press, in May 2012. The Durbin & Koopman 2012 book consists of 368 pages. The book An Introduction to State Space Time Series Analysis appeared in 2007 and is written by J.J.F. Commandeur and SJK. His other books (co-authored, software and editorial) are listed here

The research interests of SJK cover topics in statistical analysis of time series, financial econometrics, simulation-based estimation, Kalman filter, economic forecasting and, more generally, time series econometrics. His number of publications in refereed journals since 1992 is 75 while his work includes 29 entries in books and discussions. His current citation h-index at Thomson Reuters is 18 and at Google Scholar is 37.

He fullfills editorial duties at the Journal of Applied Econometrics and the Journal of Forecasting. Finally he is an OxMetrics software developer and is actively engaged in the development of the time series software packages STAMP and SsfPack.

This information is from: Prof. Siem Jan Koopman

Em.O.Univ.Prof. DI Dr. Manfred DEISTLER.

Title of the Talk: Regular and Singular AR and ARMA Models, The Single and The Mixed Frequency Case: A Structure Theory.
ABSTRACT: A multivariate AR or ARMA system, repectively, is called singular, if its innovation variance matrix is singular, otherwise the system is called regular. Singular AR and ARMA systems naturally occur in dynamic factor models where the number of static factors exceeds the number of dynamic factors, as well as in DSGE models where the number of observations is larger than the number of shocks. The emphasis of the talk is on structure theory, in particular on („constructive“) identifiability and its relation to consistent estimation. We show that identifiability of singular mulivariate AR systems is more intricate compared to the regular case and has similarities to the ARMA case. The final part of the lecture deals with mixed frequency data in case of regular and singular AR an ARMA systems. In particular we show generic identifiability of AR systems from mixed frequency data, whereas for ARMA systems such a result needs additional retrictions.

em.O.Univ.Prof. DI Dr. Manfred DEISTLER is Professor at the Vienna University of Technology, in the Institute of Statistics and Mathematical Methods in Economics. The Unit is: Econometrics and System Theory, in Wiedner Hauptstrasse 8-10, A-1040 Vienna, AUSTRIA.

RESEARCH INTERESTS:

Identification of linear dynamical systems in ARMA and state space representation, structure and estimation, in particular in the multivariate case, data driven local coordinates, subspace identification

Identification of linear dynamical factor- and errors-in-variables models, in particular structure theory

Analysis and prediction of financial time series

Analysis and prediction of business and market data

Analysis of load and price time series for electricity markets

PROJECTS:

Principal investigator of the FWF project P-17065 Identification of multivariate Dynamic Systems

Teamleader of the team TUWIEN of the european research project ERNSI

Co-initiator of and group leader at the industrial mathematics competence center, IMCC, Linz

Member of the austrian academy of sciences

Fellow of the econometric society

Fellow of the Journal of Econometrics

IEEE Fellow

This information is from: Prof. DI Dr. Manfred DEISTLER