David Veredas Rojo

David Veredas Rojo

David Veredas Rojo
Universite Libre de Bruxelles    BELGICA

David Veredas is Professor at the Solvay Brussels School of Economics and Management of the Université libre de Bruxelles (ULB). His research is, broadly, in quantitative finance. Namely, volatility, tail and systemic risks, and vast dimensional and complex financial systems. He has published numerous articles in international peer-review journals on these topics, including top-field outlets. He also writes regularly opinion pieces in newspapers and participates in finance-related policy debates.

In 2007 Prof. Veredas was a founding member of the Society for Financial Econometrics (SoFiE), since September 2010 he directs the Quantitative Finance group of the School, in 2012 he was appointed Honorary Visiting Professor at Cass Business School (London), and in 2013 he founded the Advanced Master in Quantitative Finance at the ULB.

Prof. Veredas holds a BA in Economics and a BA in Statistics from University Carlos III de Madrid, and a MA and a PhD in Economics from the Université catholique de Louvain (CORE). Prior to joining the ULB, he was a post-doctoral fellow at CIRANO, Montreal, and a Marie Curie post-doctoral fellow at CentER, Tilburg. In the spring terms of 2010 and 2012 he visited Stern School of Business -hosted at the Volatility Institute- of New York University, and the research department of the Banco de España in Madrid.

Research stay at UC3M: DEPARTMENT OF STATISTICS

Project: The goal of the research is the development of statistical and econometric methods for risk quantification in vast dimensional and complex financial systems. More in particular, develop inference for large dimensional heavy-tailed distributions.

Extreme movements in asset prices are responsible for tail risk. Benoit Mandelbrot, back in 1963, already pointed out fat tails in financial returns, but they have received little attention among the practitioners since most of the financial models rely on Gaussianity. This distributional assumption is the basis of the modern portfolio analysis and option pricing. However, the last financial crisis, characterized by large and unexpected extreme movements in asset prices, has clearly shown the failure of such assumption.

Among the existing heavy-tailed distributions, the family of alpha-stable distributions, of which the Gaussian is a special case, represents a natural generalization due to its own Central Limit Theorem. Numerous studies have found this family of distributions to be more appropriate for modeling asset returns. Extensions to the vast dimensional framework are not straightforward. The general multivariate alpha-stable distribution is intractable due to the spectral measure.

Prof. Veredas will develop a methodology for vast dimensional heavy tailed models. The building block will be the Method of Simulated Quantiles of Dominicy and Veredas (Journal of Econometrics, 2013) and its extension to the elliptical distributions of Dominicy, Ogata and Veredas (Computational Statistics, 2013). First he will provide simple, reliable and fast estimators while applicable to vast dimensions. Second, he will develop the asymptotic results that show the theoretical appropriateness of the method.

Stay Period: FEB 2014 - JUL 2014