Faculty of Business Administration


Business Economics

Tail Event Driven ASset Allocation:

Evidence from equity and mutual funds’ markets


Prof. Wolfgang Karl HÄRDLE

Ladislaus von Bortkiewicz Chair Professor of Statistics

School of Business and Economics

Humboldt University of Berlin




Classical asset allocation methods have assumed that the distribution of asset returns is smooth, well behaved with stable statistical moments over time. However, with market volatility increasing over time and after recent crises, asset allocators have cast doubts on the usefulness of such static methods that registered large drawdown of the portfolio. Others have suggested dynamic or synthetic strategies as alternatives, which have proven to be costly to implement. The authors propose and apply a method that focuses on the left tail of the distribution and does not require the knowledge of the entire distribution, and may be less costly to implement. The recently introduced TEDAS -Tail Event Driven ASset allocation approach determines the dependence between assets at tail measures. The authors extend TEDAS methodology to three gestalts differing in allocation weights’ determination: a Cornish-Fisher Value-at-Risk minimization, Markowitz diversification rule and naive equal weighting. TEDAS strategies significantly outperform other widely used allocation approaches on two asset markets: German equity and Global mutual funds.


Date:           6 March, 2017 (Monday)

Time:          10:30~11:45

Venue:        Faculty of Business Administration, E22-2011


A Short Biography of Prof. Wolfgang Karl HÄRDLE

Professor Wolfgang Karl Härdle completed his Doctorate in Mathematics at Heidelberg University and received his Habilitation in Statistics and Econometrics at Bonn University. He is currently the Ladislaus von Bortkiewicz Chair Professor of Statistics at the School of Business and Economics of the Humboldt University of Berlin. His research interests are smoothing methods, discrete choice models, statistical modelling of financial markets and computer-aided statistics. He also deals with the modelling of implied volatilities and the statistical analysis of financial risk. He has published extensively and his works have appeared in prestigious journals, among them Annals of Statistics, Econometric Theory, Journal of the American Statistical Association, Journal of Econometrics and Journal of the Royal Statistical Society. He is one of the ‘Highly cited Scientist’ according to the Institute for Scientific Information.