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Our interest in this paper is focused on actuarial models of long-term savings, and on potential econometric improvements of such models. The objective, in a nutshell, is to have a feasible method for a market timing strategy including comparisons of assets or portfolios.
We will first revisit the utility function based investment approach that leads to a conditional mean-variance-ratio based strategy. While the general strategy, the set of potential predictors and objective functions are guided by economic theory, the estimation and prediction strategy is purely data-adaptive. The reason for this is our target of providing a Market time strategy that is feasible using only the limited information given in practise to e.g. insurance companies.
Stefan Sperlich made his diploma in mathematics at the University of Göttingen and holds a PhD in economics from the Humboldt University of Berlin. From 1998 to 2006 he was Professor for statistics at the University Carlos III de Madrid, from 2006 to 2010 chair of econometrics at the University of Göttingen, and is since 2010 professor for statistics and econometrics at the University of Geneva. His research interests are ranging from nonparametric statistics over small area statistics to empirical economics, in particular impact evaluation methods and empirical finance. He is cofounder of the research center 'Poverty, Equity and Growth in Developing Countries’ at the University of Göttingen, and is research fellow at the Center for Evaluation and Development (Mannheim, Germany). He published in various top ranked scientific journals of different fields and was awarded with the Koopmans econometric theory prize (among other prizes).
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