Overview

a) Questions to be addressed

  • What are the options compared to the "standard" minimum variance approach of Markowitz?
  • What are the advantages and disadvantages of these approaches?
  • Different methods are to be compared empirically using performance and risk measures in an out-of-sample study and the relation to theoretical properties is to be illustrated.


b) Data set to be used

  • A data set is to be selected independently on the basis of the literature.
  • For this purpose, stock, commodity, currency and index returns are conceivable.


c) Additional information for processing

It is necessary to use a real out-of-sample methodology for the evaluation of portfolios with R: "Rolling Window" or "Expanding Window" methods should be used here. These must be programmed using the statistical software R. Helpful in this context are the packages PerformanceAnalytics and fPortfolio.

Literature

Books

 

  • Introductory Statistics with R von Daalgard (in der Bibliothek verfügbar)
  • Time Series Models for Business and Economic Forecasting von Franses, van Dijk und Opschoor, Cambridge University Press (kann per Fernleihe bezogen werden)
  • Probability and Statistics with R von Ugarte, Militino und Arnholt (in der Bibliothek verfügbar)
  • Angewandte Statistik: Methodensammlung mit R vonSachs/Hedderich (in der Bibliothek verfügbar)
  • Introductory Econometrics von Wooldridge (in der Bibliothek verfügbar)
  • The R Book von Crawley (in der Bibliothek verfügbar)
  • Albrecht A., Maurer R. (2005), 2. Auflage Schäffler Poeschel, Investment- und Risikomanagement

 

Starting papers

 

  • Grootveld, H., Hallerbach, W., 1999, Variance vsdownside risk: Is there really that much difference? European Journal of Operational Research, Vol. 114, p. 304-319.
  • Cumova, D., Nawrocki, D., 2011, A symmetric LPM model for heuristic mean-semivariance analysis, Journal of Economics and Business, vol. 63(3), p. 217-236.

Ansprechpartner

Academic Council
Faculty of Business and Economics
  • Phone: +49 821 598 - 4042
  • Email:
  • Room 2319 (Building J)

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