Seminar Portfolio Optimization Theory and Practice

Course Description: Part A: Helmut Kotschwar - Head Asset Management Bonds, Absolute Return & Forex, Safra Sarasin, CH - Basel In the practical part we learn how to construct efficient portfolios based on factor risk models and refined alphas. We learn also how to build factor risk models and how to utilize forecasts avoiding typical mistakes of naïve application. We understand the role of portfolio optimization as part of a revolving investment process and can utilize various measures to assess the quality of the optimized portfolios. We also understand major concepts of performance analytics and the implication for the investment organization. As practical exercise and to emphasize understanding, we practice how to program necessary steps in simple R scripts by ourselves. We will build multi factor models following three different approaches. Starting with Fama-French-Style models we will also learn how to create factor models based on Regression or Principal Component techniques. Based on selected risk models we will deconstruct return expectations and refine them to create proper input for unbiased portfolio optimization. Based on the work of Black-Litterman we learn how to neutralize immaterial but natural impact on the revolving portfolio construction process. We will construct optimal portfolios for different purposes, like asset allocation, equity or bond portfolios or liability driven investments, including typical constraints. Finally we will understand the role of the human factor in this theoretical and technical practice and assess typical risks by referring to behavioral biases well documented in scientific literature like Kahnemann, Tversky, et al. We start to become self-critical in making investment decisions. While touching many related subjects we dive deep into the task of constructing optimal portfolios.   Basic Readings: Markowitz, H.M. (March 1952): Portfolio Selection, Journal of Finance 7 (1): 7791. Sharpe, W.F. (1964): -Capital asset prices: A theory of market equilibrium under conditions of risk, Journal of Finance 19 (3): 425442. Fama, E.F., and French, K.R. (1993): Common risk factors in the returns on bonds and stocks, Journal of Financial Economics 33, 353. Grinold, R. and Kahn, R. (2000): Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk, 2nd Edition, New York: McGraw-Hill, 2000. Black F. and Litterman R. (1992): Global Portfolio Optimization, Financial Analysts Journal, September 1992, pp. 2843. Bacon, C. (2008): Practical portfolio performance measurement and attribution, 2nd edition, Wiley 2008. Tversky, A. and Kahneman, D. (1992): Advances in prospect theory: cumulative representation of uncertainty. In: Kahneman, D. , Tversky, A. (Eds.): Choices, values and frames, Cambridge University Press, Cambridge 2000, S. 4466.   Part B: Dr. Vahidin Jeleskovic, University of Kassel The aim of the second part of the course is to use MatLab to program portfolio optimization based on different reward-risk-measures and reward-risk-ratios (e.g. Sharp-ratio). This part of the course is manly based on the paper of Stoyanov, Rachev and Fabozzi (2007): Optimal Financial Portfolios in Applied Mathematical Finance, Vol. 14, P. 401-436. FB 07 Wirtschaftswissenschaften Uni Kassel WiSe 2016/17 Lehrveranstaltungspool FB 07 Dr. Jeleskovic Vahidin