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- in englischer Sprache -

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This work presents various extensions in the field of portfolio optimization from the statistical point of view. An investor wants to allocate his wealth among different risky assets and has historic price information about these assets as the only source of information. This historic information is only partially reliable as indicator for the future development of the assets’ return characteristics, as both economic fluctuation and return parameters may change over time.

In a first study, various paradigms of asset allocation are presented and compared both theoretically and empirically, utilizing a large universe of common stocks traded on the U.S. market.

The second study is concerned with the quantitative measurement of the diversification effect between different risky assets. Different previous approaches are presented and compared, and an own measure of diversification is presented. Distributional assumptions on the price process yield the possibility to quantify estimation error when applying the measure to different portfolios. An extensive empirical investigation is carried out both for the overall market variation in the last five decades as well as for the behavior of the different measures.

The last study extends the methodoly of portfolio optimization. Without any assumptions on the distribution of the price generating process, recently developed methods of data analysis are utilized to gauge the risk connected to an investment into risky assets. It turns out that whenever risk measures of important economic meaning are used to quantify the risk connected with the investment, the problem can be reformulated in a descriptive and computationally tractable way. Detailed explanations and geometric illustrations clarify the underlying statistical and methodological properties, and both simulated and historical price data are used for an application of the approach. [...]

Schlagworte

Statistik, Finanzmangement, Asset Allocation, Diversification, Market Variation, Portfolio Optimization, US Stocks, Risk Management, Naive Portfolio, Decision under Uncertainty, Robust Estimation, Non-Parametric Methods, Statistical Inference, CRSP Database, Betriebswirtschaftslehre, Ungewissheit