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Ein halbes Jahrhundert Judaistik in Frankfurt : das »kleine Fach« feiert 50-jähriges Bestehen
(2020)
Past research suggests that international real estate markets show return characteristics and interrelationships with other asset classes, which probably qualify them as an interesting component of national and international asset allocation decisions. However, the special characteristics of real estate assets are quite distinct from that of financial assets, such as stocks and bonds. This is also the case for real estate return distributions. Therefore, the proper integration of real estate markets into asset allocation decisions requires profound understanding of real estate returns' distributional characteristics .
Because of the particular characteristics of real estate, representing real estate markets through reliable a time-series is a complex task. Consequently, reliable real estate indices with a sufficiently long history in major international real estate markets are only scarcely available. Most of the research that has been done on real estate returns was done for the U.K. and U.S., where eligible indices exist. On the other hand, in other important real estate markets, such as Germany, either little or no research has been perfoimed.
In this analysis, the methodology of Maurer, Sebastian and Stephan (2000) for indirectly deriving an appraisal-based index for the German commercial real estate market will be applied. This approach is solely based on publicly available data from German open-ended real estate investment trusts. It could also provide a solution to deriving a reliable real estate time-series for other markets.
We will extend previous analyses for the U.K. and U.S. to provide additional fundamental insights into the return characteristics of the German commercial real estate market. Despite univariate considerations, the main focus is the interrelationships between various international real estate markets, as well as between those respective markets and the international stock and bond markets.
The classical approaches to asset allocation give very different conclusions about how much foreign stocks a US investor should hold. US investors should either allocate a large portion of about 40% to foreign stocks (which is the result of mean/variance optimization and the international CAPM) or they should hold no foreign stocks at all (which is the conclusion of the domestic CAPM and mean/variance spanning tests). There is no way in between.
The idea of the Bayesian approach discussed in this article is to shrink the mean/variance efficient portfolio towards the market portfolio. The shrinkage effect is determined by the investor's prior belief in the efficiency of the market portfolio and by the degree of violation of the CAPM in the sample. Interestingly, this Bayesian approach leads to the same implications for asset allocation as the mean-variance/tracking error criterion. In both cases, the optimal portfolio is a combination of the market portfolio and the mean/variance efficient portfolio with the highest Sharpe ratio.
Applying both approaches to the subject of international diversification, we find that a substantial home bias is only justified when a US investor has a strong belief in the global mean/variance efficiency of the US market portfolio and when he has a high regret aversion of falling behind the US market portfolio. We also find that the current level of home bias can be justified whenever-regret aversion is significantly higher than risk aversion.
Finally, we compare the Bayesian approach of shrinking the mean/variance efficient portfolio towards the market portfolio to another Bayesian approach which shrinks the mean/variance efficient portfolio towards the minimum-variance portfolio. An empirical out-of-sample study shows that both Bayesian approaches lead to a clearly superior performance compared to the classical mean/variance efficient portfolio.
Predictability and the cross-section of expected returns: a challenge for asset pricing models
(2020)
Many modern macro finance models imply that excess returns on arbitrary assets are predictable via the price-dividend ratio and the variance risk premium of the aggregate stock market. We propose a simple empirical test for the ability of such a model to explain the cross-section of expected returns by sorting stocks based on the sensitivity of expected returns to these quantities. Models with only one uncertainty-related state variable, like the habit model or the long-run risks model, cannot pass this test. However, even extensions with more state variables mostly fail. We derive criteria models have to satisfy to produce expected return patterns in line with the data and discuss various examples.