Structural positions and risk budgeting : quantifying the impact of structural positions and deriving implications for active portfolio management

Structural positions are very common in investment practice. A structural position is defined as a permanent overweighting of a riskier asset class relative to a prespecified benchmark portfolio. The most prominent example for a structural position is the equity bias in a balanced fund that arises by consistently overweighting equities in tactical asset allocation. Another example is the permanent allocation of credit in a fixed income portfolio with a government benchmark. The analysis provided in this article shows that whenever possible, structural positions should be avoided. Graphical illustrations based on Pythagorean theorem are used to make a connection between the active risk/return and the total risk/return framework. Structural positions alter the risk profile of the portfolio substantially, and the appeal of active management – to provide active returns uncorrelated to benchmark returns and hence to shift the efficient frontier outwards – gets lost. The article demonstrates that the commonly used alpha – tracking error criterion is not sufficient for active management. In addition, structural positions complicate measuring managers’ skill. The paper also develops normative implications for active portfolio management. Tactical asset allocation should be based on the comparison of expected excess returns of an asset class to the equilibrium risk premium of the same asset class and not to expected excess returns of other asset classes. For the cases, where structural positions cannot be avoided, a risk budgeting approach is introduced and applied to determine the optimal position size. Finally, investors are advised not to base performance evaluation only on simple manager rankings because this encourages managers to take structural positions and does not reward efforts to produce alpha. The same holds true for comparing managers’ information ratios. Information ratios, in investment practice defined as the ratio of active return to active risk, do not uncover structural positions

Portfolio choice and estimation risk : a comparison of Bayesian approaches to resampled efficiency

Estimation risk is known to have a huge impact on mean/variance (MV) optimized portfolios, which is one of the primary reasons to make standard Markowitz optimization unfeasible in practice. Several approaches to incorporate estimation risk into portfolio selection are suggested in the earlier literature. These papers regularly discuss heuristic approaches (e.g., placing restrictions on portfolio weights) and Bayesian estimators. Among the Bayesian class of estimators, we will focus in this paper on the Bayes/Stein estimator developed by Jorion (1985, 1986), which is probably the most popular estimator. We will show that optimal portfolios based on the Bayes/Stein estimator correspond to portfolios on the original mean-variance efficient frontier with a higher risk aversion. We quantify this increase in risk aversion. Furthermore, we review a relatively new approach introduced by Michaud (1998), resampling efficiency. Michaud argues that the limitations of MV efficiency in practice generally derive from a lack of statistical understanding of MV optimization. He advocates a statistical view of MV optimization that leads to new procedures that can reduce estimation risk. Resampling efficiency has been contrasted to standard Markowitz portfolios until now, but not to other approaches which explicitly incorporate estimation risk. This paper attempts to fill this gap. Optimal portfolios based on the Bayes/Stein estimator and resampling efficiency are compared in an empirical out-of-sample study in terms of their Sharpe ratio and in terms of stochastic dominance

How much foreign stocks? : Bayesian approaches to asset allocation can explain the home bias of US investors

US investors hold much less foreign stocks than mean/variance analysis applied to historical data predicts. In this article, we investigate whether this home bias can be explained by Bayesian approaches to international asset allocation. In contrast to mean/variance analysis, Bayesian approaches employ different techniques for obtaining the set of expected returns. They shrink sample means towards a reference point that is inferred from economic theory. We also show that one of the Bayesian approaches leads to the same implications for asset allocation as mean-variance/tracking error criterion. In both cases, the optimal portfolio is a combination the market portfolio and the mean/variance efficient portfolio with the highest Sharpe ratio. Applying the Bayesian approaches to the subject of international diversification, we find that substantial home bias can be explained 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 falling behind the US market portfolio. We also find that the current level of home bias can justified whenever regret aversion is significantly higher than risk aversion. Finally, we compare the Bayesian approaches to mean/variance analysis in an empirical out-ofsample study. The Bayesian approaches prove to be superior to mean/variance optimized portfolios in terms of higher risk-adjusted performance and lower turnover. However, they not systematically outperform the US market portfolio or the minimum-variance portfolio

The specificity and the development of social-emotional competence in a multi-ethnic-classroom

<p>Abstract</p> <p>Background</p> <p>Ethnic diversity in schools increases due to globalization. Thus, the children's social-emotional competence development must be considered in the context of a multi-ethnic classroom.</p> <p>Methods</p> <p>In this study, the social-emotional competence of 65 Asian-American and Latin-American children was observed at the beginning and the end of their kindergarten year.</p> <p>Results</p> <p>Initially, significant differences existed among these ethnic groups in respect to moral reasoning. Furthermore, the male children showed more dysregulated aggression but the female children implemented more moral reasoning than their male counterparts. These ethnic specificities did not disappear over the course of the year. In addition, a significant change in avoidance strategies as well as expressed emotions in the narrative took place over the course of one year.</p> <p>Conclusion</p> <p>Ethnic specificity in social-emotional competence does exist independent of gender at the beginning as well as at the end of the kindergarten year in a multi-ethnic kindergarten classroom.</p

Age and the Neural Network of Personal Familiarity

BACKGROUND: Accessing information that defines personally familiar context in real-world situations is essential for the social interactions and the independent functioning of an individual. Personal familiarity is associated with the availability of semantic and episodic information as well as the emotional meaningfulness surrounding a stimulus. These features are known to be associated with neural activity in distinct brain regions across different stimulus conditions (e.g., when perceiving faces, voices, places, objects), which may reflect a shared neural basis. Although perceiving context-rich personal familiarity may appear unchanged in aging on the behavioral level, it has not yet been studied whether this can be supported by neuroimaging data. METHODOLOGY/PRINCIPAL FINDINGS: We used functional magnetic resonance imaging to investigate the neural network associated with personal familiarity during the perception of personally familiar faces and places. Twelve young and twelve elderly cognitively healthy subjects participated in the study. Both age groups showed a similar activation pattern underlying personal familiarity, predominantly in anterior cingulate and posterior cingulate cortices, irrespective of the stimulus type. The young subjects, but not the elderly subjects demonstrated an additional anterior cingulate deactivation when perceiving unfamiliar stimuli. CONCLUSIONS/SIGNIFICANCE: Although we found evidence for an age-dependent reduction in frontal cortical deactivation, our data show that there is a stimulus-independent neural network associated with personal familiarity of faces and places, which is less susceptible to aging-related changes

Bayesian Asset Allocation and U.S. Domestic Bias

U.S. investors hold much less international stock than is optimal according to mean–variance portfolio theory applied to historical data. We investigated whether this home bias can be explained by Bayesian approaches to international asset allocation. In comparison with mean–variance analysis, Bayesian approaches use different techniques for obtaining the set of expected returns by shrinking the sample means toward a reference point that is inferred from economic theory. Applying the Bayesian approaches to the field of international diversification, we found that a substantial home bias can be explained when a U.S. investor has a strong belief in the global mean–variance efficiency of the U.S. market portfolio, and in this article, we show how to quantify the strength of this belief. We also found that one of the Bayesian approaches 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 U.S. market portfolio and the mean–variance-efficient portfolio with the highest Sharpe ratio

How much foreign stocks? : classical versus Bayesian approaches to asset allocation

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