Sebastian Utz

We analyze the performance, risk, and diversification characteristics of global screened and best-in-class equity portfolios constructed according to Inrate's sustainability ratings. The financial performance of sustainably high-rated portfolios is similar to the risk-adjusted market performance in terms of abnormal returns of a five-factor market model. In contrast, low-rated portfolios exhibit negative abnormal returns. Firms with high sustainability ratings show lower idiosyncratic risk, and higher exposure towards the high-minus-low and the conservative-minus-aggressive factor.

This research presents a novel, state-of-the-art methodology for solving the multi-criteria supplier selection problem considering risk and sustainability. The approach combines multi-objective optimization with the analytic network process to meet the requirements of a supplier portfolio configuration that takes into account sustainability. To integrate the aspect ‘risk’ into the supplier selection problem, we develop a multi-objective optimization model based on the investment portfolio theory introduced by Markowitz. The proposed model is a non-standard portfolio selection problem with four objectives: to minimize the purchasing costs, to select the supplier portfolio with the highest logistics service, to minimize the supply risk, and to order as much as possible from those suppliers with outstanding sustainability performance. The optimization model, which has three linear and one quadratic objective function, is solved by an algorithm that analytically computes a set of efficient solutions and provides graphical decision support through a visualization of the complete and exactly-computed Pareto front (a posteriori approach). The possibility of computing all Pareto optimal supplier portfolios is beneficial for decision makers as they can compare all optimal solutions at once, identify the trade-offs between the criteria, and study how the different aspects of supplier portfolio configuration may be balanced to finally choose the composition that satisfies the purchasing company’s strategy best. The approach has been applied to a real-world supplier portfolio configuration case to demonstrate its applicability and to analyze how the consideration of sustainability requirements may affect the traditional supplier selection and purchasing goals in a real-life setting.

This paper examines the influence of earnings management (EM) and tax aggressiveness (TA) on shareholder wealth and on stock price crash risk (SPCR) of German companies. The sample comprises 820 firm-year observations of 188 non-financial companies listed on German stock exchanges from 2008 to 2014. We apply generalized least square panel regression to overcome autocorrelation and heteroscedasticity problems. EM and TA are not related in terms of affecting shareholder wealth and SPCR. EM has no impact on shareholder wealth but significantly affects SPCR. TA has a significant positive effect on shareholder wealth but no impact on SPCR. Thus, EM practices applied within German companies are non-opportunistic, as they do not affect shareholder wealth and decrease SPCR. TA practices are also non-opportunistic, as they increase shareholder wealth and do not affect SPCR. This study provides insights that can improve managers' accounting choices (EM vs. TA) and alleviate investor concerns about the effect of managers' manipulation strategies. Considering other variables affecting TA, such as discretionary book tax differences, may add further insights to this discussion. The analysis of and comparison with other markets may shed more light on the validity and generalizability of our results. Our investigation of the mutual impact of EM and TA on shareholder wealth and SPCR is novel, and so too is the analysis of whether EM and TA are complementary or substitute for each other in this relationship.

This paper studies the reliability of environmental, social, and governance (ESG) assessments in the case of corporate scandals. Reliable disclosures on ESG assessments may reduce information asymmetries when it comes to due diligence, for instance. We use the press release of corporate scandals, which are seen as being unexpected events, and analyze ESG assessments before, during, and after the event year. We find a significant decline in retrospective controversy indicators during the period in which the scandals are released. Subsequent to the scandals, we document a rebound of these indicators. The assessments of forward-looking indicators indicate slightly significant increases during the scandal period. Moreover, our findings show that aggregated ESG assessments consisting of both retrospective and forward-looking indicators are useless when it comes to predicting corporate scandals. Therefore, the managerial implication of this paper recommends educating managers and investors upon how to obtain a comprehensive vision of the corporate social responsibility of a firm based on single ESG assessment indicators.

We study the relationship of corporate social responsibility (CSR) and the distribution of stock returns for an international sample. Firms with a high level of CSR generally exhibit superior stock price synchronicity in the markets of Europe, Japan, and the United States. In particular, we identify optimal levels of CSR to minimize idiosyncratic risk for each region. Moreover, CSR has a mitigating effect on crash risk in Europe and the United States. In contrast, firms from the Asia-Pacific region display CSR over-investment followed by a higher crash risk. This appears to be a consequence of globalization, which forces firms from Asia-Pacific to overinvest in CSR to adapt western standards.

This paper presents a novel framework for optimizing portfolios using distribution dependent thresholds in Omega ratio to control the downside risk. Portfolios resulting from the maximization of the classical Omega ratio simultaneously maximize the probability of superior performance compared to a threshold point set by an investor and minimize the probability of a worse performance compared to the same threshold. However, there is no mandatory rule or mechanism to choose this threshold point in the Omega ratio optimization model yet. In this paper, we redefine the Omega ratio for a loss averse investor by taking the distribution dependent threshold point as the conditional value-at-risk at an α confidence level (CVaRα) of the benchmark market. The α-value reflects the attitude of an investor towards losses. We then embed this new Omega-CVaRα model in a robust portfolio optimization Framework and present its worst case analysis under three uncertainty sets. The robustness is introduced both in the Omega measure and the CVaRα measure. We show that the worst case Omega-CVaRα robust optimization models are linear programs for mixed and box uncertainty sets and a second order cone program under ellipsoidal sets, and hence tractable in all three cases.We conduct a comprehensive empirical investigation of the classical CVaRα model, the STARRα model, the Omega-CVaRα model, and robust Omega-CVaRα model under a mixed uncertainty set for listed stocks of the S&P 500. The optimal portfolios resulting from the Omega-CVaRα model exhibit a superior performance compared to the classical CVaRα model in the sense of higher expected returns, Sharpe ratios, modified Sharpe ratios, and lesser losses in terms of VaRα and CVaRα values. The robust Omega-CVaRα model under mixed uncertainty set is shown to dominate the Omega-CVaRα model in terms of all performance measures. Furthermore, both the Omega-CVaRα and robust Omega-CVaRα model under a mixed uncertainty set yield significantly lower risk compared to STARRα model in terms of CVaRα and variance values.