Research

This study analyzes the level of agreement of Sustainable Development Goal (SDG) ratings across five different rating providers. It documents a low level of agreement that is particularly pronounced for companies from the Energy, Healthcare, and Basic Materials sectors. Moreover, the low level of agreement is mostly driven by some individual SDGs. When analyzing implications, we find different return characteristics and risk factor exposures of portfolios sorted according to SDG ratings of different rating providers. Overall, our analyses show that current SDG ratings fail to provide a clear signal of companies’ contribution to the SDGs which can have severe consequences for sustainability transitions and their financing.

We study whether members of voluntary initiatives take advantage of the opportunity to free-ride. To address this question, we investigate from an institutional theory perspective the actual implementation behavior of publicly listed signatories of the United Nations Principles for Responsible Investment (UN PRI) in a difference-in-differences and an event study setting. Our empirical results show that, after signing, UN PRI signatories integrate environmental, social, and governance (ESG) criteria in their business activities significantly more than matched non-signatories from the financial sector, indicating the commitment of the signatories to the UN PRI in general. However, while the initial members show a high commitment to the initiative's principles by increasing their ESG integration performance substantially, new members signing at a later stage of the initiative perform considerably less, and thus undermine the UN PRI’s credibility. 

The paper focuses on investors whose strength of interest in sustainability issues (such as environmental, social, and governance) causes ESG to become a third criterion alongside risk and return in portfolio selection. This causes the efficient frontier to become an efficient surface. This means that an investor’s optimal portfolio is no longer the point of most preferred risk/return tradeoff on the mean-variance (M-V) efficient frontier, but is the point of most preferred risk/return/ESG tradeoff on the investor’s M-V-ESG efficient surface. However, to find such a point requires non-trivial ESG integration which is the name given to the process of integrating ESG into the portfolio construction process after screening. With the third objective transporting the problem into 3D-space, it is difficult to search the efficient surface in any kind of comprehensive fashion using M-V based or other bi-criterion techniques as this is akin to a 2-dimensional being trying to view a 3-dimensional object. To remedy the situation, the paper proposes a tri-criterion approach that computes efficient surfaces and special non-contour curves (called NC-efficient fronts in the paper) that are stretched across the efficient surface so as to dragnet it for the points of best ESG integration within it. Using the methodology and data from the S&P500, the paper conducts computational tests on problems with up to 500 securities and under different constraint conditions so as to know what to expect from the new approach over a range of situations.

We investigated the relationship between corporate environmental, social, and governance (ESG) performance and litigation risk by examining US class action lawsuits. We found that a 1 standard deviation improvement in the ESG controversies of an average company in the sample reduced litigation risk from 3.1% to 2.4%. Moreover, an average company with low ESG performance exhibited a loss in market value twice as large as that of a company with high ESG performance—an abnormal loss of US$1.14 billion. Implementation of our findings with a trading strategy yielded positive monthly alphas, suggesting that investors benefit from lower litigation risk and the insurance-like protection of high ESG performance.

Environmental regulations force car manufacturers to renew the powertrain technology portfolio offered to the customer to comply with greenhouse gas emission targets. In turn, automotive companies face the task of identifying the right powertrain technology portfolio consisting of, e.g., internal combustion engines and electric vehicles. What makes this decision even more challenging is that future market shares of the different technologies are uncertain. This paper presents a new decision-support approach for assembling optimal powertrain technology portfolios while making decision-makers aware of the trade-offs between the achievable profit, the achievable market share, the market share risk, and the greenhouse gas emissions generated by the selected vehicle fleet. 

This paper presents a novel methodology for solving a multi-criteria supplier selection problem considering risk and sustainability. It combines multi-objective optimization with the analytic network process to consider sustainability requirements of a supplier portfolio configuration. To integrate ‘risk’ into the supplier selection problem, we develop a multi-objective optimization model based on the investment portfolio theory introduced by Markowitz. 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 studies 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. 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.

One of the most important factors shaping world outcomes is where investment dollars are placed. In this regard, there is the rapidly growing area called sustainable investing where environmental, social, and corporate governance (ESG) measures are taken into account. With people interested in this type of investing rarely able to gain exposure to the area other than through a mutual fund, we study a cross section of U.S. mutual funds to assess the extent to which ESG measures are embedded in their portfolios. With the mutual funds acting as a filter, the question is: How effective is the sustainable mutual fund industry in carrying out its charge? We find that the industry has substantial leeway to increase the sustainability quotients of its portfolios at even no cost to risk and return, thus implying that the funds are unnecessarily falling short on the reasons why investors are investing in these funds in the first place.

We present a framework for inverse optimization in a Markowitz portfolio model that is extended to include a third criterion. The third criterion causes the traditional nondominated frontier to become a surface. Until recently, it had not been possible to compute such a surface. But by using a new method that is able to generate the nondominated surfaces of tri-criterion portfolio selection problems, we are able to compute via inverse optimization the implied risk tolerances of given funds that pursue an additional objective beyond risk and return. In applying this capability to a broad sample of conventional and socially responsible (SR) mutual funds, we find that there appears to be no significant evidence that social responsibility issues, after the screening stage, are further taken into account in the asset allocation process, which is a result that is likely to be different from what many SR investors would expect.

Computing the nondominated set of a multiple objective mathematical program has long been a topic in multiple criteria decision making. In this paper, motivated by the desire to extend Markowitz portfolio selection to an additional linear criterion (sustainability, etc.), we demonstrate an exact method for computing the nondominated set of a tri-criterion program that is all linear except for the fact that one of its objectives is to minimize a convex quadratic function. With the nondominated set of the resulting quad-lin-lin program being a surface composed of curved platelets, a multiparametric algorithm is devised for computing the platelets so that they can be graphed precisely. In this way, graphs of the tri-criterion nondominated surface can be displayed so that, as in traditional portfolio selection, a most preferred portfolio can be selected while in full view of all other contenders for optimality. Finally, by giving an example for socially responsible investors, we demonstrate that our algorithm can outperform standard portfolio strategies for multicriterial decision makers.

The aim of this paper is to expand the methodological spectrum of socially responsible investing by introducing stochastic sustainability returns into safety first models for portfolio choice. We provide a foundation of the notion of sustainability in portfolio theory and establish a general model for generalized safety first portfolio management with probabilistic constraints and three specifications of it. Moreover, we prove theorems about conditions for unique optimal solutions and for the constraints of one model being more restrictive than those of another. In an empirical part, we calculate the costs of investing according to our approach in terms of less financial return.