Scientific Portfolio's special issue of the Research for Institutional Money Management supplement for Pensions and Investment, which aims to provide institutional investors with an academic research perspective on the most relevant issues in the industry today.

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In this paper, we introduce Scientific Portfolio's portfolio analysis and construction philosophy, consistent with the academically validated principles of factor investing, and integrate finance and sustainability into an intuitive framework.

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The Scientific Portfolio (SP) platform assists institutional asset owners in understanding the risks of their portfolios. In this paper we present an implementation of the Instrumented Principal Component Analysis (IPCA) model (Kelly et al., 2019) for portfolios of equity portfolios, such as funds or mandates. We show that this model enable to decompose risk in many dimensions with high accuracy and stability. In contrast to current solutions, this model only requires widely available price data and extends easily to multi-region analysis. We present the model, address issues related to its calibration, and provide analytics that enable the decomposition of risks with a high level of historical and cross-sectional granularity. We also argue that the stability of this model makes its use possible not only in the context of risk analysis but also portfolio optimisation.

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The number of equity funds claiming to be sustainable continues to grow, as well as the regulatory transparency requirements they face. Despite this trend, sustainable finance is facing a double “identity crisis”: on the one hand, civil society is increasingly denouncing financial greenwashing and questioning the real impact of sustainable finance, and on the other hand, practitioners are divided on the (double) materiality definition and the most effective levers needed to make an extra-financial impact. This article aims to assist institutional asset owners faced with these questions as they try to build a sustainable portfolio, whether indexed or active. Based on a review of the academic literature, we highlight that the main building blocks that investors ought to consider – themes, levers (exclusions, allocation, engagement) and data - are interdependent. We then propose a classification of sustainable investments, as well as different levels of ambition in terms of extra-financial impact, that lead to four families of coherent sustainable investment strategies that combine themes, levers and data in a consistent way.

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While methodologies to measure the alignment of a financial portfolio with climate objectives develop rapidly, historical and cross-sectional analysis of greenhouse gas emissions associated with a portfolio has received little attention. Yet understanding the factors that influence these emissions is essential to identifying the levers of a portfolio manager to set ambitious but realistic reduction targets and avoid the phenomenon of “portfolio greenwashing”. This paper introduces a decomposition method inspired by those used in environmental economics which enables to disentangle five factors that influence portfolio emissions. To illustrate our model, we analyze a climate impact index and its benchmark over the period 2014-2019. We show that the index reaches a similar decarbonization rate (-35%) to its benchmark by selecting the least emissions intensive companies within the sectors and the companies that structurally reduce their emissions intensity. In contrast, the benchmark achieves this decarbonization mainly through sector allocation, the most emissive sectors being less represented.

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The transition to a low-carbon economy generates new regulatory, technological, market and reputational risks for the financial sector. These climate-transition risks are mainly analyzed by portfolio managers through bottom-up fundamental approaches such as prospective scenario analysis and company scores. In order to overcome the difficulty of linking climate-transition risks with financial risks and the lack of data, recent research has investigated the impact of these risks on market prices by constructing dedicated factors. This paper contributes to this literature in two ways. First, we propose a new climate transition factor that captures both the sectoral and intra-sectoral dimension of the transition to a low-carbon economy. Second, instead of trying to add this factor to a multi-factor model, we propose to disentangle the effect of climate-transition risks from traditional risks. Our approach thus enables investors to quantify and optimize the amount of risk coming from their exposure to transition sensitive instruments.

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In this article, we estimate the level of risk diversification for a universe of US equity ETFs and observe the benefits of diversification for budgeting of active risk relative to a cap-weighted benchmark. We first introduce a risk model that only needs historical returns to break down relative risk into individual factor-related risk contributions, allowing for the construction of a measure of concentration directly inspired by the Equally weighted Risk Contribution (ERC) concept. We then use this concentration measure to highlight the impact of diversification on tracking error stability and find conclusive empirical evidence that US equity ETFs that have a diversified set of systematic active risk contributions have a more stable tracking error. These results suggest that investors seeking a stable tracking error for active risk budgeting purposes may benefit from selecting those ETFs that have a strong level of risk diversification.

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Institutional asset owners increasingly seek to customize index-linked strategies in order to take their ESG and climate preferences into consideration. This trend away from cap-weighted benchmarks does, however, bring forth challenges for asset owners in fulfilling their fiduciary duties. To address these issues, a new self-indexing approach can provide investors with the tools to fully control the index design process and independently monitor the direct and indirect impacts of customization decisions. A 2023 EDHEC survey of institutional asset owners in North America and Europe reveals that less than half of respondents have the capacity to fully analyze their risk exposures, but more than 90% anticipate the further development of digitalized customization capabilities in the institutional passive investment industry. These findings highlight the significant potential for the use of self-indexing as a solution to help institutional asset owners fulfill their fiduciary responsibilities.

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Despite regulatory efforts to enhance consistency, the increase in funds claiming to be sustainable has led to polemics about some of the funds’ stock holdings having a negative impact on climate change. In contrast to the existing literature which focuses on short term performance, we examine the impact of these controversial stocks on the risk profile of 161 funds with a ‘sustainable investment objective’. We show that excluding these stocks with a naive reallocation technique has a limited effect, which can be further reduced via an optimization procedure. These results suggest that holding stocks with a negative contribution to climate change currently has no justification from a risk perspective.

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The Scientific Portfolio platform provides a comprehensive suite of functionalities designed to support investors in making informed investment decisions. The Investment Philosophy Annex illustrates the core functionalities available, including both financial and ESG considerations, with practical examples that demonstrate their forward-looking and actionable nature.

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