Università degli studi di Modena e Reggio Emilia

This paper empirically investigates the role of Circular Economy (CE) in explaining firms' probability of default (PD) in the short and the medium term. Based on the 3R principles of CE, we identify three main dimensions of circularity whose mean represents an overall circularity score. The first, Reduce, measures the degree of reduction in GHG emissions with respect to the previous year, the second, Reuse, measures the share of renewable energy used and the third, Recycle, measures the share of waste recycled or recovered. We adopt and OLS regression over a sample of 108 European companies, from the STOXX Europe 600 Index over the period 2017 – 2021. Three main results emerge. First, both in the short and medium term circularity practices are associated to a lower PD even after accounting for usual economic – financial indicators. Second, among the three dimensions of circularity the really relevant one is Reduce. Third, when comparing the effect of circularity in the short term versus the medium term, it emerges that the negative relationship with the PD is more pronounced in the short term, suggesting that immediate benefits of CE (e.g. tax benefits, easier access to credit, better reputation) offset implementation costs, which instead can be amortized over years. These results are of interests both for managers, who may exploit the negative association of CE and PD, and for supranational institutions that via circularity regulation may also contribute to a more stable financial system.

This paper empirically investigates the performance of portfolio screening strategies based on ESG (Environmental, Social, Governance) scores, by testing three main hypotheses motivated by the introduction of sustainability considerations within portfolio theory: i) ESG screened portfolios overperform the benchmark in the long term only if the exclusion threshold is low; ii) ESG screened portfolios do not overperform the benchmark in the short term independently of the exclusion threshold; iii) ESG screened portfolios overperform the benchmark in terms of systemic risk in periods of financial distress. To this end, negative and positive screening strategies based on Bloomberg ESG disclosure scores and different screening thresholds are set up from the 559 stocks belonging to the EURO STOXX index in the period 2007-2021. The risk-adjusted performance of the ESG screened portfolios is compared with the benchmark-passive one based on Sharpe Ratio (SR) and alphas (from both a one-factor model and the Carhart four-factor model) so as to test performance over total and systemic risk respectively. Two main results emerge. First, we prove overperformance of screened portfolios only in the long run and in the presence of negative screening strategies with a low screening threshold. Second, we do not find clear evidence of over-compensation for systemic risk in all periods of financial distress, thus the alleged safe-haven property of ESG portfolios is not always there. Given the increasing attention for sustainability, our results have relevant implications for both individual investors and the asset management industry.

The introduction of the Environmental, Social, Governance (ESG) dimensions in setting up optimal portfolios has been becoming of uttermost importance for the financial industry. Given the absence of consensus in empirical literature and the limited number of studies providing performance comparison of ESG strategies, the aim of this paper is to assess the impact of ESG on optimal portfolios and to compare different approaches to the construction of ESG compliant portfolios. Following Varmaz et al. (2022) optimization model, we minimize portfolio residual risk by imposing a desired level of portfolio average systemic risk and ESG (measured by Bloomberg ESG score) over both an unscreened and a screened sample based on the 586 stocks of the EURO STOXX Index in the period January 2007 – August 2022. Three are the main results. First, regardless of the level of portfolio systemic risk, the Sharpe ratio of the optimal portfolios worsens as the target ESG level increases. Second, the Sharpe ratio dynamics of portfolios with the highest average ESG scores follows market phases: it is very close to/higher than other portfolios in bull markets, whereas it underperforms in stable or bear markets suggesting that ESG portfolios do not seem to represent a safe haven. Third, negative screenings with medium low threshold reduce the performance of optimal portfolios with respect to optimization over an unscreened sample. However, when adopting a very severe screening we obtain a superior performance implying that very virtuous companies allows investors to do well by doing good.

This paper analyses the impact of screening strategies based on ESG (Environmental, Social, Governance) scores, with a focus on periods of financial distress such as the 2008 global recession and the 2020 Covid-19 pandemic. To this end, negative and positive screening strategies based on Bloomberg ESG disclosure scores and different screening thresholds are set up from the 559 stocks belonging to the EURO STOXX index in the period 2007-2021. To compare ESG portfolios performance with a benchmark passive strategy, we compute risk-adjusted performance measures: the Sharpe ratio and the alphas resulting from both a one-factor model and the Carhart four-factor model. Three main results emerge. First, each single ESG dimension has a different role in determining performance: environmental and governance screens, and the combined ESG ones, generally lead to over performance, in contrast to the social screens. Second, ESG screens represent better performing strategies in the long-term, whereas, when the focus is on times of financial distress, the passive strategy appears to perform better and ESG portfolios do not seem to represent a safe haven. Finally, positive screening strategies, and in particular those based on the social dimension, limit diversification benefits and are characterized by significant underperformance during periods of crises. These results are useful to address ESG portfolio optimization and to gauge the role that finance may have in support of sustainable economic development.

Fostered by an empirical literature providing disparate evidence on the green premium, we propose a two-factor model to explain returns on green bonds not only as a function of market risk but also of the bond greenness. The second factor can be interpreted as a greenness premium, which can be either positive or negative depending on the product of the price given by the market to greenness and the sensitivity of the specific green bond to the latter. Based on the model proposed and its Fama-Mac Beth estimation on a sample of Euro-denominated bonds over the period 08.10-2014-31.12.2019, we are able to conclude that the market does price greenness, but the price is very small: including Government green bonds is 0.7 bps, and focusing on corporate green bonds only is – 1.3 bps. In all cases the dynamics of the price for greenness has a positive drift as the market reaches a more mature phase, landing to a positive average value (2 bps), which implies greenness being viewed as a small penalty. However, differences emerge when we look at the issuer sector level and at single bonds, thus our model is able to explain the disparate empirical evidence provided by the literature on the greenium. On the whole, results hint to a market where the difference in pricing between conventional and green bonds is, ceteris paribus, shrinking, which is consistent with greenness becoming a new normal. These results are of interest for many economic agents, including market participants and financial intermediaries, whereby the latter are also called by the regulator to manage their portfolio in consideration of climate risk.