<p>The <i>article</i>&#xa0;introduces an innovative <span>esg</span>-metric quantitative methodology, developed as additive scoring model based on the outcomes of <span>esg</span>-questionnaires. A focused <span>esg</span>-assessment based on <b>E</b>nvironmental, <b>S</b>ocial &amp; <b>G</b>overnance attributes had been developed &amp; thereafter coupled to a robust quantitative framework (topic of the present work). This lead to gain a synthetic scoring measure <i>m</i>, rating <i>R</i>, <span>esg</span>-sustainability probability <i>p</i> and <span>esg</span>-default like risk probability <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="44257_2025_38_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="76" /> </InlineMediaObject> <EquationSource Format="TEX">\(\psi =1-p\)</EquationSource> </InlineEquation>, (therefore a full metric) from the realized answers provided by the company ( answering the questionnaires). Starting from general quantitative assumptions, with an high degree of independence of the questions/business typology investigated, the realized score value is mapped into a normalized probability function <i>p</i>, with <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="44257_2025_38_Article_IEq2.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="68" /> </InlineMediaObject> <EquationSource Format="TEX">\(p\in (0,1)\)</EquationSource> </InlineEquation>, in order to make different questionnaires scales and score methodologies comparable. Main mathematical assumptions underlying the model had been summarized, justified &amp; mathematical details are provided in the final Appendix. The instrument developed had been applied to few questionnaires (4) submitted to potential startups/targets of a Venture Capital, in order to outline first model application with real values. In future an higher number of <span>esg</span>-questionnaires will be studied with the proposed methodology. Introducing an abstract structured framework enables, other the main results here presented, demonstrating theorems like theorem 5, opening operational research opportunities in the field of applied quantitative methods for <span>esg</span>-assessment and even more in general in the theory of quantitative scoring.</p>

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Quantitative ESG scoring model and metric for alternative investments and venture capital targets

  • Francesco Eusepi

摘要

The article introduces an innovative esg-metric quantitative methodology, developed as additive scoring model based on the outcomes of esg-questionnaires. A focused esg-assessment based on Environmental, Social & Governance attributes had been developed & thereafter coupled to a robust quantitative framework (topic of the present work). This lead to gain a synthetic scoring measure m, rating R, esg-sustainability probability p and esg-default like risk probability \(\psi =1-p\) , (therefore a full metric) from the realized answers provided by the company ( answering the questionnaires). Starting from general quantitative assumptions, with an high degree of independence of the questions/business typology investigated, the realized score value is mapped into a normalized probability function p, with \(p\in (0,1)\) , in order to make different questionnaires scales and score methodologies comparable. Main mathematical assumptions underlying the model had been summarized, justified & mathematical details are provided in the final Appendix. The instrument developed had been applied to few questionnaires (4) submitted to potential startups/targets of a Venture Capital, in order to outline first model application with real values. In future an higher number of esg-questionnaires will be studied with the proposed methodology. Introducing an abstract structured framework enables, other the main results here presented, demonstrating theorems like theorem 5, opening operational research opportunities in the field of applied quantitative methods for esg-assessment and even more in general in the theory of quantitative scoring.