{"id":1176,"date":"2018-03-06T19:19:33","date_gmt":"2018-03-06T18:19:33","guid":{"rendered":"\/silviamuzzioli\/?page_id=1176"},"modified":"2024-09-23T09:36:05","modified_gmt":"2024-09-23T09:36:05","slug":"implied-moments-i-mom","status":"publish","type":"page","link":"https:\/\/morespace.economia.unimore.it\/silviamuzzioli\/implied-moments-i-mom\/","title":{"rendered":"FUNDED RESEARCH PROJECTS"},"content":{"rendered":"

PRIN: PROGETTI DI RICERCA DI RILEVANTE INTERESSE NAZIONALE \u2013 Bando 2022 PNRR Prot. P20225MJW8 “CLIMATE RISK AND STOCK RETURNS”.<\/h2>\n

Green investments remain one of the major challenges for future sustainable and impactful growth of EU countries. Since results about the importance and the sign of climate risk factors and sustainability scores in explaining future stock returns are often mixed, it is crucial to provide investors with a better understanding of the relationship between climate risks and the cross-section of stock returns to encourage conscious investment in environmentally sustainable firms. Despite recent progress, considerable challenges still limit the potential for available ESG information to support long-term value and climate-related international objectives. More specifically, ESG scores are available for a limited number of companies, and ESG data are available at a low computation frequency (on a quarterly or an annual basis). When available, ESG scores provided by different information providers (e.g., Bloomberg, Reuters, S&P Global) differ one from each other, creating confusion on the investor’s side. Moreover, at the level of the individual company, there could be a tendency to disclose only partial information, emphasizing the environmental dimensions on which the firm performs best and neglecting those where the firm does not do as well (greenwashing). To fill these gaps, the project aims to investigate in depth the relationship between climate risk and the cross-section of stock returns, aggregating different sources of information to cope with the green washing problem and making it possible to deal with uncertainty inherent in the data with appropriate econometric techniques.<\/p>\n

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VOLATILITY AND IMPLIED MOMENTS<\/h2>\n

NEW MEASURES AND INDICES OF FINANCIAL CONNECTEDNESS<\/h2>\n

2015-2018<\/h3>\n

funded by FONDAZIONE CRMO and University of Modena and Reggio Emilia<\/p>\n

PRINCIPAL INVESTIGATOR:<\/h3>\n

SILVIA MUZZIOLI \u00a0 \u00a0 \u00a0 institutional web page<\/a>\u00a0 \u00a0cv<\/a><\/p>\n

PARTICIPANTS:<\/h3>\n

BERNARD DE BAETS institutional web page<\/a>
\nANDREA CIPOLLINI\u00a0institutional web page<\/a> cv<\/a>
\nELYAS ELYASIANI\u00a0institutional web page<\/a> cv<\/a>
\nLUCA GAMBARELLI\u00a0institutional web page<\/a> cv<\/a>
\nALBERTO ZAFFARONI\u00a0institutional web page<\/a> cv<\/a><\/p>\n

RESEARCH QUESTIONS:<\/strong><\/h3>\n

1. How to obtain the risk measures (volatility, skewness, and other indices) and how to assess their usefulness:<\/strong><\/h4>\n