Current students

My research proposal is focused on the study of Green Finance in relation to endogenous and exogeneous shocks, which have a relevant aftermath on the financial markets. Two recent examples of shocks that have impacted most financial assets are the Covid-19 pandemic and the political instability that arouse after the outbreak of the war in Ukraine in February 2022. Sustainable finance is a topic that has assumed special relevance over the last two decades, especially in the most developed countries, due to the need of an ecological transition towards lower, generated by human activities on the planet. For instance, the European Union has presented a series of measures through which its member states engage themselves to become climate neutral by 2050: the most impactful is the European Green Deal, whose development started in 2019. In fact, the distinction between green and brown companies has become crucial; in addition, their performance appears to be negatively correlated as the former seem to outperform the latter [4], even during stressful scenarios [1]. In literature, research has been conducted to analyze the spillover effects generated among several assets: as an example, one could consider the spillover effect which exists among commodities’ and stocks’ volatilities, as outlined in [2], [3], [6], and [8]. Indeed, there is a strong link between these two kinds of assets since an increase in the price of the former causes a reduction in the profitability This project aims to analyze the impact that different shocks have caused on the commodities and the companies established in the energy sector, with a particular focus on its quantification in terms of transition risks. Transition risks are business-related risks that follow societal and economic shifts toward a low-carbon and more climate-friendly future. These risks can include policy and regulatory risks, technological risks, market risks, reputational risks, and legal risks.The war in Ukraine may be of particular interest for the research: the macroeconomic scenario would have no precedent in the literature since we have just left behind two years of a pandemic, which has forced the central banks to actuate unconventional accommodative monetary policies, causing high levels of inflation. Furthermore, the European economy may experience a period of stagflation due to the possible recession, should the war in Ukraine continue for a long period of time. In fact, the necessity for Europe to become independent from the Russian commodities, such as oil and gas, has generated two opposite effects. On the one hand, it has helped in understanding the importance of accelerating the use of renewable commodities. On the other hand, however, it has revived the attention towards more polluting and traditional sources of energy, such as coal. Therefore, two main innovative and original contributions should emerge from this work: the first one is the quantification of how much different shocks impact the financial markets, in terms of transition risks; the second one is the measurement of the spillover effect between the stocks’ and the commodities’ returns and volatilities to discover whether the relationship between green and brown companies’ financial performance changes after a shock. In general, quantifying the transition risks is not an easy task due to the following reasons: ;

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• Communications from a large number of companies about their exposure to ESG factors are currently voluntary and may not be fully representative of their involvement;
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• The analyses developed so far are only applicable to some industrial sectors and do not allow to appreciate the differences which exist within the same sector.
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; The transition risks materialize when the introduction of decisive mitigation policies, significant technological innovations or rapid changes in public preferences lead to a quick and different evaluation of financial assets by the markets and financial intermediaries. As a consequence, violent adjustments in the prices of energy products and the demand for securities of the companies most exposed to the change could affect the quality of loans and financial assets on the balance sheets of banks and institutional investors, which may be a valid proxy for the estimation of the transition risks [7].More specifically, the transition risks can be induced by the following: ;

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• Introduction of incentives to reduce emissions, such as the EU Emission Trading Systems (ETS), all the more so if connected with fiscal measures that directly affect certain sectors;
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• Introduction of ad hoc economic policies by governments or by the European Union (e.g., the European Green Deal);
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• Lack of adequate and comparable information about exposure to climate risks by financial institutions, both directly and through the financial assets / liabilities held / issued by them;
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• Increase in credit risks, with particular reference to the sectors and geographic areas most exposed to environmental risks;
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• Request for higher capital requirements in the face of increased credit, market or operational risks;
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• Increases in sovereign risks for those countries in which climate (physical) risks have manifested themselves, or can occur, to a greater extent.
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; With respect to the methodological approach, the analysis of the phenomena will be carried out by means of various econometric techniques. For instance, a generalized vector autoregressive (VAR) framework [3] could be used to evaluate how the volatility and the correlations between commodities, green and brown companies have evolved over time. The analysis may be further extended to portfolio optimization and risk management by applying new Machine Learning techniques among the ones summarized in [5].[1] Alessi L., Ossola E. and Panzica R., The Greenium matters: evidence on the pricing of climate risks, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-76-08729-8, doi:10.2760/403111, JRC116108 [2] Costola, M. and Lorusso, M. (2022). Spillovers among energy commodities and the Russian stock market. Journal of Commodity Markets. 100249, ISSN 2405-8513 [3] Diebold, F. X. and Yilmaz, K. (2012). Better to give than to receive: predictive directional measurement of volatility spillovers. International Journal of Forecasting 28, 57-66 [4] Gil, C. (2022). What can we learn from the financial market about sustainability? Environment Systems and decisions, 42:1-7 [5] Goodell, J. W., Kumar, S., Lim, W. M., and Pattnaik, D. (2021). Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis. Journal of Behavioral and Experimental Finance. [6] Mohamed El Hedi Arouri, Jamel Jouini, Duc Khuong Nguyen, Volatility spillovers between oil prices and stock sector returns: Implications for portfolio management, Journal of International Money and Finance, Volume 30, Issue 7, 2011, Pages 1387-1405 [7] Xingmin, Z., Shuai, Z., and Liping, L. (2022). The banking instability and climate change: Evidence from China. Energy Economics, Volume 106, Issue C [8] Yuan, D., Li, S., Li, R., and Zhang, F. (2022). Economic policy uncertainty, oil and stock markets in BRIC: Evidence from quantiles analysis. Energy Economics. 105972, ISSN 0140-9883