Optimal risk management considering environmental and climatic changes.

Climate change presents challenges to policy and economic stability, necessitating effective trading strategies to reduce environmental risks. This article addresses gaps in existing studies by using a Markov-switching model to consider climate risk. Backward stochastic differential equations are used to optimize utility with three hedging strategies based on the concept of risk aversion. Numerical scenarios confirm the model's superiority in incorporating exogenous events, with our risk-averse strategy outperforming classical approaches. Our strategy outperforms classical strategies by taking a flexible risk trading when investors face risk-averse behavior due to climate risk events. The findings presented in this article have important implications for the development of more resilient investment portfolios and can contribute to climate policy.

Shift contagion and minimum causal intensity portfolio during the COVID-19 and the ongoing Russia-Ukraine conflict.

Using the TYDL causality test, this paper attempts (i) to investigate the existence of shift contagion among a large spectrum of financial markets during recent stress and stress-free periods and (ii) to propose a new approach of portfolio management based on the minimization of the causal intensity. During the COVID-19 crisis period, the shift contagion analysis not only reveal a tripling of the causal links between the markets studied, but also a change in the causal structure. Beyond the initial impact of the COVID-19 crisis on financial markets, policy interventions seem to have helped in reassuring market participants that the further spread of financial stress would be mitigated. However, the Russian-Ukrainian conflict, and the high degree of uncertainty it entailed, has again exacerbated the interdependencies between financial markets. In terms of portfolio analysis, our minimum-causal-intensity approach records a lower (respectively higher) reward-to-volatility ratio than the Markowitz (1952 & 1959) minimum-variance traditional approach during the pre-COVID-19 (respectively pre-war) period. On the other hand, both approaches, the one we propose in this paper and the minimum-variance approach, record negative reward-to-volatility ratios during crisis periods.

A fair and progressive carbon price for a sustainable economy.

The principle of "common but differentiated responsibility", as a key concept of the United Nations Framework Convention on Climate Change (UNFCCC), acknowledges the conditions for a generally acceptable and differentiated pricing mechanism on carbon emissions. With reference to this principle, carbon price determination has become a necessary instrument for sustainable policies. Considering the development gaps and the historical responsibility of the OECD's countries, a single carbon price would raise a major issue of equity between "developed" and "developing" countries. Although from a climate perspective each molecule of CO2 produces the same level of damage despite the nature or the location of the activity generating the emissions, all CO2 emissions are not on an equal footing. Indeed, some are necessary to improve the lives of people in "developing" countries when others can be considered not indispensable, especially beyond a certain level of development. In this policy paper, we explain how the price of carbon should be fixed according to a reference price depending on the Human Development Index (HDI) and CO2 emissions per capita. The HDI criterion enables to integrate progressivity into taxation while distinguishing what is essential from what is not. By taking a reference price based on the HDI, countries with low HDIs should pay a lower carbon price. However, with same HDI levels, countries with higher CO2 emissions should pay a penalty on the reference price. Our policy paper analyses the benefits of a differentiated and progressive carbon pricing mechanism to facilitate intergovernmental cooperation for a more sustainable economy.

Meteorological factors against COVID-19 and the role of human mobility.

In the vein of recent empirical literature, we reassessed the impact of weather factors on Covid-19 daily cases and fatalities in a panel of 37 OECD countries between 1st January and 27th July 2020. We considered five different meteorological factors. For the first time, we used a dynamic panel model and considered two different kinds of channels between climate and Covid-19 virus: direct/physical factors related to the survival and durability dynamics of the virus on surfaces and outdoors and indirect/social factors through human behaviour and individual mobility, such as walking or driving outdoors, to capture the impact of weather on social distancing and, thus, on Covid-19 cases and fatalities. Our work revealed that temperature, humidity and solar radiation, which has been clearly under considered in previous studies, significantly reduce the number of Covid-19 cases and fatalities. Indirect effects through human behaviour, i.e., correlations between temperature (or solar radiation) and human mobility, were significantly positive and should be considered to correctly assess the effects of climatic factors. Increasing temperature, humidity or solar radiation effects were positively correlated with increasing mobility effects on Covid-19 cases and fatalities. The net effect from weather on the Covid-19 outbreak will, thus, be the result of the physical/direct negative effect of temperature or solar radiation and the mobility/indirect positive effect due to the interaction between human mobility and those meterological variables. Reducing direct effects of temperature and solar radiation on Covid-19 cases and fatalities, when they were significant, were partly and slightly compensated for positive indirect effects through human mobility. Suitable control policies should be implemented to control mobility and social distancing even when the weather is favourable to reduce the spread of the Covid-19 virus.

Co-movement of COVID-19 and Bitcoin: Evidence from wavelet coherence analysis.

We apply wavelet methods to daily data of COVID-19 world deaths and daily Bitcoin prices from 31th December 2019 to 29th April 2020. We find, especially for the period post April 5, that levels of COVID-19 caused a rise in Bitcoin prices. We contribute to the fast-growing body of work on the financial impacts of COVID-19, as well as to ongoing consideration of whether Bitcoin is a safe haven investment. Our results should be of great interest to both scholars and policy makers, as well as investment professionals interested in the financial implications of both COVID-19 and cryptocurrencies.

The role of economic structural factors in determining pandemic mortality rates: Evidence from the COVID-19 outbreak in France.

Among the majority of research on individual factors leading to coronavirus mortality, age has been identified as a dominant factor. Health and other individual factors including gender, comorbidity, ethnicity and obesity have also been identified by other studies. In contrast, we examine the role of economic structural factors on COVID-19 mortality rates. Particularly, focusing on a densely populated region of France, we document evidence that higher economic "precariousness indicators" such as unemployment and poverty rates, lack of formal education and housing are important factors in determining COVID-19 mortality rates. Our study will help inform policy makers regarding the role of economic factors in managing pandemics.