The network of commodity risk

In this paper, we investigate the interconnections among and within the Energy, Agricultural, and Metal commodities, operating in a risk management framework with a twofold goal. First, we estimate the Value-at-Risk (VaR) employing GARCH and Markov-switching GARCH models with different error term distributions. The use of such models allows us to take into account well-known stylized facts shown in the time series of commodities as well as possible regime changes in their conditional variance dynamics. We rely on backtesting procedures to select the best model for each commodity. Second, we estimate the sparse Gaussian Graphical model of commodities exploiting the Graphical LASSO (GLASSO) methodology to detect the most relevant conditional dependence structure among and within the sectors. A novel feature of our framework is that GLASSO estimation is achieved exploring the precision matrix of the multivariate Gaussian distribution obtained using a Gaussian copula with marginals given by the residuals of the aforementioned selected models. We apply our approach to the sample of twenty-four series of commodity futures prices over the years 2005–2022. We find that Soybean Oil, Cotton, and Coffee represent the major sources of propagation of financial distress in commodity markets while Gold, Natural Gas UK, and Heating Oil are depicted as safe-haven commodities. The impact of Covid-19 is reflected in increased heterogeneity, as captured by the strongest relationships between commodities belonging to the same commodity sector and by weakened inter-sectorial connections. This finding suggests that connectedness does not always increase in response to crisis events.

Nonthyroidal illness syndrome (NTIS) in severe COVID-19 patients: role of T3 on the Na/K pump gene expression and on hydroelectrolytic equilibrium.

BACKGROUND: Nonthyroidal Illness Syndrome (NTIS) can be detected in many critical illnesses. Recently, we demonstrated that this condition is frequently observed in COVID-19 patients too and it is correlated with the severity the disease. However, the exact mechanism through which thyroid hormones influence the course of COVID-19, as well as that of many other critical illnesses, is not clear yet and treatment with T4, T3 or a combination of both is still controversial. Aim of this study was to analyze body composition in COVID-19 patients in search of possible correlation with the thyroid function. METHODS AND FINDINGS: We report here our experience performed in 74 critically ill COVID-19 patients hospitalized in the intensive care unit (ICU) of our University Hospital in Rome. In these patients, we evaluated the thyroid hormone function and body composition by Bioelectrical Impedance Analysis (BIA) during the acute phase of the disease at admission in the ICU. To examine the effects of thyroid function on BIA parameters we analyzed also 96 outpatients, affected by thyroid diseases in different functional conditions. We demonstrated that COVID-19 patients with low FT3 serum values exhibited increased values of the Total Body Water/Free Fat Mass (TBW/FFM) ratio. Patients with the lowest FT3 serum values had also the highest level of TBW/FFM ratio. This ratio is an indicator of the fraction of FFM as water and represents one of the best-known body-composition constants in mammals. We found an inverse correlation between FT3 serum values and this constant. Reduced FT3 serum values in COVID-19 patients were correlated with the increase in the total body water (TBW), the extracellular water (ECW) and the sodium/potassium exchangeable ratio (Nae:Ke), and with the reduction of the intracellular water (ICW). No specific correlation was observed in thyroid patients at different functional conditions between any BIA parameters and FT3 serum values, except for the patient with myxedema, that showed a picture similar to that seen in COVID-19 patients with NTIS. Since the Na+/K+ pump is a well-known T3 target, we measured the mRNA expression levels of the two genes coding for the two major isoforms of this pump. We demonstrated that COVID-19 patients with NTIS had lower levels of mRNA of both genes in the peripheral blood mononuclear cells (PBMC)s obtained from our patients during the acute phase of the disease. In addition, we retrieved data from transcriptome analysis, performed on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM)s treated with T3 and we demonstrated that in these cells T3 is able to stimulate the expression of these two genes in a dose-dependent manner. CONCLUSIONS: In conclusion, we demonstrated that measurement of BIA parameters is a useful method to analyze water and salt retention in COVID-19 patients hospitalized in ICU and, in particular, in those that develop NTIS. Our results indicate that NTIS has peculiar similarities with myxedema seen in severe hypothyroid patients, albeit it occurs more rapidly. The Na+/K+ pump is a possible target of T3 action, involved in the pathogenesis of the anasarcatic condition observed in our COVID-19 patients with NTIS. Finally, measurement of BIA parameters may represent good endpoints to evaluate the benefit of future clinical interventional trials, based on the administration of T3 in patients with NTIS.

Option Pricing, Zero Lower Bound, and COVID-19

This paper provides a quantitative assessment of equity options priced at the Zero Lower Bound, i.e., when interest rates are set essentially to zero. We obtain closed form formulas for American options when the Zero Lower Bound policy holds. We perform numerical implementation of American put options written on the stock Federal National Mortgage Association (FNMA) and of related bounds for the optimal exercise. The results show similarities with the corresponding European options priced at the Zero Lower Bound during the COVID-19 crisis.

Multivariate Analysis of Energy Commodities during the COVID-19 Pandemic: Evidence from a Mixed-Frequency Approach

This paper shows the effects of the COVID-19 pandemic on energy markets. We estimate daily volatilities and correlations among energy commodities relying on a mixed-frequency approach that exploits information from the number of weekly deaths related to COVID-19 in the United States. The mixed-frequency approach takes advantage of the MIxing-Data Sampling (MIDAS) methods. We compare our results to those obtained by employing two well-known models that do not account for the COVID-19 low-frequency variable, namely the Dynamic EquiCorrelation (DECO) and corrected Dynamic Conditional Correlation (cDCC). Moreover, we consider four possible specifications of the volatility: GARCH, GJR, GARCH-MIDAS, and Double-Asymmetric GARCH-MIDAS. The empirical results show that our approach is statistically superior to other models and represents a valuable methodology that can be used for risk managers, investors, and policy makers to assess the effects of the pandemic on spillovers effects in energy markets.

COVID-19 After Lung Resection in Northern Italy.

We reviewed surgical cases from 4 Thoracic Surgery departments in the Lombardia region of Italy, the area mostly affected by Coronavirus pandemic in Europe, with the aim to describe the impact of COVID-19 on the treatment of thoracic surgical patients. Clinical, radiological and laboratory data from patients who underwent lung resection from December 2019 to March 2020 were retrospectively collected until June 2020. Univariable Cox regression models were estimated to evaluate potential prognostic factors for developing COVID-19 and to investigate postoperative mortality among patients who developed symptomatic COVID-19 infection. We examined data from 107 patients. (74 lobectomies, 32 wedge/segmentectomies and 1 pneumonectomy). Twelve patients developed COVID-19 (Group 1), whereas 95 patients were not infected (Group 2). In Group 1, 6 patients (50%) died from complications related to infection; in Group 2, one patient (1%) died because of non-COVID-19-related causes. Median days from surgery to first symptoms, CT confirmation, clinical confirmation and PCR positivity was 48.1, 54.3, 55.1, and 55.2 respectively. At univariable analysis, DLCO/VA% (P = 0.008), duration of the surgery (P = 0.009), smoking history (pack/year) (P < 0.001), BMI (P< 0.001) and number of segments resected (P = 0.010) were associated with COVID-19 onset. Moreover, CCI (P < 0.001), DLCO/VA% (P = 0.002), cigarette pack/year (P < 0.001), BMI (P < 0.001) and COVID-19 (P < 0.001) were associated with death. Patients who undergo lung resection and then develop symptomatic COVID-19 infection are at higher risk of developing severe respiratory complications and postoperative death. Insidious symptoms' onset may lead to a delay in diagnosis. We suggest two mitigating strategies: (1) Improve symptoms surveillance and isolation during recovery period, (2) Be aware of a potential greater risk of developing symptomatic COVID-19 and death correlated with elevated CCI, BMI, smoking history, DLCO/VA%, number of resected segments and duration of surgery.