Correction: Information flow dynamics between geopolitical risk and major asset returns.

[This corrects the article DOI: 10.1371/journal.pone.0284811.].

Examining the hedge performance of US dollar, VIX, and gold during the coronavirus pandemic: Is US dollar a better hedge asset?

This study utilizes the hedging potential of the U.S. Dollar Index (USDX) during the COVID-19 period, specifically comparing its positive effects on optimal portfolio weights and hedging ratios with those of traditional hedging assets, such as the VIX and gold. The scalar BEKK GARCH model is employed to forecast volatility and calculate hedging indicators. The results show that USDX exhibits strong hedging abilities against S&P 500 index volatility. These findings highlight the advantageous role of the USDX as a hedging instrument, particularly during periods of heightened market uncertainty, such as during the COVID-19 crisis. Despite the increased market volatility during the COVID-19 pandemic, the value of the optimal portfolio weights is stable and the volatility of the weights is significantly reduced, demonstrating the strength of the USDX's low risk and volatility in hedging against market fluctuations. Moreover, the increase in the hedge ratio indicates that more capital is allocated to hedging, reflecting the increased correlation between the USDX and S&P 500 index. These results emphasize the beneficial role of the USDX as a hedging instrument during times of elevated market uncertainty, such as during the COVID-19 crisis. Ultimately, USDX can provide valuable insights for market participants seeking effective hedging strategies.

The dynamic network of industries in US stock market: Evidence of GFC, COVID-19 pandemic and Russia-Ukraine war.

We investigate the topology of sectoral returns in the US stock market using minimum spanning tree (MST) analysis. We examine four distinct time periods: the full period, the Global Financial Crisis (GFC), the COVID-19 pandemic, and the Russia-Ukraine war period. By comparing the static results across these periods, we identify differences in the network structure. Additionally, a rolling window analysis is conducted to explore the time-varying nature of the MST. We employ a TVP-VAR based connectedness framework to ensure a robust analysis of the sectoral return linkages. Our main findings are summarized as follows: First, the structure of the MST varies in different periods, with distinct crisis period structures. During the GFC, the industrial sector dominated clustering, whereas COVID-19 affected the financial, IT, and industrial sectors. The Russia-Ukraine war period showed clustering centered on materials, except in the industrial sector. These varying structures may explain the different characteristics of each crisis. Second, both static and rolling window analyses highlight the significance of the industrial sector in the US stock market. Third, the utilities sector exhibits the lowest centrality measures, indicating its minimal importance and lack of relationships with other industries. These findings provide valuable insights into the interrelationships among industries in the US stock market. Market participants can leverage these findings to enhance their understanding and improve their portfolio management. By utilizing this information, investors can develop optimal diversification strategies to maximize returns and minimize risk.

Dynamic spillovers and portfolio implication between green cryptocurrencies and fossil fuels.

Are green investments decoupled from the dirty investment such as the fossil fuel markets? We address this issue by extending the literature on environmental, social, and governance (ESG) assets by examining the dynamic relationship between fossil fuels and digital ESG assets proxied by green cryptocurrencies using the TVP-VAR(Time-varying parameter vector auto regression) spillover framework. Furthermore, we analyze the hedging attributes of green cryptocurrencies and fossil fuels in a minimum connectedness framework. The main findings are as follows: First, green cryptocurrencies are the main shock transmitters in all asset systems. Second, the dynamic connectedness between green cryptocurrencies and fossil fuels increased during the COVID-19 and Russia-Ukraine conflicts. Third, green cryptocurrencies have shown considerable hedging effectiveness against the fossil fuels. Our study has important implications for investors, regulators, and policy makers, such as shifting to green cryptocurrencies, regulation of carbon footprint, and promoting eco-friendly assets.

Information flow dynamics between geopolitical risk and major asset returns.

We quantify information flows between geopolitical risk (GPR) and global financial assets such as equity, bonds, and commodities, with a focus on the Russian-Ukrainian conflict. We combine transfer entropy and the I-CEEMDAN framework to measure information flows at multi-term scales. Our empirical results indicate that (i) in the short term, crude oil and Russian equity show opposite responses to GPR; (ii) in the medium and long term, GPR information increases the risk in the financial market; and (iii) the efficiency of the financial asset markets can be confirmed on a long-term scale. These findings have important implications for market participants, such as investors, portfolio managers, and policymakers.

Impact of liquidity spillovers among industrial sectors on stock markets during crisis periods: Evidence from the S&P 500 index.

We investigate liquidity spillovers among industry sectors in the S&P 500 index to explain the interconnection dynamics in the US stock market. To do so, we define a sectoral liquidity measure based on the Amihud liquidity measure. Employing the spillover model, we further examine US sectors' liquidity spillovers during the global financial crisis (GFC) and the COVID-19 pandemic. Based on the relationship between liquidity in financial markets and business cycles, our findings show that (i) liquidity connections became stronger during both crises, (ii) in the GFC period, the material sector was the primary transmitter of total liquidity spillovers, whereas in the COVID-19 pandemic period, the consumer discretionary sector was the main conveyor of total liquidity spillovers and the real estate sector was the dominant recipient of total liquidity spillovers, and (iii) net liquidity spillovers between all sectors fluctuated notably during the GFC, while the industrial, consumer staples, and healthcare sectors had the largest net liquidity spillovers during the COVID-19 crisis. These findings have important implications for portfolio managers and policymakers.

A Mellin Transform Approach to the Pricing of Options with Default Risk.

The stochastic elasticity of variance model introduced by Kim et al. (Appl Stoch Models Bus Ind 30(6):753-765, 2014) is a useful model for forecasting extraordinary volatility behavior which would take place in a financial crisis and high volatility of a market could be linked to default risk of option contracts. So, it is natural to study the pricing of options with default risk under the stochastic elasticity of variance. Based on a framework with two separate scales that could minimize the number of necessary parameters for calibration but reflect the essential characteristics of the underlying asset and the firm value of the option writer, we obtain a closed form approximation formula for the option price via double Mellin transform with singular perturbation. Our formula is explicitly expressed as the Black-Scholes formula plus correction terms. The correction terms are given by the simple derivatives of the Black-Scholes solution so that the model calibration can be done very fast and effectively.

Industry volatility and economic uncertainty due to the COVID-19 pandemic: Evidence from wavelet coherence analysis.

This study investigates the impact of economic uncertainty due to the coronavirus (COVID-19) pandemic on the industrial economy in the US in terms of the interdependence and causality relationship. We apply wavelet coherence analysis to economic policy uncertainty (EPU) data and monthly sector volatility of the S&P 500 index from January 2008 to May 2020. The results reveal that EPU in terms of COVID-19 has influenced the sector volatility more than the global financial crisis (GFC) for all sectors. Furthermore, EPU leads the volatility of all sectors during COVID-19 pandemic, while some sector's volatilities lead EPU during the GFC.

Relationship between uncertainty in the oil and stock markets before and after the shale gas revolution: Evidence from the OVX, VIX, and VKOSPI volatility indices.

We investigate the relationship between crude oil prices and stock markets. Unlike prior studies, we use implied volatility indices and evaluate the change in the relationship between the volatility indices through a sub-period analysis. Specifically, we examine the causal relationships among the crude oil, S&P 500 index, and KOSPI 200 index volatilities by using the autoregressive distributed lag (ARDL) bounds and the Toda-Yamamoto Granger causality tests. In addition, a BEKK-GARCH model is employed to enhance the robustness of the causality test results. These experiments indicate that the OVX and VIX show bi-directional causality in the period that includes the shale gas revolution and no causality in the period that does not. Further, the OVX Granger causes the VKOSPI in the former period, but there is no causality between them in the latter period. Finally, we find strong unidirectional causality from the VIX to the VKOSPI in both sub-periods. These results have important implications for the analysis of portfolio risk management and for assisting energy policymakers and traders in making effective decisions and investments, respectively.

Purification and Nitrogen Doping of Nanothin Exfoliated Graphite Through RF Thermal Plasma Treatment.

A mixture of nanothin exfoliated (NTE) graphite and urea (CO(NH2)2) powder was treated with radio frequency (RF) thermal plasma to achieve in situ purification and nitrogen doping of NTE graphite using the high-temperature flame of the RF plasma. Reactive species such as NH3, NH2, and HCNO generated by the thermolysis of urea play an important role in the purification and nitrogen doping of NTE graphite. The nitrogen content of NTE graphite subjected to plasma treatment increased by 5 times compared with that of raw NTE graphite. Three types of nitrogen species, namely, quaternary N, pyridinic N, and pyrrolic N, were observed after N doping with plasma treatment. The sheet resistance of N-doped NTE graphite reduced to 12-21% compared to that of the untreated NTE graphite, with the corresponding resistivity being ~7 × 10-6 Ω m.

Troponin I and D-Dimer for Discriminating Acute Pulmonary Thromboembolism from Myocardial Infarction.

BACKGROUND: Acute pulmonary thromboembolism (APTE) is a life-threatening condition, often manifesting with chest pain, dyspnea, and increased cardiac biomarkers including cardiac troponin I (CTI) and D-dimer. Therefore, APTE is often misdiagnosed with classical non-ST elevation myocardial infarction (NSTEMI), resulting in unnecessary coronary interventions and a delay of therapy. OBJECTIVES: Our aim was to distinguish APTE from NSTEMI based on CTI and D-dimer levels. METHODS: Complete clinical and laboratory data sets from APTE patients (n = 123) were compared with matched NSTEMI patients (n = 123) who presented with chest pain. The APTE diagnosis was confirmed by chest tomography, angiography, or radionuclide ventilation-perfusion scan, while NSTEMI was established by clinical symptoms, cardiac biomarkers, and coronary angiography. Clinical characteristics, CTI (initial and peak), and D-dimer levels at presentation were retrospectively analyzed. RESULTS: The clinical characteristics were not different between APTE and NSTEMI patients. However, significantly lower initial CTI (0.2 ± 0.5 vs. 4.4 ± 9.5 ng/ml) and peak CTI (0.7 ± 2.7 vs. 17.1 ± 20.4 ng/ml), but higher initial D-dimer (9.8 ± 9.4 vs. 1.6 ± 3.6 ng/ml), distinguished APTE from NSTEMI. By receiver operating characteristic curve analysis, the cutoff values for initial CTI, peak CTI, and D-dimer were 0.25, 0.98, and 3.18 ng/ml, respectively. CONCLUSION: Patients with APTE exhibited lower initial and peak CTI but higher D-dimer levels than NSTEMI patients. Assessing cardiac biomarkers is useful for differentiating APTE from NSTEMI. Further large randomized biomarker studies are urgently needed to facilitate a better APTE diagnosis since clinical characteristics are not particularly helpful.

Role of Cu in Mo6S8 and Cu mixture cathodes for magnesium ion batteries.

The reversible capacity of Chevrel Mo6S8 cathode can be increased by the simple addition of the Cu metal to Mo6S8 electrodes. However, the exact reaction mechanism of the additional reversible capacity for the Mo6S8 and Cu mixture cathode has not been clearly understood yet. To clarify this unusual behavior, we synthesize a novel Cu nanoparticle/graphene composite for the preparation of the mixture electrode. We thoroughly investigate the electrochemical behaviors of the Mo6S8 and Cu mixture cathode with the relevant structural verifications during Mg(2+) insertion and extraction. The in situ formation of Cu(x)Mo6S8 is observed, indicating the spontaneous electrochemical insertion of Cu to the Mo6S8 host from the Cu nanoparticle/graphene composite. The reversible electrochemical replacement reaction of Cu in the Mo6S8 structure is clarified with the direct evidence for the solid state Cu deposition/dissolution at the surface of Mo6S8 particles. Moreover, the Mo6S8 and Cu mixture cathode improves the rate capability compared to the pristine. We believe that our finding will contribute to understanding the origin of the additional capacity of the Mo6S8 cathode arising from Cu addition and improve the electrochemical performance of the Mo6S8 cathode for rechargeable Mg batteries.

Radio Frequency-Thermal Plasma Synthesis of Metal Nano-Thin Exfoliated Graphite Hybrid.

Nano-metal with nano-thin exfoliated (NTE) graphite hybrid material has been synthesized by radio frequency (RF) thermal plasma. A micro-sized nickel powder and the NTE graphite powder were fed into the RF plasma and nano sized nickel particles attached to the surface of the NTE graphite were found. In the high temperature of RF thermal plasma that is of higher than 10,000 K, the NTE graphite was not vaporized or damaged, while the metal powder was vaporized. The size of nickel nanoparticles on the NTE graphite was 40 80 nme. The size and number density of produced metal nanoparticle can be controlled by the process pressure in a reactor, the feeding ratio of raw materials, and the flow rate of working gas. X-ray diffraction results of the produced hybrid nano material indicate that there was a bonding between the nano metal and the NTE graphite. The inert nature of surface of the NTE graphite has been a barrier for the NTE graphite to be used a compounding additive. The nano metal covered NTE graphite will open up many potential applications of NTE graphite and polymer compound materials.