Default risk transmission in the travel and leisure industry

Default risk in the Travel and Leisure (T&L) industry remains understudied despite its implications for the industry's health and stability. This paper investigates the transmission of default risk among US T&L firms over various credit horizons from July 22, 2008 to December 9, 2022, paying special attention to the impact of COVID-19. The short-, medium-, and long-term default risk factors are extracted from the Credit Default Spread (CDS) curve of the US T&L industry then used within a connectedness approach. The results reveal considerable default risk transmission, particularly in the long-term. Default risk transmission has spiked across all horizons since the pandemic, reflecting the deterioration in credit quality of T&L firms under the pandemic. Analysis of the drivers of default risk transmission shows that several macro-financial variables, especially news market sentiment and stock market volatility induced by the pandemic, have an important explanatory role.

Is credit default swap spread a leading indicator of bank default risk? Evidence of Indian banks during the COVID-19 pandemic

The paper investigates whether credit default swaps (CDSs) spread of Indian banks is a leading indicator for bank default risk. The paper uses Merton-type models to estimate theoretical CDS spread of the sample of Indian banks and then compares it to their balance sheet ratios. Though theoretically, higher CDS spreads indicate higher default risk, the paper finds that in times of shocks, like the present COVID-19 crisis, it becomes difficult to isolate the spread movements due to true default risk versus those based on panic and speculation. The paper then correlates equity premiums and CDS premiums and finds negative correlation. The equity market returns lead the CDS market returns in capturing default risk. As default risk is priced better in equity markets, it is preferable for institutional investors to trade default risk of Indian banks in the stock markets rather than the CDS markets.

Sovereign default network and currency risk premia.

We construct a sovereign default network by employing high-dimensional vector autoregressions obtained by analyzing connectedness in sovereign credit default swap markets. We develop four measures of centrality, namely, degree, betweenness, closeness, and eigenvector centralities, to detect whether network properties drive the currency risk premia. We observe that closeness and betweenness centralities can negatively drive currency excess returns but do not exhibit a relationship with forward spread. Thus, our developed network centralities are independent of an unconditional carry trade risk factor. Based on our findings, we develop a trading strategy by taking a long position on peripheral countries' currencies and a short position on core countries' currencies. The aforementioned strategy generates a higher Sharpe ratio than the currency momentum strategy. Our proposed strategy is robust to foreign exchange regimes and the coronavirus disease 2019 pandemic.

Recent Development of Supramolecular Cancer Theranostics Based on Cyclodextrins: A Review.

With the development of personalized medical demands for precise diagnosis, rational management and effective cancer treatment, supramolecular theranostic systems have received widespread attention due to their reversibly switchable structures, sensitive response to biological stimuli and integration ability for multiple capabilities in a single platform with a programmable fashion. Cyclodextrins (CDs), benefiting from their excellent characteristics, such as non-toxicity, easy modification, unique host-guest properties, good biocompatibility, etc., as building blocks, serve as an all-purpose strategy for the fabrication of a supramolecular cancer theranostics nanodevice that is capable of biosafety, controllability, functionality and programmability. This review focuses on the supramolecular systems of CD-bioimaging probes, CD-drugs, CD-genes, CD-proteins, CD-photosensitizers and CD-photothermal agents as well as multicomponent cooperation systems with regards to building a nanodevice with functions of diagnosis and (or) therapeutics of cancer treatment. By introducing several state-of-the-art examples, emphasis will be placed on the design of various functional modules, the supramolecular interaction strategies under the fantastic topological structures and the hidden "bridge" between their structures and therapeutic efficacy, aiming for further comprehension of the important role of a cyclodextrin-based nanoplatform in advancing supramolecular cancer theranostics.

A photoelectrochemical immunosensor based on magnetic all-solid-state Z-scheme heterojunction for SARS-CoV-2 nucleocapsid protein detection.

Rapid, convenient and accurate detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is urgently needed to timely diagnosis of coronavirus pandemic (COVID-19) and control of the epidemic. In this study, a signal-off photoelectrochemical (PEC) immunosensor was constructed for SARS-CoV-2 nucleocapsid (N) protein detection based on a magnetic all-solid-state Z-scheme heterojunction (Fe3O4@SiO2@TiO2@CdS/Au, FSTCA). Integrating the advantages of magnetic materials and all-solid-state Z-scheme heterostructures, FSTCA was implemented to ligate the capture antibody to form magnetic capture probe (FSTCA/Ab1). It can simplify the separation and washing process to improve reproducibility and stability, while allowing immune recognition to be performed in the liquid phase instead of the traditional solid-liquid interface to improve anti-interference. Besides, the heterojunction inhibited the recombination of photogenerated electron/hole (e-/h+) and promoted the light absorption to provide superior photoelectric substrate signal. The mechanism of photogenerated e-/h+ transfer of FSTCA were investigated by the electron spin resonance (ESR) spectroscopy. SiO2 spheres loaded with Au NPs utilized as an efficient signal quencher. The steric hindrance effect of SiO2@Au labeled detection antibodies (SiO2@Au-Ab2) conjugates significantly diminished light absorption and hindered the transfer of photogenerated electrons, further amplifying the signal change value. Based on the above merits, the elaborated immunosensor had a wide linear range of 10 pg mL-1-100 ng mL-1 and a low detection limit down to 2.9 pg mL-1 (S/N = 3). The fabricated PEC immunosensor demonstrated strong anti-interference, easy operation, and high sensitivity, showing enormous potential in clinical diagnosis of SARS-CoV-2.

COVID-19 Pandemic and Global Corporate CDS Spreads.

We examine the impact of the COVID-19 pandemic on the credit risk of companies around the world. We find that increased infection rates affect firms more adversely as reflected by the wider increase in their credit default swap (CDS) spreads if they are larger, more leveraged, closer to default, have poorer governance and more limited stakeholder engagement, and operate in more highly exposed industries. We observe that country-level determinants like GDP, political stability, foreign direct investment, and commitment to crisis management (income support, health and lockdown policies) also affect the sensitivity of CDS spreads to COVID-19 infection rates. A negative amplification effect exists for firms with high default probability in countries with fiscal constraints. A direct comparison between global CDS and stock markets reveals that the CDS market prices in a distinct set of corporate traits and government policies in pandemic times.

THE ASYMMETRIC LINKAGES BETWEEN SOVEREIGN CDS SPREADS AND STOCK MARKET INDICES IN THE PERIOD COVERING THE COVID-19 PANDEMIC: EVIDENCE FROM THE BRIC COUNTRIES

This paper analyses the asymmetric linkages between the credit default swap (CDS) spreads and stock market indices for the BRIC countries which include Brazil, Russia, India, and China for the period of 2013:12-2021:03. We use the data of Bovespa, Moex, Shanghai, and Sensex stock market indices and CDS spreads obtained from the Bloomberg terminal. In our analysis, we employ the Hatemi-J (2012) asymmetric causality test which considers positive and negative shocks might have different causal effects between variables. Our findings support the evidence of causality relationships between CDS spreads and stock market indices for the BRIC countries in the relevant period suggesting that the CDS spreads can be used for anticipating the movements in stock market indices. Furthermore, we obtain meaningful results for particularly Russia and Brazil. Accordingly, we notice that the increases in CDS spreads lead to negative changes in stock market indices for Russia, and decreases in CDS spreads lead to positive changes in stock market indices for Brazil. © 2022, Symmetrion. All rights reserved.

Credit default swap pricing with counterparty risk in a reduced form model with a common jump process

In this paper, we study the credit default swap (CDS) pricing with counterparty risk in a reduced form model. The default jump intensities of the reference firm and counterparty are both assumed to follow the mean-reverting CIR processes with independent jumps respectively and a common jump. The approximate closed-form solutions of the joint survival probability density and the probability density of the first default can be obtained by using the PDE method. Then with the expressions of the probability densities, we can get the formula for the CDS price with counterparty risk in a reduced form model with a common jump. In the numerical analysis part, we find that the default of the reference asset has a greater impact on the CDS price than that of the default of counterparty after introducing the common jump process.

From fears to recession? Time‐frequency risk contagion among stock and credit default swap markets during the COVID pandemic

This study uses a high-dimensional time-frequency volatility spillover model to examine risk interactions across 32 global stock and credit default swap (CDS) markets during the coronavirus (COVID-19) pandemic. Our empirical results mainly show that cross-market risk spillovers between these two types of markets are rare over the whole crisis period. Adding CDS assets to the stock portfolio would significantly decrease the overall risk spillovers in the mixed portfolio. Then, the time-frequency spillover and rolling window analyses confirm this finding and provide further evidence of frequency heterogeneity of risk spillovers during the pandemic. The outbreak of the COVID pandemic only sharply increases short-term risk spillovers between the stock and sovereign CDS market but exerts insignificant impacts on the medium and long-term cross-market risk spillovers. Moreover, our results show that developed countries are net transmitters in the stock markets. In contrast, the emerging markets account for the most risk spillovers in sovereign CDS markets over the sample period, emphasizing the heterogenous adverse impacts of the pandemic across various countries and markets. Finally, we find that bailouts implemented by the US and EU central banks, though with heterogeneous impacts across frequencies, gradually enhance the confidence and resilience of investors in these markets.

Network Topology of Dynamic Credit Default Swap Curves of Energy Firms and the Role of Oil Shocks

Using network analysis on the connectedness of default factors in a credit default swap (CDS) dataset of U.S. and European energy firms, we provide the first evidence of differences in the shape and dynamics of the interconnectedness of the level, slope, and curvature, representing long-, short-and middle-term default factors, respectively. The interconnectedness of the three default factors increases during the European sovereign debt crisis (ESDC), whereas only the interconnect-edness of the level factor increases during the oil price crash, and the interconnect-edness of both level and slope factors spikes during COVID19. European firms contribute more to the transmission of long-term and short-term default risk from early 2011 till the beginning of the 2014–2105 oil price crash;afterwards, U.S. firms are major default transmitters despite some periods of parity with European firms. The impacts of oil demand and supply shocks on the various interconnect-edness are quantile-dependent and more pronounced in the long term for the credit risk of the energy firms. © 2022 by the IAEE. All rights reserved.

Covid-19, sovereign risk and monetary policy: Evidence from the European Monetary Union

This paper investigates the impact of Covid-19 pandemic and monetary policy measures adopted by the European Central Bank (ECB) on the sovereign risk for the European Monetary Union (EMU) countries for the period between March-2020 and November-2020 using daily data. The impact of Covid-19 and monetary policy shocks on the credit default swap rates and bond yields are investigated relying on a fixed effects panel regression model for five core (Germany, France, Austria, Netherlands, Belgium) and three periphery (Italy, Portugal and Spain) countries. To investigate the cross-country differences in the responses, the interactions of the independent variables with periphery dummy and other country-specific variables are included in the regressions. The results of the empirical analysis suggest that Covid-19 shock increased the sovereign risk in the periphery EMU countries significantly and monetary policy measures have been effective in easing financial conditions in these countries. The results are insignificant for the core countries. The results also show that financial stability alleviates the negative impact of Covid-19 on the sovereign risk.

Credit risk interdependence in global financial markets: Evidence from three regions using multiple and partial wavelet approaches

Credit risk linkage has primarily been examined from the lens of developed country markets and using volatility index. In this paper, we investigate the interconnectedness and causality among the global financial market risks during crisis periods, using partial and multiple wavelet coherence analysis. Specifically, we employ financial sector credit default swap indices from three regions (Asia, North America, and Europe) from January 2008 to June 2021 as a proxy for risk in the financial industry. The sample period includes three global crises, namely the 2008 global financial crisis, the European debt crisis, and the current coronavirus disease of 2019 pandemic. Our findings can be summarized as follows. First, credit risks in global financial markets are highly connected across the three regions. However, if the impact of a particular region is not considered, the other two regions become less connected in terms of credit risk. Second, considerable interactions among the credit risk of financial industries in the three regions occur during crisis periods. Third, significant relationships between credit risks in Asia and North America ensue in the long-term, which is independent of the European region. Our findings provide significant implications for financial market participants, as the credit risk transmission can directly affect not only financial market stability but also portfolio risk exposure.

Elucidating the neuropathophysiology of COVID-19 using quantum dot biomimetics of SARS-CoV-2

Quantum dots were encapsulated in polymeric phospholipid micelles conjugated to multiple ligands of SARS-CoV-2 spike protein to form fluorescent biomimetic nanoparticles for SARS-CoV-2 (COVID-QDs). Phosphatidylethanolaminepolyethylene glycol (PE:PEG) was appended with bis(4-methylphenyl)sulfone to form PE:PEG:bis-sulfone and self-assembled into micelles around CdSe/CdS core/shell quantum dots via thin-film rehydration. The introduction of the bis-sulfone group the surface of the micelle-encapsulated quantum dots provides multiple sites for conjugation to his-tagged SARS-CoV-2 spike protein via a bisalkylation mechanism. Based on the eluted unconjugated fraction, we estimate that an average of seven spike proteins are conjugated per COVID-QD. We treated an in-vitro model system for the neurovascular unit (NVU) with these COVID-QD constructs to investigate the COVID-QDs, and by proxy SARS-CoV-2, may modulate the NVU leading to the COVID-19 associated neuropathophysiology. © 2022 SPIE

Methylene Blue functionalized carbon nanodots combined with different shape gold nanostructures for sensitive and selective SARS-CoV-2 sensing.

The development of DNA-sensing platforms based on new synthetized Methylene Blue functionalized carbon nanodots combined with different shape gold nanostructures (AuNs), as a new pathway to develop a selective and sensitive methodology for SARS-CoV-2 detection is presented. A mixture of gold nanoparticles and gold nanotriangles have been synthetized to modify disposable electrodes that act as an enhanced nanostructured electrochemical surface for DNA probe immobilization. On the other hand, modified carbon nanodots prepared a la carte to contain Methylene Blue (MB-CDs) are used as electrochemical indicators of the hybridization event. These MB-CDs, due to their structure, are able to interact differently with double and single-stranded DNA molecules. Based on this strategy, target sequences of the SARS-CoV-2 virus have been detected in a straightforward way and rapidly with a detection limit of 2.00 aM. Moreover, this platform allows the detection of the SARS-CoV-2 sequence in the presence of other viruses, and also a single nucleotide polymorphism (SNPs). The developed approach has been tested directly on RNA obtained from nasopharyngeal samples from COVID-19 patients, avoiding any amplification process. The results agree well with those obtained by RT-qPCR or reverse transcription quantitative polymerase chain reaction technique.

Ambivalent Change in CDS Spreads in 11 Euro Area Countries

One of the macroeconomic consequences of the COVID-19 epidemic is that the global economy has seen a robust increase in the countries` gross external debt and the sovereign public debt that is part of it. Nor have the eurozone Member States escaped this effect. The increase in gross external debt and sovereign government debt also means that it has become theoretically more risky for investors to buy debt securities (typically bonds). Theoretically, however, it follows that as a result of the increase in risks in the country, CDS spreads had to rise as well. The study uses a correlation calculation to show that the development of the price of CDSs is more closely correlated with gross government debt than with gross external debt. Using hierarchical cluster analysis, the study groups the countries of the Eurozone. The basis for clustering is the close relationship between a countrys gross government debt and its CDS spread over the period under review A relevant conclusion of the study is that the increase in gross government debt was not followed by an increase in CDS spreads because the financial source of the increase in government debt was different from previous years.

Prospects of NIR fluorescent nanosensors for green detection of SARS-CoV-2.

The pandemic of the novel coronavirus disease 2019 (COVID-19) is continuously causing hazards for the world. Effective detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can relieve the impact, but various toxic chemicals are also released into the environment. Fluorescence sensors offer a facile analytical strategy. During fluorescence sensing, biological samples such as tissues and body fluids have autofluorescence, giving false-positive/negative results because of the interferences. Fluorescence near-infrared (NIR) nanosensors can be designed from low-toxic materials with insignificant background signals. Although this research is still in its infancy, further developments in this field have the potential for sustainable detection of SARS-CoV-2. Herein, we summarize the reported NIR fluorescent nanosensors with the potential to detect SARS-CoV-2. The green synthesis of NIR fluorescent nanomaterials, environmentally compatible sensing strategies, and possible methods to reduce the testing frequencies are discussed. Further optimization strategies for developing NIR fluorescent nanosensors to facilitate greener diagnostics of SARS-CoV-2 for pandemic control are proposed.

Credit default swap market retrospective: observations from the 2008-9 financial crisis and the onset of the Covid-19 pandemic

Global credit default swap (CDS) markets experienced unprecedented whipsaw spread realizations during March and April 2020. While the main source of market uncertainty was the Covid-19 pandemic, the March 2020 oil price war between Saudi Arabia and Russia added "fuel to the fire". In this paper credit market fluctuations, measured by the levels of the main and most heavily traded index instruments, are analyzed and compared with the analogous index realizations during the 2008-9 financial crisis. The Covid-19 credit market fluctuations exceeded those during the financial crisis in terms of daily amplitudes and the rates at which spread tightening followed the initial spread widening. The fast-moving credit markets led to record index trading and clearing activity at all three major CDS clearinghouses. Clearinghouse volumes and general clearing trends during the onset of the Covid-19 pandemic are presented in the context of the observed explosion in market volatility. The continuous development and investment in central clearing over the last 10 years greatly contributed to the financial stability of the CDS markets during the Covid-19 crisis, providing increased market transparency, capital efficiency and robust risk management services in the presence of record daily volumes, open interest levels and mark-to-market payments.

Building Toward More Just Data Practices

Introduction: This tutorial offers technical and professional communication (TPC) professionals a heuristic designed to support more just data practices. Key concepts: Understanding how data contribute to discussions of public problems matters, especially in times of crisis during which multiply marginalized communities are disproportionately affected. Critical Data Studies clarifies how data practice and priorities emerging from various domains of power exacerbate structural inequalities. If we recognize, reveal, and reject data practices that cast data as if they were neutral or fixed, we can ensure that our data practices as TPC professionals are more just. Key lessons: 1. Recognize that data are socially constructed and often incomplete. 2. Reveal the overarching social, political, cultural, and economic conditions that shape data collection and by extension, data itself. 3. Reject faulty or biased processes for data interpretation and analysis that perpetuate inequality. Implications for practice: By acknowledging the relationship between data and context, we can promote better, more just data practices, preparing TPC professionals to work alongside community stakeholders in intersectional coalitions and challenging the conditions that lead to unjust data that fail to represent, over-represent, or blatantly misrepresent the realities of vulnerable communities.

Are CDS spreads predictable during the Covid-19 pandemic? Forecasting based on SVM, GMDH, LSTM and Markov switching autoregression.

This paper investigates the forecasting performance for credit default swap (CDS) spreads by Support Vector Machines (SVM), Group Method of Data Handling (GMDH), Long Short-Term Memory (LSTM) and Markov switching autoregression (MSA) for daily CDS spreads of the 513 leading US companies, in the period 2009-2020. The goal of this study is to test the forecasting performance of these methods before and during the Covid-19 pandemic and to check whether there are changes in the market efficiency. MSA outperforms all other methods most frequently. GMDH breaks the efficient market hypothesis more frequently (75%) than other methods. The change of the relative predictability during Covid-19 is small with some increase of the advantage of the investigated methods over a benchmark. We find that the market has been less efficient during Covid-19, however, there are no huge differences in prediction performances before and during the Covid-19 period.

2AI&7D Model of Resistomics to Counter the Accelerating Antibiotic Resistance and the Medical Climate Crisis

The antimicrobial resistance (AMR) crisis is referred to as ‘Medical Climate Crisis’. Inappropriate use of antimicrobial drugs is driving the resistance evolution in pathogenic microorganisms. In 2014 it was estimated that by 2050 more people will die due to antimicrobial resistance compared to cancer. It will cause a reduction of 2% to 3.5% in Gross Domestic Product (GDP) and cost the world up to 100 trillion USD. The indiscriminate use of antibiotics for COVID-19 patients has accelerated the resistance rate. COVID-19 reduced the window of opportunity for the fight against AMR. This man-made crisis can only be averted through accurate actionable antibiotic knowledge, usage, and a knowledge driven Resistomics. In this paper, we present the 2AI (Artificial Intelligence and Augmented Intelligence) and 7D (right Diagnosis, right Disease-causing-agent, right Drug, right Dose, right Duration, right Documentation, and De-escalation) model of antibiotic stewardship. The resistance related integrated knowledge of resistomics is stored as a knowledge graph in a Neo4j properties graph database for 24 × 7 access. This actionable knowledge is made available through smartphones and the Web as a Progressive Web Applications (PWA). The 2AI&7D Model delivers the right knowledge at the right time to the specialists and non-specialist alike at the point-of-action (Stewardship committee, Smart Clinic, and Smart Hospital) and then delivers the actionable accurate knowledge to the healthcare provider at the point-of-care in realtime. © 2021, Springer Nature Switzerland AG.