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This study aims to explore the risk spillover effects among different sectors of the Chinese stock market after the outbreak of COVID-19 from both Internet sentiment and price fluctuations.

The authors develop four indicators used for risk contagion analysis, including Internet investors and news sentiments constructed by the FinBERT model, together with realized and jump volatilities yielded by high-frequency data. The authors also apply the time-varying parameter vector autoregressive (TVP-VAR) model-based and the tail-based connectedness framework to investigate the interdependence of tail risk during catastrophic events.

The empirical analysis provides meaningful results related to the COVID-19 pandemic, stock market conditions and tail behavior. The results show that after the outbreak of COVID-19, the connectivity between risk spillovers in China's stock market has grown, indicating the increased instability of the connected system and enhanced connectivity in the tail. The changes in network structure during COVID-19 pandemic are not only reflected by the increased spillover connectivity but also by the closer relationships between some industries. The authors also found that major public events could significantly impact total connectedness. In addition, spillovers and network structures vary with market conditions and tend to exhibit a highly connected network structure during extreme market status.

The results confirm the connectivity between sentiments and volatilities spillovers in China's stock market, especially in the tails. The conclusion further expands the practical application and theoretical framework of behavioral finance and also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management across stock sectors.

This paper aims to investigate the interconnectedness of redenomination risk premiums across the four main European sovereign bond markets (France, Germany, Italy and the Netherlands).

The authors used the time-varying parameter vector autoregressions method to achieve the objectives.

This study reveals that the redenomination risk connectedness throughout the Euro area sovereign bond markets is dynamic and exhibits remarkable variations across various crisis episodes, such as the COVID-19 pandemic and Russia–Ukraine tensions. In addition, the analysis uncovers significant bilateral connections between countries. Furthermore, the research finds that spillovers from the US dollar redenomination premium (USDRP) are greater than those from the euro redenomination premium (ERP) and currency redenomination premium (CRP). However, during the Ukraine–Russia tensions, the connectedness between the USDRP is stronger than that between the ERP and CRP. On the other hand, the connectedness between CRP is higher than the USDRP and ERP during the COVID-19 pandemic. Importantly, this study demonstrates that the four countries play a role as both shock transmitters and receivers, switching alternatively.

This study contributes to the related literature by exploring the redenomination risk connectedness throughout the Euro area sovereign bond markets. Specifically, we rely on the USDRP, the ERP and CRP. These findings have serious implications for both portfolio risk management.

As financial markets for environmentally friendly investment grow in both scope and size, analyzing the relationship between green financial markets and African stocks becomes an important issue. Therefore, this paper examines the role of infectious disease-based uncertainty on the dynamic spillovers between African stock markets and clean energy stocks.

The authors employ the dynamic spillover in time and frequency domains and the nonparametric causality-in-quantiles approach over the period of November 30, 2010, to August 18, 2021.

These findings are discernible in this study's analysis. First, the authors find evidence of strong connectedness between the African stock markets and the clean energy market, and long-lived but weak in the short and medium investment horizons. Second, the BDS test shows that nonlinearity is crucial when examining the role of infectious disease-based equity market volatility in affecting the interactions between clean energy stocks and African stock markets. Third, the causal analysis provides evidence in support of a nonlinear causal relationship between uncertainties due to infectious diseases and the connection between both markets, mostly at lower and median quantiles.

Considering the global and recent use of clean energy equities and the stock markets for hedging and speculative purposes, one may argue that rising uncertainties may significantly influence risk transmissions across these markets. This study, therefore, is the first to examine the role of pandemic uncertainty on the connection between clean stocks and the African stock markets.

In recent years, the development of metaheuristic algorithms for solving optimization problems within a reasonable timeframe has garnered significant attention from the global scientific community. In this work, a new metaheuristic algorithm inspired by the inflection mechanism of the avian influenza virus H5N1 in poultry and humans, taking into account its mutation mechanism, called H5N1.

This algorithm aims to explore optimal solutions for optimization problems by simulating the adaptive behavior and evolutionary process of the H5N1 virus, thereby enhancing the algorithm’s performance for all types of optimization problems. Additionally, a balanced stochastic probability mechanism derived from the infection probability is presented. Using this mechanism, the H5N1 algorithm can change its phrase, including exploitation and exploration phases. Two versions of H5N1, SH5N1 and MH5N1, are presented to solve single-objective optimization problems (SOPs) and multi-objective optimization problems (MOPs).

The performance of the algorithm is evaluated using a set of benchmark functions, including seven unimodal, six multimodal, ten fixed-dimension multimodal to solve SOPs, ZDT functions and CEC2009 has been used to demonstrate its superiority over other recent algorithms. Finally, six optimization engineering problems have been tested. The results obtained indicate that the proposed algorithm outperformed ten algorithms in SOPs and seven algorithms in MOPs.

The experimental findings demonstrate the outstanding convergence of the H5N1 algorithm and its ability to generate solutions of superior quality.

This study attempts to examine the time-varying volatility spillovers between environmentally sustainable assets and quantify the value-at-risk of the portfolios across various frequencies.

To accomplish these objectives, this paper utilizes a connectedness index-based TVP-VAR model and applies the wavelet-based VaR ratio to daily data spanning from January 2018 to September 2023.

The empirical findings reveal a notable increase in the connectedness index between green stocks and green bonds during the COVID-19 crisis, signifying evidence of a contagion effect. The portfolio’s risk ratio also exhibited a sharp rise amid the pandemic, particularly over medium and long-term horizons, driven by increased spillover among green assets. Notably, our analysis indicates that green bonds influence the connectedness system between green stocks and the value-at-risk ratio, reducing volatility spillover and portfolio risk ratios across various investment horizons. These results highlight the role of green bonds as an effective diversification asset against the risks associated with green equities.

This research investigates the dynamic connectedness and value-at-risk ratio between eight green sectoral renewable energy and non-energy equities and green bonds. We put forward some portfolio implications for green investors with an environmental consciousness who desire to decarbonize their portfolios and mitigate environmental issues.

Innovative technologies have gained popularity in recent years as a means of improving workers' general well-being at work. Among these exciting new technologies is virtual reality (VR). With a focus on enhancing individual performance, this chapter explores the application of VR as a human resource (HR) intervention to improve spirituality in the workplace. To offer a theoretical foundation for comprehending the possible effects of VR interventions on workplace spirituality, this chapter thoroughly evaluates the literature on mindfulness, quantum consciousness and workplace spirituality. By integrating VR technology with the ideas of these theoretical frameworks, HR professionals may create interventions that foster employee effectiveness, resilience and personal growth. It has also been suggested that HR managers employ VR mindfulness and meditation sessions, virtual retreats, values alignment workshops, empathy-building simulations and spiritual reflection spaces as practical VR interventions to enhance workplace spirituality. To illustrate the usefulness of VR in enhancing workplace spirituality, a few companies that have successfully implemented VR therapies are also cited. Lastly, the challenges and moral dilemmas associated with utilising VR to promote workplace spirituality have been examined. These include privacy difficulties, possible biases in VR content and the requirement for ongoing evaluation and feedback techniques. This chapter highlights how VR has the potential to be a game-changing tool for improving workplace spirituality and boosting individual effectiveness.

This paper aims to analyze the connectedness between Gulf Cooperation Council (GCC) stock market index and cryptocurrencies. It investigates the relevant impact of RavenPack COVID sentiment on the dynamic of stock market indices and conventional cryptocurrencies as well as their Islamic counterparts during the onset of the COVID-19 crisis.

The authors rely on the methodology of Diebold and Yilmaz (2012, 2014) to construct network-associated measures. Then, the wavelet coherence model was applied to explore co-movements between GCC stock markets, cryptocurrencies and RavenPack COVID sentiment. As a robustness check, the authors used the time-frequency connectedness developed by Barunik and Krehlik (2018) to verify the direction and scale connectedness among these markets.

The results illustrate the effect of COVID-19 on all cryptocurrency markets. The time variations of stock returns display stylized fact tails and volatility clustering for all return series. This stressful period increased investor pessimism and fears and generated negative emotions. The findings also highlight a high spillover of shocks between RavenPack COVID sentiment, Islamic and conventional stock return indices and cryptocurrencies. In addition, we find that RavenPack COVID sentiment is the main net transmitter of shocks for all conventional market indices and that most Islamic indices and cryptocurrencies are net receivers.

This study provides two main types of implications: On the one hand, it helps fund managers adjust the risk exposure of their portfolio by including stocks that significantly respond to COVID-19 sentiment and those that do not. On the other hand, the volatility mechanism and investor sentiment can be interesting for investors as it allows them to consider the dynamics of each market and thus optimize the asset portfolio allocation.

This finding suggests that the RavenPack COVID sentiment is a net transmitter of shocks. It is considered a prominent channel of shock spillovers during the health crisis, which confirms the behavioral contagion. This study also identifies the contribution of particular interest to fund managers and investors. In fact, it helps them design their portfolio strategy accordingly.

Many firms engage customers using coalition loyalty programs. One unique characteristic of these programs is that one partner’s performance can affect the performance of other partners (cross-partner effect). While previous research discusses cross-partner effects from the program sales perspective, the role of point redemptions in cross-partner effects is unknown to marketers. This study aims to investigate this role and discusses its variations among stores of the same chain and those of different chains.

Using the data of a popular coalition loyalty program, this paper estimates an empirical model that accounts for the dynamics of program sales and point redemptions and the heterogeneity among different partners in the program.

Cross-partner effects are different between point redemption and program sales. In particular, program sales (point redemptions) in other stores of different chains positively (negatively) affect the focal store’s point redemptions. However, point redemptions in other stores of the same chain as the focal store positively affect the focal store’s program sales.

Coalition loyalty programs are becoming popular around the globe. This research investigates the cross-partner effects of coalition loyalty programs. This is of immense value to practitioners and researchers alike.

This research gives marketing managers insights into the workings of coalition loyalty programs.

This research contributes to loyalty program literature in three ways. First, it complements the literature by investigating the role of point redemption in cross-partner effects. Second, it discusses cross-partner effects in the competing stores from the same chain of the focal store and those from different chains. Third, it explores the dynamic effects of program sales and point redemptions at other stores on program sales at the focal store.