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The purpose of this paper is to introduce a methodology to evaluate sovereign risk. Hereby, a value-based approach using different market measures is introduced.

This study’s approach aims to provide a value-based assessment of sovereign risk, combining market measures from government bond, credit derivatives and other markets as well as economic indicators.

The study finds that the assessment of sovereign risk is only possible when using information from different markets and adjusting according to the information included in these measures. Combining both market-based and economic information leads to a value-based evaluation of sovereign risk.

The practical implications are given for any institution with sovereign risk on their asset side. In fact, part of this research was done for the German Actuarial Foundation which uses the recommendations of this paper for the insurance industry.

The study’s approach is novel because it is the first to include several market-based and economic measures of a sovereign and combines it into a value-based assessment.

The paper examines the impact of COVID-19 on bank stock returns over various time scales and frequencies for 36 countries. Moreover, the authors look at the governments' responses to the corona crisis and examine its impact on bank stock returns.

The paper applies continuous wavelet transformation to obtain robust estimates of the co-movement (coherency) between confirmed cases and bank stock returns over time and at different time scales. Furthermore, the authors apply fixed effects panel regression to examine the response of bank stocks to domestic COVID-19 policies.

The results indicate that the number of confirmed COVID-19 cases negatively impacts bank stock returns during different waves of the pandemic in the medium-run. However, there is only little dependence in the very short-run. Moreover, bank stock returns positively react to domestic COVID-19 polices. This demonstrates that governmental interventions not only reduce the spread of COVID-19 but are also able to thereby calm financial markets.

The application of wavelet methods to the field of economics and finance is relatively recent and allows the distinction between short-term and long-term effects. Standard econometric methods, in contrast, only operate within the time domain. This paper combines wavelet methods with conventional econometrics to answer the research question.

The ups and downs of the stock markets are consistently in the news. All things considered, there's no end to reporting the trajectory of volatility. Wide value changes in stock prices are a daily event in any stock market as speculators respond to monetary, business, and political situations. The main question is − did the Indian stock market develop a speculative bubble during the time of the US subprime crisis? Also, in terms of knowledge gained for an investor or a policy maker, we ask the following question: As to what extent are speculative bubbles predictable during a financial crisis? Knowledge gained by investors is also a part and parcel of an applied knowledge economy in a broader dimension.

In this chapter, the authors use a speculative bubble tracker, based on a Wiener stochastic process, to check for the existence of speculative bubbles during the 2008–2009 US subprime crisis. The data used in the study are daily SENSEX values (i.e., combination of stock prices of 30 well-established, most actively traded stocks of financially sound companies listed in the Bombay Stock Exchange) for the period between December 2007 and December 2009. Using such forms of daily data, the authors trace out the price movements using a Brownian motion equation and hence, try to correlate the stock price fluctuations with fluctuations in the crisis index (as put together by the authors) in the Indian context. Interestingly, for India, such a speculative bubble was prevalent during the time period considered pertaining to the 2008 US subprime crisis.

Summing up, the implication in terms of knowledge gained is particularly of interest for the portfolio managers who are engaged in devising diversification strategies for their portfolios.

This chapter presents a study on the work of commercial diplomats as international business promoters at foreign posts. Research has largely overlooked the actual roles and activities of commercial diplomats in explaining the effectiveness of commercial diplomacy and international business support. In this study, it is assumed that commercial diplomats’ behavior is influenced by informal institutions. Face-to-face semi-structured interviews with 23 commercial diplomats at foreign posts from different countries were conducted and analyzed. The results show three different types of role behavior and differences in proactivity per type. Informal institutions such as background, skills, and experience, cultural differences, and the working environment suggest to explain the differences in levels of proactive international business support behavior of commercial diplomats. Further research is needed to assert these findings.

The purpose of this paper is to present a new constrained optimization algorithm based on a particle swarm optimization (PSO) algorithm approach.

This paper introduces a hybrid approach based on a modified ring neighborhood with two new perturbation operators designed to keep diversity. A constraint handling technique based on feasibility and sum of constraints violation is adopted. Also, a special technique to handle equality constraints is proposed.

The paper shows that it is possible to improve PSO and keeping the advantages of its social interaction through a simple idea: perturbing the PSO memory.

The proposed algorithm shows a competitive performance against the state‐of‐the‐art constrained optimization algorithms.

The proposed algorithm can be used to solve single objective problems with linear or non‐linear functions, and subject to both equality and inequality constraints which can be linear and non‐linear. In this paper, it is applied to various engineering design problems, and for the solution of state‐of‐the‐art benchmark problems.

A new neighborhood structure for PSO algorithm is presented. Two perturbation operators to improve PSO algorithm are proposed. A special technique to handle equality constraints is proposed.

This paper aims to investigate the impact of COVID-19 and the stringency of the government policy response on stock market returns globally and at the regional level.

Pooled-ordinary least squares (OLS) and panel data techniques are used to analyse the daily data set across 88 countries in the Americas, Europe, Asia-Pacific, Middle East and Africa for the period of 1 January 2020 to 10 May 2021.

Using pooled-OLS and panel data techniques, the analyses show that both the daily growth in confirmed cases and deaths caused by COVID-19 have significant negative effects on stock returns across all markets. The effects are non-linear and U-shaped. Stock markets react more to the growth of confirmed cases than to the growth in the number of confirmed deaths. The results, however, vary across regions. More specifically, this study finds that the negative effect of confirmed cases is stronger in the Americas and the Middle East, followed by Europe. The negative direct effect of deaths caused by COVID-19 is stronger in the European region, followed by the Middle East, in relation to the rest of the world. The stock market returns in the African region are not, however, statistically significant. The researcher finds evidence that stringent policy responses lead to a significant increase in the stock market returns, both globally and across regions.

The results suggest that the integrity of the government and its interventions complemented by a stable and reliable monetary policy are crucial in providing confidence to firms and households in uncertain times.

COVID-19 has a significant impact on national economies and stock markets, triggering various governments’ interventions across all geographic regions. The pandemic has significantly affected all aspects of life, especially the stock markets. However, their empirical impact on stock returns is still unclear. This paper is the first of its kind to fill this gap by providing an in-depth quantitative analysis of the impact of both COVID-19 and stringency of the governmental policy responses on stock market returns globally and at the regional level. It is also the first to use an advanced analytical framework in analysing the effects of daily growth in both total and newly confirmed cases, and the daily growth in both total and new deaths caused by COVID-19 on them. The dynamic nature of the data on COVID-19 is taken into account. The non-linearity of the effects is also considered.

The study examines the roles of capital rules, macro variables and bank business models in determining the safety of banks as measured by the “distance-to-default” (DTD) with the purpose of drawing implications for regulation of bank capital and business models.

A panel regression study using pre- and post-crisis data for 108 US and European banks is used to explore the issue empirically. A new technique is also used to back out the amount of capital banks would have needed during the crisis to keep the “DTD” in the very safe zone.

The simple leverage ratio has a strong relationship with “DTD”, while the Basel ratio does not. The most important business model features are derivatives and wholesale funding, which have a strong negative relationship with “DTD”. Trading and available-for-sale securities have a positive influence. Calculations show that it is not possible for any reasonable capital rule to compensate for the risks created by business model features encompassing large derivative-based activities. Bank separation policies are essential.

The micro evidence-based analysis as an approach to bank regulation and business model requirements stands in contrast to the ad hoc way policy has been constructed before and after the crisis. The empirical evidence supports separation based on the balance sheet size of derivatives and a leverage ratio instead of the complex Basel risk-weighted capital approach. The current approaches to structural separation are criticised constructively, and some evidence-based suggestions for improving bank business models to reduce systemic risk are made.

This paper attempts to provide insights into the functioning of innovative companies in times of the global financial crisis. In doing so, the following study investigates whether innovations protected companies from the adverse effects of the global recession. On this occasion, the paper analyzes the economic performance of innovative industries in Poland, highlighting institutional and systemic barriers that curb their development. The main purpose of this paper is to clarify whether targeting innovative companies for equity investments proved beneficial during the global financial crisis.

This paper employs the mean return per unit of risk (MRPUR) analysis in order to investigate international portfolio diversification opportunities delivered by targeting innovative companies for equity investments in times of the global financial crisis. The paper also uses interviews and questionnaires to broaden the knowledge about issues related to the functioning of innovative companies. This is motivated by the fact that the research remains under-researched by the reviewed studies.

The paper links innovations in business strategy and production to the ability of companies to resist the global financial crisis. This paper argues that innovative approach to business strategies proved far more profitable for companies than relying on novelties in production. Furthermore, the paper provides strong evidence that innovative companies could contribute to mitigation of the global economic downturn by stimulating the sustainable economic growth in Poland. As far as the main purpose of this paper is concerned, the current study delivers useful and informative insights into the international portfolio diversification processes that assume targeting innovative investees.

This paper delivers practical implications for innovative companies, market regulators, policymakers and international investors.

The current paper addresses the absence of the academic literature devoted to the analysis of financial performance of the Polish investee companies representing innovative industries. In doing so, this paper advises on changes in regulations that would facilitate further development of innovative companies. Moreover, the paper paints the picture of the investment environment prevailing in the Central European emerging stock market of Poland. Hereto, delivering general insights into the functioning and regulatory framework of the Polish stock market proves useful in assessing the economic and financial development of Poland.

The purpose of this study is to explore some quantitative indicators from the social network analysis, observe the variations of these indicators over time and determine whether these indicators fit into the traditional team development stages model or theory. The primary focus is on the perspective of social interaction rather than the suitability of the indicator, i.e. the authors will not determine the optimal indicators nor compare the performance of different indicators. This study aims to propose a quantitative method to identify the development stages of virtual teams.

Two phases were designed in this study. The first phase was a simple study to prove the preliminary ideas and explore which quantitative indicators would be suitable for analysis. In total, 16 undergraduates were randomly assigned to two virtual teams. They were required to complete an information system (IS) project through virtual teamwork and use information and communications technologies (ICTs) to communicate with each other. After proving the preliminary ideas, the authors collected communication data of the 30 virtual teams working on IS projects in the second phase. The total duration of this process was two months.

The findings practically identified three stages, which were found to be consistent with that of the previous qualitative studies. In the initial (inclusion) stage, intensity had an upward trend. In the second (control) stage, centralization had an upward trend. In the final (affection) stage, intensity and density had upward trends and centralization had a downward trend. Both density and centralization also became smooth in this final stage. The conclusion can serve as a basis for further studies in virtual team development.

A successful virtual team will help industries to reduce their costs and increase performance and benefits. The findings will help industries quickly and objectively identify which stage they are at. This quantified approach will provide managers and leaders with a simple, useful way to highlight the needs for managing different aspects of team behavior at each stage of development. After establishing this approach, managers and leaders will be able to make plans to improve existing processes, set priorities, provide suitable principles and guidelines, etc., and eventually improve virtual team performance.