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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.

This study examines how specific micro-level macroeconomic indicators influence corporate performance volatility among US corporate bodies in the short run.

The study employs error correction autoregressive distributed lagged (ARDL) model (ECM) to examine how micro-level variables influence volatility associated with corporate performance in the short run.

This paper finds that disaggregated or micro-level variables examined, tend to exhibit features that are not readily apparent from the aggregate variable from which such variables are derived. For instance, reported empirical estimate suggests that, growth in expenditures on services and nondurable goods tend to lower volatility associated with corporate performance, whereas government expenditures and expenditures on durable goods rather worsens volatility associated with corporate performance, all things being equal. Additionally, presented empirical estimates further provide evidence suggesting that macroeconomic uncertainty and inflation uncertainty significantly moderate or influence the extent to which disaggregated variables impact corporate performance volatility.

Compared to related studies in the reviewed literature, this study rather examines volatility associated with corporate performance instead of the corporate performance indicator itself. Additionally, this paper also examines how disaggregated variable instead of aggregate variables impact such volatility. Finally, the moderating role of key macroeconomic conditions in such a relationship is also examined.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

The volatility of bitcoin (BTC) and time horizon is the center point for investment decisions. However, attention is not often drawn to the relationship between BTC and equity indices. Thus, the purpose of this paper is to investigate the volatility and time frequency domain of BTC with stock markets.

As cryptocurrencies continue to gain viability as an asset class, institutional investors and publicly traded firms have started taking investment positions in digital currencies. What firms may not be considering, however, is the effect these assets may have on their risk profiles. This study aims to (1) measure the effect of cryptocurrencies on the risk and return characteristics of publicly traded companies; (2) decipher the motives behind holding cryptocurrencies as an asset class; and (3) determine whether one reason for holding is more effective than another. To conduct this research, the four largest publicly traded holders of cryptocurrency as well as four of the most prominent cryptocurrencies are explored.

The cross-sectional analysis approach has been used to analyze the daily returns, volatility, betas and Sharpe Ratios of firms during periods without cryptocurrency strategies and during periods with cryptocurrency strategies.

The impact of the cryptocurrency asset class on common stock performance and corporate disclosures are documented. The importance of risk disclosures on cryptocurrency holdings is emphasized: Firms must better inform their stakeholders through comprehensive disclosures in financial statements. Firms utilize cryptocurrencies for various reasons such as treasury management tools or as direct sources of income. Consequently, the impact on returns and risks varies substantially.

To the best of the authors’ knowledge, this is one of the first studies on cryptocurrency investments in the treasury departments of publicly traded companies. The study contributes to the literature by extracting relevant information regarding company risk reporting and cryptocurrency risk at firms. The conclusions also promote firm transparency with detailed reporting of cryptocurrency holding risks.

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.

This study analyzes the static and dynamic risk spillover between US/Chinese stock markets, cryptocurrencies and gold using daily data from August 24, 2018, to January 29, 2021. This study provides practical policy implications for investors and portfolio managers.

The authors use the Diebold and Yilmaz (2012) spillover indices based on the forecast error variance decomposition from vector autoregression framework. This approach allows the authors to examine both return and volatility spillover before and after the COVID-19 pandemic crisis. First, the authors used a static analysis to calculate the return and volatility spillover indices. Second, the authors make a dynamic analysis based on the 30-day moving window spillover index estimation.

Generally, results show evidence of significant spillovers between markets, particularly during the COVID-19 pandemic. In addition, cryptocurrencies and gold markets are net receivers of risk. This study provides also practical policy implications for investors and portfolio managers. The reached findings suggest that the mix of Bitcoin (or Ethereum), gold and equities could offer diversification opportunities for US and Chinese investors. Gold, Bitcoin and Ethereum can be considered as safe havens or as hedging instruments during the COVID-19 crisis. In contrast, Stablecoins (Tether and TrueUSD) do not offer hedging opportunities for US and Chinese investors.

The paper's empirical contribution lies in examining both return and volatility spillover between the US and Chinese stock market indices, gold and cryptocurrencies before and after the COVID-19 pandemic crisis. This contribution goes a long way in helping investors to identify optimal diversification and hedging strategies during a crisis.

This article aims to explain the role of philosophical anchors and research paradigms in business research, and how they can be extrapolated in the transformative era of automation, digitalization, hyperconnectivity, obligations, globalization and sustainability (ADHOGS) in the midst of disruption, volatility, uncertainty, complexity and ambiguity (DVUCA).

This article entails a general review based on the 3Es of exposure, expertise and experience, delving into the ontological, epistemological, methodological, axiological and rhetorical aspects of the major research paradigms—i.e. positivism, post-positivism, constructivism, interpretivism and pragmatism—and their interplay with the emergent trends shaping business research.

This article underscores the multifaceted nature of business research in the modern day, with an increasing need for blending, or shifting between, research paradigms to address the complex issues arising from automation, digitalization, hyperconnectivity, obligations, globalization and sustainability (ADHOGS). This article also highlights the nuanced interplay between research paradigms and theoretical perspectives, demonstrating the rich, diverse potential of business research inquiries.

While this article provides a broad overview of the interplay between research paradigms and emerging trends, future research could explore each of these interplays in greater detail, conducting empirical studies or utilizing specific case studies.

Researchers and practitioners should be open to adopting, combining or switching between different paradigms according to the demands of their research questions, context and trends shaping the business landscape, thereby underscoring the need for methodological flexibility and reflexivity in business research.

The shift toward embracing digital transformations and integrating sustainability in business research holds significant implications, driving socially responsible and sustainable business practices at the micro-level, and by extension, industrial revolution and sustainable development at the macro-level.

This article offers a holistic and contextualized view of the philosophy of science and research paradigms for business research, bridging the gap between philosophical foundations and contemporary research trends.

This paper aims to empirically investigate the sources of real exchange rate fluctuations in Egypt using structural vector autoregression (SVAR). The data covers the period between 1980 and 2016, where exchange regime has been changed more than once.

This paper investigates the source of real exchange rate fluctuations for the period between 1980 and 2016 using the SVAR method. The SVAR method will incorporate real gross domestic product (GDP), real effective exchange rate (REER) and price level in a multidimensional equations system. However, impulse response function (IRF) and error variance decompositions (EVDC) will be generated by the system to have a behavioral insight of real exchange rate in response to economic shocks.

The IRF and EVDC results indicate a significant impact of demand shocks over the real exchange rate relative to supply shocks and monetary shocks in the period between 1980 and 2016. On the other hand, monetary shocks will have a negligible effect on the real exchange rate in the short run and converging to its previous level in the covering period of the study.

In the best of the authors' knowledge, the topic of the source of the real exchange rate fluctuations in Egypt has not been discussed in a wide range due to the lack of time series data. However, this study provides constructed data for REER for Egypt with the published method in the International Monetary Fund (IMF). Furthermore, the study involves theoretical and econometric modeling to ensure the reliability of the economic results.

The aim of the study was to analyze the performance of Black-Litterman (BL) portfolios using a views estimation procedure that simulates investor forecasts based on technical analysis.

Ibovespa, S&P500, Bitcoin and interbank deposit rate (IDR) indexes were respectively considered proxies for the national, international, cryptocurrency and fixed income stock markets. Forecasts were made out of the sample aiming at incorporating them in the BL model, using several portfolio weighting methods from June 13, 2013 to August 30, 2022.

The Sharpe, Treynor and Omega ratios point out that the proposed model, considering only variable return assets, generates portfolios with performances superior to their traditionally calculated counterparts, with emphasis on the risk parity portfolio. Nonetheless, the inclusion of the IDR leads to performance losses, especially in scenarios with lower risk tolerance. And finally, given the impact of turnover, the naive portfolio was also detected as a viable alternative.

The results obtained can contribute to improve investors practices, specifically by validating both the performance improvement – when including foreign assets and cryptocurrencies –, and the application of the BL model for asset pricing.

The main contributions of the study are: performance analysis incorporating cryptocurrencies and international assets in an uncertain recent period; the use of a methodology to compute the views simulating the behavior of managers using technical analysis; and comparing the performance of portfolio management strategies based on the BL model, taking into account different levels of risk and uncertainty.