Purpose: This study aims to investigate the safe-haven and hedging properties of Bitcoin against a wide variety of conventional assets before and during the coronavirus disease 2019 (COVID-19) pandemic.Design/methodology/approach: This paper uses a smooth transition regression (STR) to jointly test the hedging properties of Bitcoin in normal conditions and Bitcoin's safe-haven properties in extreme stock market conditions.Findings: Highlighting the results, the authors show that Bitcoin is able to provide safe-haven feature during the COVID-19 pandemic period while Bitcoin serves as a hedge tool in the pre-COVID-19 pandemic period. The findings also show that the prowess of the safe-haven/hedge nature is sensitive to the type of the asset market and the time horizon when switching from daily to weekly frequency data.Originality/value: This is one of the first studies that conduct a combined analysis of the safe-haven and hedging capabilities of Bitcoin against several asset classes using an STR method. This study uses the longest sample period to yet, allowing researchers to examine Bitcoin's safe-haven and hedging features both before and after the COVID-19 pandemic.

Purpose: This paper examines the relationship between volatility, sentiment and returns in terms of levels and changes for both lower and higher data frequencies using quantile regression (QR) method.Design/methodology/approach: In the first step, the study applies the Granger causality test to understand the causal relationship between realized volatility, returns and sentiment as levels and changes. In the second step, the study employs a QR method to investigate whether investor sentiment and returns can predict realized volatility. This regression method gives robust results irrespective of distributional assumptions and to outliers in the dependent variable.Findings: Empirical results show that the VIX volatility index is a better fear gauge of market-wide investors' sentiments and has a predictive power for future realized volatility in terms of levels and changes for both higher and lower data frequencies. This study provides evidence that the relationship between realized volatility, investor sentiment and returns, respectively, is not symmetric for all quantiles of QR, as opposed to OLS regression. Furthermore, this work supports the behavioral theory beyond leverage hypothesis in explaining the asymmetric relation between returns and volatility at higher and lower data frequencies.Originality/value: This paper adds to the limited understanding of investor sentiment’s impact on volatility by proposing a QR model which provides a more complete picture of the relationship at all parts of the volatility distribution for both higher and lower data frequencies and in terms of levels and changes. To the author knowledge, this is the first paper to study the volatility responses to positive and negative sentiment changes for developed market and to use both lower and higher data frequencies as well as data in terms of levels and changes.

Purpose: This study investigates the diversification benefits of multiple cryptocurrencies and their usefulness as investment assets, individually or combined, in enhancing the performance of a well-diversified portfolio of traditional assets before and during the pandemic COVID-19.Design/methodology/approach: This paper uses two optimization techniques, namely the mean-variance and the maximum Sharpe ratio. The naïve diversification rules are used for comparison. Besides, the Sharpe and the Sortino ratios are used as performance measures.Findings: The results show that cryptocurrencies diversification benefits occur more during the COVID-19 pandemic rather than before it, with the maximum Sharpe ratio portfolio presenting its highest performance. Furthermore, the results suggest that, during COVID-19, the diversification benefits are slightly better when using a combination of cryptocurrencies to an already well-diversified portfolio of traditional assets rather than individual ones. This serves to improve the performance of the maximum Sharpe ratio portfolio, and to some extent, the naïve portfolio. Yet, cryptocurrencies, whether added individually or combined to a well-diversified portfolio of traditional assets, don't fit in the minimum variance portfolio. Besides, the efficient frontier during COVID-19 pandemic dominates the one before COVID-19 pandemic, giving the investor a better risk-return trade-off.Originality/value: To the best of the author's knowledge, this is the first study that examines the diversification benefits of multiple cryptocurrencies both as individual investments and as additional asset classes, before and during COVID-19 pandemic. The paper covers all analyses performed separately in previous studies, which brings new evidence regarding the potential for cryptocurrencies in portfolio diversification under different portfolio strategies.

Purpose: This study explores the dynamic connectedness among geopolitical risk (GPR), crude oil market volatility (OVX), investor attention (IA), and major agricultural, livestock and metal commodity markets. Design/methodology/approach: Employing the quantile-frequency connectedness framework developed by Chatziantoniou et al. (2022), we examine how the interrelationships among these variables evolve across market conditions -ranging from normal to extreme- and across various investment horizons, from short to long-term. In contrast to traditional methods that focus solely on either quantile or frequency domains, our approach captures the dual dimensions of financial contagion. The sample period spans from January 2020 to June 2024, which encompasses the Russian-Ukrainian and the Israeli-Palestinian conflicts. Findings: The connectedness analysis reveals several noteworthy findings. First, extreme quantiles display substantially higher total connectedness compared to the median quantile. Furthermore, the results highlight a pronounced asymmetry in connectedness, with spillover effects being more pronounced in the extreme upper quantile than in the extreme lower quantile. Second, under normal and bearish market conditions, short-term connectedness tends to dominate, whereas bullish markets are characterized by stronger long-term spillovers. Originality/value: The manuscript offers a novel contribution by jointly exploring the connectedness between geopolitical risk, crude oil volatility, investor attention, and commodity markets using the advanced quantile-frequency connectedness approach of Chatziantoniou et al. (2022). This dual-dimensional framework, applied to two major recent conflicts (Russia-Ukraine and Israel-Palestine), adds originality, especially in capturing both the economic and psychological dimensions of market reactions across varying time horizons and market regimes.