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PurposeThe purpose of this paper is to review the main methods used in the literature to measure financial literacy (FL) of individuals.Design/methodology/approachThe paper begins by describing how the different items used to measure the FL level of individuals are constructed. Then, it focuses on how do researchers select the items. Finally, it reviews the different calculation methods used in the literature to assess the FL level.FindingsFL as a concept is tough to define and measure. Several studies focus on the definition and the measure of this concept. Different items are used in the literature and are mostly related to the study topics. The used calculation methods differ across the different studies.Originality/valueThis paper sheds light on the principal methodologies used in the literature to measure FL. It highlights the relationship between the items' content areas and the studies' subjects. Thus, this paper suggests guidance for future studies on measuring methods of FL.

This paper aims to investigate the COVID-19 pandemic impacts on the interconnectedness between the Chinese stock market and major financial and commodity markets—gold, silver, Bitcoin, WTI, S&P 500, and Euro STOXX 50—and analyze the portfolio design implications. Using daily data from 2018 to 2021, we first apply the wavelet power spectrum (WPS) to visualize volatility shifts. In contrast to previous research, we empirically identify the precise COVID-19 outbreak dates for each market using the Perron (1997) breakpoint test. Finally, we employ the bivariate DCC-GARCH model to analyze the connectedness between markets. The findings reveal that the COVID-19 pandemic caused volatility shifts of different intensities for all of the studied markets. Moreover, each return series exhibits one break date, which is specific to each market and corresponds to a distinct COVID-19-related event. Correlations, hedge ratios, and optimal portfolio weights changed significantly after the COVID-19 outbreak. There is evidence of contagion effects between the Chinese stock market and S&P 500, Euro STOXX 50, gold, and silver. Interestingly, the latter two assets lost their safe haven property with SSE. However, WTI and Bitcoin act as safe havens against SSE risks.

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This study investigates how oil price movements impact the main Eurozone industry supersectors returns. We use a multifactor market model in which we incorporate oil price changes as an additional risk factor. In order to account for possible breaks in the relationship, we use the Bai and Perron (1998, 2003) breakpoints identification methodology. We find evidence of the presence of structural instabilities on the relationship between sector stock returns and oil price changes. Different breakpoints are identified, particularly the 2003 Iraq invasion year, the 2008 subprime crisis and the 2012 Euro debt crisis. Moreover, our results prove that stock return sensitivities to oil prices are time varying and sector dependent. Besides, the subprime financial crisis appears to induce a significantly positive effect on the oil-stock market nexus. However, the Euro debt crisis has a mostly negative effect. The other identified breakpoints do not seem to have any significant effect on the oil stock market nexus.