A Comparative Analysis of the Nature of Stock Return Volatility in BRICS and G7 Markets

Abstract

Through globalization and financial market liberalization, the opening up of markets has increased cross-border investments as investors search for higher risk-adjusted returns. This ability to invest internationally has raised the attention given to emerging markets that offer higher risk-adjusted returns relative to developed markets. However, despite the growing importance of emerging markets, the literature on the nature of volatility in global markets is typified by generalizations of findings from developed markets. To fill this gap, this study comparatively examined the nature of stock return volatility in developed G7 and emerging BRICS markets. Broad market index data and GARCH models over the period 2003:01–2020:08 were employed. The study found evidence of volatility persistence, asymmetry, mean reversion and weak evidence of a risk premium in both emerging and developed markets. There was also evidence of significant differences in the nature of volatility within the two sets of markets. These volatility patterns in both groups cast doubt on the assertion that developed markets are more informationally efficient than emerging markets. Thus, markets in the same group may not always have the same nature of volatility, especially in the wake of structural events such as the COVID-19 global pandemic.

Financial modelling of cryptocurrency: a case study of Bitcoin, Ethereum, and Dogecoin in comparison with JSE stock returns.

“…For the cryptocurrency, the AR parameters remained significant, whilst for the JSE, the non-significance is retained. The mean and the alpha parameter of the JSE are insignificant, which agrees with the results of Muguto and Muzindutsi (2022) who also used the structural breaks, which did not change these parameters. Their research revealed a significant structural break for the variance equation.…”

“…Such findings may indicate the need for some form of cryptocurrency market regulation. The inefficiency also means that traditional asset pricing models such as the CAPM and APT will be inadequate to model returns in these markets (Muguto and Muzindutsi 2022).…”

“…For most cases, these models use the student t, skewed student t and the general error distributions. Examples of such studies include those of Muguto and Muzindutsi (2022) who used the GARCH, GJR-GARCH and EGARCH to quantify the half-life of volatility in the BRICS markets and the G7 markets. The same models were used by John et al (2019) who studied the half-life of Bitcoin.…”

Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment

“…Hence, not surprisingly the associated international academic literature on stock market volatility, in terms of econometric methods and predictors being considered, is massive to say the least, with a proper review being beyond the scope of this paper. We refer interested readers to the works of [3][4][5][6][7] for detailed discussions in this regard.…”

Gentlemen seek harmony but not uniformity: The heterogeneity of entrepreneurial team and organizational resilience

“…This choice also led to a divergence in the findings of the study ( Clement et al, 2021 ). Therefore, to uncover the “black box” formed by the organizational resilience of new ventures in the context of Localization in China, it is necessary to consider the characteristics of local culture ( Arikan et al, 2020 ) and interpret the mediating and moderating effects from a new perspective ( Muguto and Muzindutsi, 2022 ). Considering the long-standing problems of culture and economy ( Niedermeyer et al, 2020 ), Weber’s debates on culture and economic ethics, new institutional economics ( Carnevali et al, 2021 ), and informal institution theory ( Fricke et al, 2022 ) have made important contributions to studying the relationship between culture and economy ( Clark and Sourdin, 2020 ).…”