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The purpose of this paper is to examine the relationship between financial development, openness in financial services trade and economic growth in BRICS countries for the period 1990–2012.

An index for financial development has been constructed using principal component analysis technique by including banking sector development, stock market development, bond market development and insurance sector development. For the robustness of the result, the long-run cointegrating relationship amongst the variables has been analyzed.

Overall financial development has a positive and significant impact on economic growth. To take the full advantage of openness in financial services trade, countries need to put more emphasis on the development of their stock markets, bond markets and the insurance sector. The result shows that openness in financial services trade has a positive impact on economic growth when the stock market, bond market and insurance sector are included in the system.

The policy implication of the findings is that policymakers should focus more on developing all four areas of finance to get the full benefit of the financial system on the process of economic growth.

The authors have constructed the better indicators of financial development in the case of BRICS economies. Most of the studies in BRICS economies have measured the development of the financial sector as either banking sector development or stock market development. However, the present study includes all four areas of finance (banking sector development, stock market development, insurance sector development and bond market development) into account.

China’s economic development in the past 40 years has an array of distinctive features that have attracted the attention of the world. The paper aims to discuss this issue.

The analysis logic is as follows: with regard to the mechanism, the above factors were met in a timely manner and jointly contributed positive energy to China’s economic growth, with the increase in the savings rate as the necessary condition and foundation, and the increase in the savings rate is attributed to the explosive expansion of the financial system at the beginning of reform and the formation of positive incentives for residents, enterprises and governments at all levels, and the expansion of the financial system and the formation of positive incentives are clearly the crystallization of the wisdom of Chinese-style progressive reform.

Therefore, we have every reason to believe that the growth prospects of the Chinese economy remain bright. The author is nonetheless confident that the new two-step strategy for economic development will be realized, proposed by the 19th CPC National Congress.

Moreover, the growth of China’s economy has long been accompanied by the “double surplus” of current accounts and capital and financial accounts in the international balance of payments, which is not completely consistent with the traditional paradigm of development economics. These phenomena are so unique that the international community calls it the “Mystery of China” or “China’s Development Path.”

Critics say cryptocurrencies are hard to predict and lack both economic value and accounting standards, while supporters argue they are revolutionary financial technology and a new asset class. This study aims to help accounting and financial modelers compare cryptocurrencies with other asset classes (such as gold, stocks and bond markets) and develop cryptocurrency forecast models.

Daily data from 12/31/2013 to 08/01/2020 (including the COVID-19 pandemic period) for the top six cryptocurrencies that constitute 80% of the market are used. Cryptocurrency price, return and volatility are forecasted using five traditional econometric techniques: pooled ordinary least squares (OLS) regression, fixed-effect model (FEM), random-effect model (REM), panel vector error correction model (VECM) and generalized autoregressive conditional heteroskedasticity (GARCH). Fama and French's five-factor analysis, a frequently used method to study stock returns, is conducted on cryptocurrency returns in a panel-data setting. Finally, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to a portfolio makes a difference.

The seven findings in this analysis are summarized as follows: (1) VECM produces the best out-of-sample price forecast of cryptocurrency prices; (2) cryptocurrencies are unlike cash for accounting purposes as they are very volatile: the standard deviations of daily returns are several times larger than those of the other financial assets; (3) cryptocurrencies are not a substitute for gold as a safe-haven asset; (4) the five most significant determinants of cryptocurrency daily returns are emerging markets stock index, S&P 500 stock index, return on gold, volatility of daily returns and the volatility index (VIX); (5) their return volatility is persistent and can be forecasted using the GARCH model; (6) in a portfolio setting, cryptocurrencies exhibit negative alpha, high beta, similar to small and growth stocks and (7) a cryptocurrency portfolio offers more portfolio choices for investors and resembles a levered portfolio.

One of the tasks of the financial econometrics profession is building pro forma models that meet accounting standards and satisfy auditors. This paper undertook such activity by deploying traditional financial econometric methods and applying them to an emerging cryptocurrency asset class.

This paper attempts to contribute to the existing academic literature in three ways: Pro forma models for price forecasting: five established traditional econometric techniques (as opposed to novel methods) are deployed to forecast prices; Cryptocurrency as a group: instead of analyzing one currency at a time and running the risk of missing out on cross-sectional effects (as done by most other researchers), the top-six cryptocurrencies constitute 80% of the market, are analyzed together as a group using panel-data methods; Cryptocurrencies as financial assets in a portfolio: To understand the linkages between cryptocurrencies and traditional portfolio characteristics, an efficient frontier is produced with and without cryptocurrencies to see how adding cryptocurrencies to an investment portfolio makes a difference.

The performance of financial markets is significantly influenced by the political environment during general elections. This study investigates the effect of general elections on stock market performance in selected African markets.

Prior studies have been inconsistent in determining whether electioneering events negatively or positively influence stock market performance. The study utilized panel data set with annual observations from 1990 to 2020. The generalized method of moments (GMM) is employed to investigate the effect of electioneering and change in government on key stock market performance indicators, including stock market capitalization, stock market turnover ratio and the value of stock traded.

The study finds that electioneering activities generally have a positive impact on the performance of the stock market, whereas a change in government has a negative impact. As a result, the study recommends that stakeholders of the stock market remain vigilant and actively monitor electioneering events to devise and implement effective policies aimed at mitigating political risks during general elections. By adopting these measures, investor confidence can be significantly enhanced, fostering a more robust and secure investment environment.

The study investigates a neglected section of the literature by highlighting not only the effect of elections on stock market indicators but also possible change in government during elections.

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.

The aim of the paper is to investigate the risk-hedging and/or safe haven properties of environmental, social and governance (ESG) index during the COVID-19 in China.

This paper employs the DCC, VCC, CCC as well as Newey–West estimator regression.

The findings provide empirical evidence of the risk hedging properties of ESG indexes as well as of the environmental, social and governance thematic indexes during the outbreak of the COVID-19 crisis. The results also support the superior risk hedging properties of ESG indexes over cryptocurrency. However, the authors do not find any safe haven properties of ESG, Bitcoin, gold and West Texas Intermediate (WTI).

The paper offers therefore, practical policy implications for asset managers, central bankers and investors suggesting the pandemic risk-hedging opportunities of ESG investments.

The study represents one of the first empirical contributions examining safe-haven and hedging properties of ESG indexes compared to traditional and innovative safe haven assets, during the eruption of the COVID-19 crisis.

The paper aims to identify the differences between developed and developing country firms with respect to firm-specific and country-level determinants of their capital structure. For this purpose, all constituent firms in one of the oldest Islamic equity indices, Dow Jones Islamic Market World Index (DJIM), are considered and the Muslim-majority status of each firm's domicile country is recognized.

The study employs Hausman–Taylor random effects regression with endogenous covariates to explain the debt ratios of firms in DJIM by separating them into developed and developing country subsamples in an unbalanced panel data setting. Developing country subsample is further split into two based on the Muslim-majority status of each firm's domicile country.

Consistent with the previous literature, this study finds that firm-specific characteristics are the main determinants of their capital structure. Additionally, the paper shows that country-level characteristics have an impact on the debt ratio, however, the types of factors vary across developed and developing countries. Debt ratios in developing country firms are lower than those in developed country firms, largely due to the significantly smaller leverage ratios of firms in Muslim-majority countries. Although the debt ratios of DJIM firms are higher in “non-Muslim” countries, the set of firm-level capital structure determinants are not statistically explained by operating in a “Muslim” country. The study also documents that, before the global financial crisis of 2008, companies in developing countries have gradually become less leveraged worldwide.

This paper provides a new perspective into the differences between developed and developing country firms' capital structures by focusing on a relatively homogeneous data set restricted by leverage screening rules of an Islamic equity index and recognizing the Muslim-majority status of each firm's domicile country.

This study investigates the effect of global and domestic uncertainty on the dynamics of portfolio investment in 21 economies (mostly advanced and larger emerging economies) from 2001–2016.

Specifically, the evolution of the net portfolio equity investment inflows (FPI net inflows) and the evolution of net portfolio investment (FPI net) are investigated in a context in which the degree and the volatility of domestic economic policy uncertainty (EPU) and world uncertainty index (WUI) varied. The authors provide an empirical analysis through the sequential (two-stage) estimation of linear panel data models for unbalanced panel data.

An increase in the degree and volatility of domestic EPU has a significant negative influence on FPI net inflows, while an increase in WUI has a significant positive one. Notably, a simultaneous increase in the domestic EPU and WUI enhances the net inflows of FPI, whereas a simultaneous increase in the volatility of these indicators reduces the net inflows of FPI. An increase in the degree and volatility of both domestic EPU and WUI have a significant positive effect on the net portfolio investment, implying that a significant net portfolio investment is going out of the country.

The results of this study encourage international investors to consider uncertainty indicators (and, more specifically, their variations) in their portfolio strategy to optimize their position on the international markets. The findings of this study invite policy-makers from large countries to reduce the perceived domestic uncertainty since this parameter can influence international investors' sensitivity and willingness to diversify their position out of the country.

The authors' approach focuses on the variations of uncertainty (existing literature mainly works with the indicators). While the results confirm the role played by large markets in international portfolio investment management, it nuances the changes in the portfolio management behaviors toward other markets when facing a changing uncertainty.

The purpose of the study is to find out the impact of gold and oil prices on the stock market.

This study uses the data on gold prices, stock exchange and oil prices for the period 1991–2016. This study applied descriptive statistics, augmented Dickey–Fuller test, correlation and autoregressive distributed lag test.

The data analysis results showed that gold and oil prices have a significant impact on the stock market.

Following empirical evidence of this study, the authors recommend that investors should invest in gold because the main reason is that hike in inflation reduces the real value of money, and people seek to invest in alternative investment avenues like gold to preserve the value of their assets and earn additional returns. This suggests that investment in gold can be used as a tool to decline inflation pressure to a sustainable level. This study was restricted to use small sample data owing to the availability of data from 1991 to 2017 and could not use structural break unit root tests with two structural break and structural break cointegration approach, as these tests require high-frequency data set.

This study provides information to the investors who want to get the benefit of diversification by investing in gold, oil and stock market. In the current era, gold prices and oil prices are fluctuating day by day, and investors think that stock returns may or may not be affected by these fluctuations. This study is unique because it focusses on current issues and takes the current data in this research to help investment institutions or portfolio managers.

This paper aims to provide an important perspective to the predictive capacity of Organization of the Petroleum Exporting Countries (OPEC) meeting dates and production announcements for energy futures (crude oil West Texas Intermediate (WTI), gasoline reformulated gasoline blendstock for oxygen blending (RBOB), Brent oil, London gas oil, natural gas and heating oil) market returns and volatilities.

To examine the impact of OPEC news on energy futures market returns and volatilities, the authors use a conditional quantile regression methodology during the period from April 01, 2013 to June 30, 2017.

From the empirical findings, the authors show a conditional dependence between energy futures returns and OPEC-based predictors; hence, the authors can find clear the significance of relationship in the process of financialization of the OPEC announcements and energy futures in the case of this paper. From the quantile-causality test, the authors find that the effect of OPEC news is important to energy futures. Specifically, OPEC announcements dates predict the quantiles of the conditional distribution of energy futures market returns.

The authors confirm the presence of unidirectional nexus between OPEC news and energy commodities futures in the long term.