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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 purpose of this study is to examine whether there is a unidirectional or a bidirectional relationship between women and the environment, and to further study the effect of women on environmental quality.

To achieve this purpose, a Granger causality test and a random effects panel data model are used to study women–environment relationship in developing countries. Error correction model (ECM) is the chosen estimation technique. A Granger causality test is used because of its frequent use in examining the existence of a unidirectional or a bidirectional relationship between two or more variables. A random effects panel data model is used as it has proven to be more efficient than the fixed-effects panel data model.

Women Granger-cause environmental quality while the opposite is not true in developing countries in the long run. This indicates the existence of a unidirectional relationship between women and the environment when the long-run relationship is considered. However, when considering the long- and short-run relationship together, the results indicate the presence of a bidirectional relationship. The empirical results of the random effects panel data model through ECM estimation indicate the positive effect of women on improving environmental quality as illustrated by the coefficient of the current change of women. This shows that women are concerned about environmental degradation. In addition, the empirical results highlight the persistence of CO₂ emissions. Results also confirm that foreign direct investment inflows lead to further environmental degradation. However, education and trade openness coefficients are found insignificant at the current period.

The research results have great implications on women empowerment, the reduction of gender bias and the increase in government expenditure on women’s education and health because of women’s positive effect in improving environmental quality.

To the best of the author’s knowledge, this is the first paper that examines the two-way relationship between women and the environment and, hence, it fills the gap present in the literature.

Globalization occupies a central research activity and remains an increasingly controversial phenomenon in economics. This phenomenon corresponds to a subject that can be criticized through its impact on national economies. On the other hand, the world economy is evolving in a liberalized environment in which foreign direct investment plays a fundamental role in the economic development of each country. The advent of financial flows – FDI, remittances and official development assistance – can be a key factor in the development of the economy. The subject of this article is to analyses the effect of financial flows on economic growth in developing countries. Empirically, different approaches have been employed. As part of this work, an attempt was made to use a panel data approach. The results indicate ambiguous effects and confirm the results of previous work.

The authors seek to study the effect of foreign direct investment, remittances and official development assistance (ODA) and some control variables i.e. domestic credit, life expectancy, gross fixed capital formation (GFCF), inflation and three institutional factors on economic growth in developing countries by adopting the panel data methodology. Then, the authors will discuss empirical tests to assess the econometric relevance of the model specification before presenting the analysis of the results and their interpretations that lead to economic policy implications. As part of this work, the authors have rolled panel data for developing countries at an annual frequency during the period from 1990 to 2016. In a first stage of empirical analysis, the authors will carry out a technical study of the heterogeneity test of the individual fixed effects of the countries. This kind of analysis makes it possible to identify the problems retained in the specific choice of econometric modeling to be undertaken in the specificities of the panel data.

The empirical results validate the hypotheses put forward and indicate the evidence of an ambiguous effect of financial flows on economic growth. The empirical findings from this analysis suggest the use of economic-type solutions to resolve some of the shortcomings encountered in terms of unexpected effects. Governments in these countries should improve the business environment by establishing a framework that further encourages domestic and foreign investment.

In this article, the authors adopt the panel data to study the links between financial flows and economic growth. The authors considered four groups of countries by income.

The purpose of this paper is to quantify several measures to examine the determinants of profitability for the listed Indian banks. The authors include both public sector (PSUs) and private sector’s banks in the study. The authors have taken all the banks that are registered on the Bombay stock exchange (BSE) in the sample. This paper also intends to identify the association between the net profit margin (PM) and return on assets (ROA) with the several other independent variables of the Indian banking sector including private banks and public banks over the past six years starting from April 1, 2012 to March 31, 2017. Therefore, a sample of 39 listed banking companies and total 195 balanced observations are selected for the analysis purpose.

The authors have used profitability as a dependent variable represented by net PM, ROA and several financial ratios as independent variables. Financial statement and income statement of all listed banks were obtained from BSE and particular company’s website. Panel data regression has been analyzed with both the descriptive research techniques, i.e., fixed effects and random effects. The authors also verified both panel techniques with Hausman’s specification test, which is a widely used procedure for selecting a panel effect. The authors applied PP – Fisher χ², PP – Choi Z-statistics and Hadri to testing whether the data set is free from unit root problem and data set is a stationary series.

Results imply that interest expended interest earned (IEIE) and credit deposit ratio (CRDR) reduced the profitability of private banks in India. IEIE, CRDR and quick ratio (QR) reduced the profitability of public banks in India, while cash deposit ratio (CDR) and Advances to Loan Funds (ALF) increased the effectiveness of public banks. Under the total banks IEIE, CRDR reduced the profitability, on the other side, CDR, ALF and Total Debt to Owners Fund (TDOF) increased the profitability of total banks in India. Under the dependency of ROA, CRDR and TDOF reduced the return of private banks in India, while CDR, ALF and QR enhanced the profitability of private banks.

No variables found significant under public banks while taking ROA as a dependent variable. Under the overall banking data, CRDR reduced the profitability. On the other side, capital adequacy ratio and ALF increased the profitability of total banks in India. The findings of this study will support policy creators, financial executives and investors in constructing investment decisions.

This paper aims to examine the effect of financial restatement on changing the auditor in the following years.

The study uses data of 105 companies (735 company-years) listed on the Tehran Stock Exchange collected during the period 2008-2014. Logistic regression is used to test the hypotheses.

The results of hypotheses present that restatement does not cause auditor changes and that as the severity of a restatement increases, the auditor change in the following year of restatement also does not increase. Restating companies having strong governance do not go for auditor changes as compared with other companies. In addition, in companies that are restating, non-big auditor changes are not more likely than a big auditor. Also, in companies restating simultaneous with a CEO turnover, there is no possibility of auditor change. Furthermore, multinomial logistic regression showed that the adjustments resulting from the correction of errors and changes in procedures and the amount of adjustments do not cause auditor change in the following year. So, the results have shown that the restatement is not an important factor in changing auditor the next year.

The current study analyses the impact of financial restatement on auditor changes in a deep manner in a developing country like Iran.

The purpose of this paper is to examine empirically the efficiency types of Islamic and conventional banks. It seeks to show whether the efficiency level of conventional and Islamic banks significantly differs from each other. In addition, it investigates the influential factors on each type of efficiency.

The paper utilises the data envelopment analysis in its windows version to estimate the efficiency scores reflecting the time variance and compares between banking models. The paper uses pure technical efficiency (TE) and scale efficiency to achieve the objective of the study. In addition, the panel data technique is adopted to assess the determinants of the efficiency of the banks econometrically.

The findings of panel regression initially indicate that the pure TE is higher for conventional banks compared to Islamic banks. However, the Islamic banks are more scale efficient than their conventional counterpart. Macro and micro indicators have different impacts on the both types of efficiency. However, the unique factors that show consistent influence on the efficiency types were loans/finance, non-interest income/finance/liquidity and GDP. Furthermore, the determinants are shaped differently for Islamic and conventional banks when the banking model is controlled for.

This paper examines the efficiency types using a unique window analysis approach to examine the types of efficiency with a longitudinal set of data from 1996 to 2011.

This study will examine the impact of cash dividends on the market value of banks listed in Middle East and North African (MENA) emerging countries during the period 2000–2015.

The current study adopts residual income approach based on Ohlson's (1995) valuation model. By testing different statistical techniques, fixed effect is applied on panel data for (144) banks listed on 11 MENA stock markets over the period 2000–2015. Furthermore, additional tests are applied to confirm the primary results.

The analysis reveals that current dividend payouts and dividend yield do not provide information relevant to the establishment of market values in MENA emerging markets; thus, they have no material impact on MENA banks' market values. This lack of current dividend payment effect is consistent with Miller and Modigliani (1961) dividend irrelevance assumption: there is no evidence of either an informational or real cash inflow effect of current dividend payments. The findings of this study can be attributed to the fact that MENA banks may be forced to place more emphasis on allocating money for investment instead of paying dividends given them they are subject to liquidity requirements for investment, expansion, general operations and compliance with regulations. Only after all these financial needs are covered can the remaining surplus be distributed as cash dividends. Therefore, cash dividends represent earnings residual rather than an active decision variable that impacts a firm's market value. This is consistent with the residual dividend hypothesis, which is the crux of Miller and Modigliani (1996) irrelevance theory of dividends.

The current study is restricted to a sample of one type of financial firms, banks, because of the problem of missing data and limited information related to other financial firms for the same period. Therefore, further research could be additional types of financial firms such as insurance firms that play a vital role in MENA emerging economies.

The results of this study have some important implications for banks' dividend policymakers. Dividend policymakers in MENA emerging markets seem to follow residual dividend policy, in which they distribute dividends according to what is left over after all acceptable investment opportunities have been undertaken. This makes for inconsistent and unstable dividend policy trends, making it difficult for investors to predict future dividend decisions. Further, this practice may deliver information to shareholders about a lack of positive future investment opportunities, and this may negatively affect the share value of banks.

This study is the first of its kind – up to the author's knowledge – that examines a large cross-country sample of MENA banks (144) to cover a long time period in the recent past, and, more importantly, after the banking sector in the region has experienced major transformations during last two decades. In addition, most of the MENA region countries included in this study, namely, banks, operate in tax-free environments (there are neither taxes on dividends nor on capital gains). This feature adds complexity to the ongoing dividend debate.

This paper aims to investigate simultaneously the causality and the dynamic links between exchange rates and stock market indices. It attempts to identify the short- and long-term effect of the US dollar on major stock market indices of Brazil, Russia, India, China and South-Africa (BRICS) nations.

This paper applies a new methodology combining the panel generalized method of moments model and the panel auto-regressive distributed lag (ARDL) method to investigate the existence of a causal short-/long-run relationships and dynamic dependence among all stock market returns and exchanges rates changes of BRICS countries.

Results show that exchange rate changes have a significant effect on the past and the current volatility of the BRICS stock indices. Besides, ARDL estimations reveal that exchange rate movements have a significant effect on short- and long-term stocks market indices of all BRICS countries

The findings have implications for policymakers and market participants who try to manage the exchange rate will have a different dose of intervention if they know that the effects of currency depreciation are different than appreciation. These results have important implications that investors should take into account in frequency-varying exchange rates and stock returns and regulators should consider developing sound policy measures to prevent financial risk.