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The purpose of this study is to estimate the convergence order of the Aumann–Serrano Riskiness Index.

This study uses the equivalent relation between the Aumann–Serrano Riskiness Index and the moment generating function and aggregately compares between each two statistical moments for statistical significance. Thus, this study enables to find the convergence order of the index to its stable value.

This study finds that the first-best estimation of the Aumann–Serrano Riskiness Index is reached in no less than its seventh statistical moment. However, this study also finds that its second-best approximation could be achieved with its second statistical moment.

The implications of this research support the standard deviation as a statistically sufficient approximation of Aumann–Serrano Riskiness Index, thus strengthening the CAPM methodology for asset pricing in the financial markets.

This research sheds a new light, both in theory and in practice, on understanding of the risk’s structure, as it may improve accuracy of asset pricing.

The purpose of this paper is to increase the accuracy of the efficient portfolios frontier and the capital market line using the Riskiness Index.

This paper will develop the mean-riskiness model for portfolio selection using the Riskiness Index.

This paper’s main result is establishing a mean-riskiness efficient set of portfolios. In addition, the paper presents two applications for the mean-riskiness portfolio management method: one that is based on the multi-normal distribution (which is identical to the MV model optimal portfolio) and one that is based on the multi-normal inverse Gaussian distribution (which increases the portfolio’s accuracy, as it includes the a-symmetry and tail-heaviness features in addition to the scale and diversification features of the MV model).

The Riskiness Index is not a coherent measurement of financial risk, and the mean-riskiness model application is based on a high-order approximation to the portfolio’s rate of return distribution.

The mean-riskiness model increases portfolio management accuracy using the Riskiness Index. As the approximation order increases, the portfolio’s accuracy increases as well. This result can lead to a more efficient asset allocation in the capital markets.

The literature has demonstrated that lump-sum (LS) outperforms dollar-cost averaging (DCA) in uptrend markets while DCA outperforms LS only when the asset price is mean-reverted or downtrend. To bridge the gap in the literature, this study aims to use both Sharpe ratio (SR) and economic performance measure (EPM) to compare the performance of DCA and LS under both accumulative and disaccumulative approaches when the asset price is simulated to be uptrend.

This study uses both disaccumulative and accumulative approaches to compare DCA with LS and uses both SR and EPM to evaluate their performance when the asset price is simulated to be uptrend. Instead of using the annualized returns that are commonly used by other DCA studies, we compute the holding-period returns in the comparison in this paper.

The simulation shows that no matter which approach is used, DCA outperforms LS in nearly all the cases in the less uptrend markets while DCA still performs better than LS in many cases of the uptrend markets, especially when the market is more volatile and investment horizon is long, regardless which approach the authors used. The authors also find more evidence supporting DCA over LS by using EPM, which is more suitable in the analysis because the returns generated by DCA are positive skewed and flat-tailed that are ignored when SR is used.

The authors conclude that DCA is a better trading strategy than LS for investment even in the uptrend market, especially on high risky assets.

Investors could consider choosing DCA instead of LS as their trading strategy, especially when they prefer long term investment and investing in high-risk assets.

Fund managers could consider recommending DCA to their customers, especially when they prefer long term investment and investing in high-risk assets.

This is the own study and, as far as the authors know, this is the first study in the literature uses both SR and EPM to compare the performance of DCA and LS under both accumulative and disaccumulative approaches when the asset price is simulated to be uptrend.

This paper aims to give a brief review on behavioral economics and behavioral finance and discusses some of the previous research on agents' utility functions, applicable risk measures, diversification strategies and portfolio optimization.

The authors also cover related disciplines such as trading rules, contagion and various econometric aspects.

While scholars could first develop theoretical models in behavioral economics and behavioral finance, they subsequently may develop corresponding statistical and econometric models, this finally includes simulation studies to examine whether the estimators or statistics have good power and size. This all helps us to better understand financial and economic decision-making from a descriptive standpoint.

The research paper is original.

This paper aims to explain the weaknesses and inconsistencies inherent in the Dodd-Frank Act of 2010 (USA).

The approach is entirely theoretical and multi-disciplinary (and relies on some third-party empirical research), and it consists of a literature review, critique and the development of theories which are applicable across countries.

The Dodd-Frank Act is inefficient and inadequate as a response to the global financial crisis. The Dodd-Frank Act has not resulted in significant economic growth and has increased transaction costs and compliance costs for both government agencies and financial services companies.

The author developed the theories introduced in the paper.

The purpose of this paper is to revise, update and extend the economic vulnerability and economic resilience indices, where economic vulnerability is associated with inherent exposure to external shocks and economic resilience with policies that enable a country to minimize or withstand the negative effects of such shocks. This study also proposes a revised vulnerability/resilience framework to assess the risk of a country being harmed by external economic shocks.

The methodology used in the study involves defining economic vulnerability in terms of inherent features of an economy and defining economic resilience in terms of policy-induced changes, and then devising measureable indices to measure such vulnerability and resilience across countries. The exercise required the examination of various global indices to assess their suitability, in terms of relevance and country coverage, for measuring the vulnerability index and the resilience index and the components of the two indices.

The main finding of the study is that a number highly vulnerable states, including economically successful small island economies, emerged with high resilience scores, suggesting that they adopt policies that enable them to withstand the harmful effects of external shocks. This possibly explains why these states register relatively high GDP per capita, in spite of their high exposure to shocks. On the other hand, a number of countries, mostly large and poor developing countries, that are not highly exposed to external shocks due to their limited dependence on external trade, emerged with a low degree of policy-induced economic resilience.

The study utilized global indicators which sometimes had missing data and these had to be filled in using approximations based on assumptions, and alternative assumption could have produced a different approximations. In addition the classification of countries in terms of the vulnerability and resilience nexus depended highly on many underpinning assumptions, including the definitions and the measurement of the components, the weighting schemes and the thresholds used. It is likely that alternative assumptions would yield alternative classifications.

An important practical implication of this study is that highly economically vulnerable states can reduce the harmful effects of external economic shocks if they adopt policies that lead to resilience building. On the other hand, countries that are not highly exposed to external shocks, can render themselves economically unstable due to their weak economic, social and environmental governance.

This study considers social development and cohesion as one of the pillars of resilience building. The implication of this approach is that social governance, leading to improvements in the education and health of the population could reduce the harm arising from a country’s exposure to external shocks. This is because social governance affects the extent to which relations within a society are properly developed, enabling an effective functioning of the economic apparatus without the hindrance of civil unrest.

This study has extended previous work on the vulnerability and resilience framework, to include almost all countries of the world, using updated data, and has revised the resilience index to include environmental governance. It has also redefined market flexibility to allow for the downsides of excessive financial riskiness. The revision of vulnerability and resilience indices in the light of new data and their interaction showed more convincingly that economies that are highly economically vulnerable could still register economic success as a result of resilience-conducive policies associated with good economic, political, social and environmental governance.

The purpose of this paper is to investigate how bank-specific factors affect the riskiness of conventional and Islamic banks in response to shocks in major financial indices as market conditions change.

The authors use a multivariate quantile model using daily equity returns data to analyze financial risk spillovers in the values at risk that may occur between major financial indices and the equity prices of conventional and Islamic banks worldwide. Then, using both quantile and quantile-on-quantile models, the authors examine the effects of bank-specific variables such as leverage ratio, bank size, return on equity and capital adequacy ratio on the initial impact of shocks in major global financial indices on bank equity price returns at different quantiles of shocks and bank-specific variables.

The findings reveal that major financial indices can predict bank stock returns. Moreover, the authors find that the effect of bank-specific factors on the riskiness of banks is heterogeneous in that it depends on the bank type (Islamic vs conventional), the level of banking variable (high vs low) and, more importantly, market conditions.

To the best of the authors’ knowledge, this is the first study that compares the dual banking system with stock market performance while considering bank-specific variables as market conditions change. The results of this study reveal that the effect of bank-specific variables on bank performance varies according to different quantiles of shocks and bank-specific variables. Islamic banks may echo or differ from conventional banks depending on the specific factor under investigation.

Sees the objective of teaching financial management to be to help managers and potential managers to make sensible investment and financing decisions. Acknowledges that financial theory teaches that investment and financing decisions should be based on cash flow and risk. Provides information on payback period; return on capital employed, earnings per share effect, working capital, profit planning, standard costing, financial statement planning and ratio analysis. Seeks to combine the practical rules of thumb of the traditionalists with the ideas of the financial theorists to form a balanced approach to practical financial management for MBA students, financial managers and undergraduates.

The purpose of the study is to adopt Morlet’s wavelet method to examine the differences in the level of volatility (i.e. riskiness) between the conventional and Shari’ah indexes during the COVID-19 pandemic (February 4 to June 19, 2020) on selected Association of South East Asian Nation (ASEAN) and Gulf Cooperation Council (GCC) countries. As a comparison, the equivalent time period of relative tranquillity is used; February 4 to June 19, 2019.

Morlet’s wavelet method is used in analyzing the volatility levels for both the conventional and Shari’ah indexes before and during the COVID-19 pandemic for the selected ASEAN and GCC countries.

This study has several findings; first, the markets in the ASEAN region appear to be more volatile during the pandemic than in the GCC region. Second, most of the Shari’ah indexes were more volatile during the COVID-19 pandemic than their conventional counterparts. Nevertheless, the GCC index pairs appear to show more similarities between both the Shari’ah and conventional index.

The findings from this study indicate that investors, government, regulators and all other stakeholders should stay vigilant during a pandemic or health threat period as it has become a pertinent source of volatility spillovers. As such, investors should devise optimal asset allocation strategies, portfolio diversification and portfolio rebalancing measures, taking into consideration not only financial adversity but also public health gravity as a potential source of turbulent markets.

This study uses the wavelet method to examine the volatility level of both the Shari’ah and conventional indexes during the COVID-19 pandemic and its equivalent time frame in 2019. It has further added to the Islamic literature by comparing the volatility between selected ASEAN and GCC countries. The wavelet method is most appropriate for short-duration studies as it captures both the time and frequency domains of the time-series behavior.

The purpose of this paper is to explore the determinants of three different types of bank liquidity: funding liquidity, liquidity creation, and stock liquidity in emerging markets.

It uses an extensive set of data from all the listed banks of Brazil, Russia, India, China, and South Africa, collectively known as the BRICS countries, spanning the period 2002-2014. Multiple linear regression has been used to estimate the coefficients of the determinants.

In case of emerging markets, bank size is not a determinant of different types of liquidity, except funding liquidity. Besides, the recent financial crisis had an impact on funding liquidity as well as “cat nonfat” measure of liquidity creation but it did not affect “cat fat” measure and stock liquidity. The variation in funding liquidity is also explained by the profitability and the riskiness of the bank. Effective interest rate, national savings rate, and inflation rate are also the determinants of funding liquidity. Bank-specific determinants of liquidity creation include bank leverage and profitability, and macroeconomic determinants include stock market index, effective interest rate, and unemployment rate. The variation in stock liquidity of the bank is explained by profitability and price of stocks, trading volume, volatility of stock returns, and percentage change in real gross domestic product. Neither market capitalization nor stock market index is the determinant of stock liquidity of the banks.

This study uses the data from publically listed banks only.

The findings of this study may be used by the policy makers and bank managers in the emerging markets to design better policies and to strengthen the banking system to avoid financial turmoil in future.

Most of the existing studies focus on bank liquidity in developed countries and studies aiming on emerging countries are rare. The existing studies focus more on funding liquidity and liquidity creation but to the best of the authors’ knowledge, none of the studies analyze the determinants of banks’ stock liquidity. So, this study bridges the above mentioned gaps by focusing on bank liquidity in emerging markets, and exploring the determinants of the stock liquidity of the banks.