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This paper aims to optimize the charging schedule for battery electric buses (BEBs) to minimize the charging cost considering the time-of-use electricity price.

The BEBs charging schedule optimization problem is formulated as a mixed-integer linear programming model. The objective is to minimize the total charging cost of the BEB fleet. The charge decision of each BEB at the end of each trip is to be determined. Two types of constraints are adopted to ensure that the charging schedule meets the operational requirements of the BEB fleet and that the number of charging piles can meet the demand of the charging schedule.

This paper conducts numerical cases to validate the effect of the proposed model based on the actual timetable and charging data of a bus line. The results show that the total charge cost with the optimized charging schedule is 15.56% lower than the actual total charge cost under given conditions. The results also suggest that increasing the number of charging piles can reduce the charging cost to some extent, which can provide a reference for planning the number of charging piles.

Considering time-of-use electricity price in the BEBs charging schedule will not only reduce the operation cost of electric transit but also make the best use of electricity resources.

The European Parliament and Commission are considering introducing a green supporting factor (GSF) or brown penalty (BP) for capital reserve requirements. This paper aims to estimate the potential impact such a policy intervention may have on both capital reserves of European banks and the cost and availability of capital to “green” and “brown” investments.

The paper draws on the existing empirical and theoretical literature on the impacts of changes to capital reserve requirements on the real economy. It applies these estimates on the particular policy intervention currently being discussed at EU level to estimate the potential range of impacts on the cost of capital – measured in basis points – and the availability of capital – measured in per cent changes to lending.

A GSF would have a limited effect on overall capital requirements of banks compared to a BP – given the larger universe of assets on which such a penalty would be applied. The estimated effect is a reduction in capital requirements associated with a GSF of around €3-4bn based on baseline “green” definitions. In terms of cost of capital, the paper estimates a reduction of 5 to 26 basis points for green projects (with inverse expected effects for a BP). In terms of availability of capital, analysing a BP suggests a potential reduction in lending to brown assets of up to 8 per cent.

The paper provides direct evidence, with the first quantitative analysis of the potential impact of the current policy proposition discussed at EU-level.

This research aims to evaluate the accuracy of several Value-at-Risk (VaR) approaches for determining the Minimum Capital Requirement (MCR) for Islamic stock markets during the pandemic health crisis.

This research evaluates the performance of numerous VaR models for computing the MCR for market risk in compliance with the Basel II and Basel II.5 guidelines for ten Islamic indices. Five models were applied—namely the RiskMetrics, Generalized Autoregressive Conditional Heteroskedasticity, denoted (GARCH), fractional integrated GARCH, denoted (FIGARCH), and SPLINE-GARCH approaches—under three innovations (normal (N), Student (St) and skewed-Student (Sk-t) and the extreme value theory (EVT).

The main findings of this empirical study reveal that (1) extreme value theory performs better for most indices during the market crisis and (2) VaR models under a normal distribution provide quite poor performance than models with fat-tailed innovations in terms of risk estimation.

Since the world is now undergoing the third wave of the COVID-19 pandemic, this study will not be able to assess performance of VaR models during the fourth wave of COVID-19.

The results suggest that the Islamic Financial Services Board (IFSB) should enhance market discipline mechanisms, while central banks and national authorities should harmonize their regulatory frameworks in line with Basel/IFSB reform agenda.

Previous studies focused on evaluating market risk models using non-Islamic indexes. However, this research uses the Islamic indexes to analyze the VaR forecasting models. Besides, they tested the accuracy of VaR models based on traditional GARCH models, whereas the authors introduce the Spline GARCH developed by Engle and Rangel (2008). Finally, most studies have focus on the period of 2007–2008 financial crisis, while the authors investigate the issue of market risk quantification for several Islamic market equity during the sanitary crisis of COVID-19.

Most of the major Islamic countries’ stock exchanges have not been able to perform at the same pace with the major emerging countries’ stock exchanges since the mid of 1990s. The purpose of this paper is to examine the implications of stock market liberalization on cost of capital as one of the crucial driver to stock market development and physical investment growth in emerging Islamic countries.

This study employs static panel data techniques on the sample of seven emerging Islamic countries over the years 1989-2008.

The findings of this study suggest that stock market liberalization significantly reduces cost of capital in the stock markets of sample Islamic countries, which carries policy-oriented implications. Reduction in the cost of capital increases the number of exchange-traded companies, profitability of projects and aggregate investment level; therefore, the study findings are highly concerned by the economic policymakers, corporations and investors alike.

In the literature, different proxies are employed to measure stock market liberalization and cost of capital as well. Due to data limitations, this study could not employ different proxies for both, especially for stock market liberalization, for robustness purpose. That limitation further restricted the coverage of Islamic stock markets and time period. Therefore, generalization of the study results for overall Islamic stock markets can be slightly drawn.

The paper provides further understanding regarding the effects of SML on cost of capital, thereby indirectly on the stock market development, in the context of EIC.

Customers of Islamic banking industry continue to be skeptical on Sharīʿah compliance of Islamic banks despite receiving fatwa from the competent authorities. The purpose of this paper is to quantify the Sharīʿah risk taken by Islamic banks, so that customers are better informed on the level of Sharīʿah compliance that will help in removing the persistent level of skepticism toward Sharīʿah compliance.

This research has used the scorecard based modeling approach to build the Sharīʿah risk rating model, which consists of 14 factors that capture Sharīʿah risk and are grouped in 5 major areas revolving around regulatory support, quality of Sharīʿah supervision, business structure, product mix and treatment of capital adequacy ratio. The score calculated by applying the model is grouped into 4 tiers reflecting the level Sharīʿah compliance at bank as non-compliant, weak compliance, satisfactory compliance and high level of Sharīʿah compliance. Three case studies were conducted by applying the model to Islamic banks from Malaysia, Pakistan and Saudi Arabia.

The final Sharīʿah risk scores calculated by the model clearly differentiate the 3 banks on basis of their Sharīʿah risk. The underlying scores also highlighted the areas where banks need to improve to reduce their Sharīʿah risk.

This model can be applied by customers of Islamic banks who are interested in understanding Sharīʿah-related aspects of Islamic banking industry. This model can be applied on standalone basis or as an extension to the conventional counter party risk rating models. This model can benefit management of Islamic banks toward allocation of capital against Sharīʿah risk under Basel III, and regulators can apply the model to measure industry wide risk of Sharīʿah non-compliance.