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This study aims to analyze the effect of cryptocurrency capitalization market development on bank deposits variability in the United Arab Emirates (UAE) spanning the period 2005M1–2020M4 using the novel nonlinear autoregressive distributive lag (NARDL).

The study employs the NARDL recently developed by Shin et al. (2014) to estimate the long and short-run relationships between the variables rather than the widely known ARDL (Pesaran et al., 2001), which suffers from a complex structure in the estimation equation that usually includes lags and differences in both short and long terms. The implementation of NARDL required several proceedings after plotting the descriptive data, commencing with unit root tests, selection of lag length, estimating the long-and-short variables coefficients, heteroscedasticity test and Wald test for symmetries.

The long-run estimations of the positive and negative asymmetric coefficients indicate that cryptocurrencies capitalization has a negative impact on bank deposits in the UAE. Further, the short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decrease bank deposits.

The study has applied to the UAE spanning the period 2005M1–2020M4 using the NARDL.

The short-run estimations coefficients exhibit that both significant positive and negative partial sum squares of cryptocurrencies decreases bank deposits, which means that the increase in the magnitude of cryptocurrencies capitalization stimulates depositors and speculators to adjust their portfolios towards contracting their deposits in banks to invest partially in cryptocurrencies, on the other hand, the decline in cryptocurrencies capitalization process spur depositors and speculators to reduce their deposits for purchasing cryptocurrencies at lower prices.

The study infers that individuals and businesses are cautious when investing in cryptocurrencies, and they need more certainty and trust to include these types of assets in their portfolios. The fluctuation in cryptocurrencies capitalization prompts speculators to change their deposits according to the cryptocurrencies' prices.

This study explores the short-and long-run asymmetric impacts of cryptocurrencies capitalization development on bank deposits volatility in the UAE, based on a NARDL, for providing a manifest depiction of whether the cryptocurrencies industry might be a threat to conventional banking system performance in the potential future.

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

Commercial banks face several risks, including credit, liquidity, operational and disruptive risks. In addition to these risks that are challenging for banks to control and manage, crises and disasters can exert substantially more destructive shocks. These shocks can exacerbate internal risks and cause severe damage to the bank's performance, leading banks to bankruptcy and closure. This study aims to facilitate achieving resilient banking policies through a model-based assessment of business continuity management (BCM) policies.

By applying a system dynamics (SD) methodology, a systemic model that includes a causal structure of the banking business is presented. To build a simulation model, data are collected from a commercial bank in Iran. By presenting the simulation model of the bank's business, the consequences of some given crises on the bank's performance are tested, and the effectiveness of risk and crisis management policies is evaluated. Vensim Personal Learning Edition (PLE) software is used to construct the simulation model.

Results indicate that the current BCM policies do not show appropriate resilience in the face of various crises. Commercial banks cannot create sustainable value for the banks' shareholders despite the possibility of profitability, as the shareholders lack adequate resilience and soundness. These commercial banks do not have the appropriate resilience for the next pandemic after coronavirus disease 2019 (COVID-19). Moreover, the robustness of the current banking business model is very fragile for the banking run crisis.

A forward-looking view of resilient banking can be obtained by combining liquidity coverage, stable funding, capital adequacy and insights from stress tests. Resilient banking requires a balanced combination of robustness, soundness and profitability.

The present study is a combination of bank business management, risk and resilience management and SD simulation. This approach can analyze and simulate the dynamics of bank resilience. Additionally, present of a decision support system (DSS) to analyze and simulate the outcomes of different crisis management policies and solutions is an innovative approach to developing effective and resilient banking policies.

This paper aims to determine causal relationships between the level of productive credit, real deposits and money demand – all of them in real terms – and Gross National Product between 2006 and 2020.

The vector autoregressive technique (VAR) was used, where data from real macroeconomic aggregates published by the Central Bank of Ecuador (BCE) are correlated, such as productive credit, gross domestic product (GDP) per capita, deposits and money demand.

The results indicate that there is no causal relationship, in the Granger sense, between GDP and financial activity, but there is between the growth rate of real money demand per capita and the growth rate of total real deposits per capita.

The study shows that bank credit mainly finances the operations of current assets and/or liabilities. In addition, economic agents use the banking system mainly to carry out transactional and precautionary activities.

This study empirically demonstrates a contradiction between pillar 3 of Basel norms III and the designation of Systemically Important Banks (SIBs), also known as Too Big to Fail (TBTF). The objective of this study is threefold, which has been approached in a phased manner. The first is to determine the systemic importance of the banks under study; second, to examine if market discipline exists at different levels of systemic importance of banks and lastly, to examine if the strength of market discipline varies at different levels of systemic importance.

This study is based on all the public and private sector banks operating in the Indian banking sector. The Gaussian Mixture Model algorithm has been utilized to classify banks into distinct levels of systemic importance. Thereafter, market discipline has been observed by analyzing depositors' sentiments toward banks' risk (CAMEL indicators). The analysis has been performed by employing the system Generalized Method of Moments (GMM) to estimate models with different dependent variables.

The findings affirm the existence of market discipline across all levels of systemic importance. However, the strength of market discipline varies with the systemic importance of the banks, with weak market discipline being a negative externality of the SIBs designation.

By employing the Gaussian Mixture Model algorithm to develop a framework for categorizing banks on the basis of their systemic importance, this study is the first to go beyond the conventional method as outlined by the Reserve Bank of India (RBI).

This study aims to review to what extent Islamic banks carry conventional monetary policy impulses. Hence, the authors focus to review on the presence or absence of an Islamic financing channel.

A systematic approach to the literature review was adopted. The search criterion is confined to empirical studies that examined the transmission of interest-based monetary policy through Islamic banks’ financing, particularly empirical studies that check the existence of an Islamic bank financing channel of conventional monetary policy. By adopting a systematic approach, over 40 empirical papers published in Scopus and Google Scholar were selected for review and analysis to suggest prospects for future analysis in this field.

The existence of Islamic banks may raise concerns for local central banks, particularly in terms of implementing monetary policies that rely on interest rates. Indeed, the specific nature of the business model of Islamic banks based on the sharing of losses and profits as an alternative to interest rate–based remuneration suggests a priori the non-transmission of monetary policy through these free-interest banks. Despite this, the actual asset structure of Islamic banks may facilitate the transmission of monetary impulses to the economy. Currently, there are limited and inconclusive empirical studies on how Islamic bank financing contributes to the transmission of monetary policy. Additional research is required to fully comprehend the response of Islamic banks to fluctuations in monetary policy interest rates, as well as the factors that impact their reactions.

This literature review is incredibly important as it thoroughly examines a critical issue from both academic and practical perspectives. Analyzing how monetary policy actions can be transmitted through Islamic bank financing is an important task that can provide insights for future research. A straightforward response to this inquiry could assist central banks in formulating effective monetary policy.

This study aims to examine the dynamics of the market development of Islamic banking in Pakistan. This study investigates how shocks to the economy in the form of changes in benchmark rate and exchange rate and internal factors such as efficiency, profitability and asset quality affect the development of Islamic banking. The study also evaluates the impact of Islamic banking on the real economy in the macro perspective and society at large in terms of inclusiveness, competitiveness and fairness.

Autoregressive distributed lagged model method is used for analysing the short-run and long-run determinants of market development of Islamic banking and the economic impact of Islamic banking on the real economy.

Profitability and exchange rate have a positive effect on market development of Islamic banking while higher inefficiency and interbank rate have a negative effect. On the other hand, financing intensity and profitability in Islamic banking positively affect the large-scale manufacturing sector.

Stable profits, high asset quality, efficiency and rising import demand with low policy rate environment complement Islamic banking growth. Moreover, the economic assessment shows that Islamic banks have been able to achieve the financial inclusion of those who want to avoid Riba, but they need concerted efforts to improve competitiveness and distinction with regard to distributional impact.

To the best of the authors’ knowledge, this is the first study in Pakistan to evaluate determinants of market development of Islamic banking taking 16-year quarterly data and assessing the economic effects of Islamic banking on inclusiveness, competitiveness and fairness.

Sudden and unannounced policy changes by the government that provide banks with windfall deposits creates a challenge in terms of resource deployment. In the process, there is an impact on their risk and returns. Using data on domestic Indian commercial banks, this study aims to examine the impact of such an announcement – the 2016 demonetisation episode – on bank behaviour.

Using data on domestic Indian commercial banks during 2010–2020, the paper investigates the effect of a sudden and unannounced policy change on their risk and returns. Using the demonetisation undertaken in November 2016 as a natural experiment, the paper applies the difference-in-differences methodology to tease out the causal impact.

The findings reveal a decline in risk and an increase in returns of state-owned banks, consistent with a flight-to-safety. The response differed in terms of market and accounting measures and across state-owned banks with differing levels of capital and asset quality.

Although several aspects of the demonetisation episode have been well analysed, its impact on banks – the main conduits of the exercise – and in particular on their risk and returns, is an unaddressed area of research. Viewed from this standpoint, this is one of the early studies to undertake a comprehensive empirical analysis on this aspect.

This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

This paper seeks to examine the effect of monetary policy rate (MPR) on the lending rates of commercial banks in Ghana.

The paper employed the autoregressive distributed lag (ARDL) model as well as the non-linear autoregressive distributed lag (NARDL) model econometric techniques on a quarterly time series data from 2002 to 2018.

The ARDL results revealed that, MPR has a positive and significant effect on lending rate in the long and short run. Although there exists a direct relationship between MPR and lending rate, from the NARDL revealed an asymmetric effect of MPR on lending rate to the effect that, lending rate in Ghana responds more to positive shock (a rise in MPR) compared to a negative shock (a decrease in MPR) both in the long and short run.

The paper contributes to policy and literature in Ghana by providing empirical evidence on the asymmetric effect that MPR has on lending rates in Ghana. The paper recommends among others, the establishment of a rating system of banks according to their monetary policy compliance, where highly rated banks could have for instance a reduction on borrowed reserves from the central bank.