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This paper aims to investigate the financial uncertainty vary according to different financial assets type: conventional and Islamic.

Common factors are related to risk or known information. For this, the authors use general dynamic factor model to extract common variation between both types of indexes. Then they calculate stochastic volatility for each idiosyncratic component. They also carry out the study on three different family indexes respectively, Dow Jones, S&P and MSCI indexes, for the period going from January 1, 2008 to June 30, 2018. Through a comparison analysis with uncertainty index designed for conventional assets, the authors examine the similarity between the two indexes via mean, median and variance tests. They decrypt the interrelation between them by using OLS linear regression, vector autoregressive model.

The findings show that Islamic assets uncertainty is different from conventional uncertainty level. This difference can be due to the Shariah screening and the prohibition of gharar. The main findings suggest that Islamic financial uncertainty is lower than conventional one. The OLS results prove that conventional financial uncertainties have no impact on their Islamic counterparts. In addition, Islamic financial uncertainty appears to have no significant influence on conventional one exception for Dow Jones pair. Overall, the findings support the decoupling hypothesis in term of uncertainty only for SP and MSCI indexes.

Risk averse investors can find their claim in Shariah-compliant assets, as it offers a low level of financial uncertainty. A portfolio manager may benefit from the long run non-association in uncertainty between Islamic and conventional assets especially in time of crisis.

In this work, the authors measured financial uncertainty differently and take into account the specific features of each index type to improve the results quality.

This study aims to analyze the imbalances in the public finance structure of Pakistan’s economy and highlight the need for comprehensive reforms. Specifically, it aims to contribute to the empirical literature by analyzing the relationship between fiscal vulnerability, financial stress and macroeconomic policies in Pakistan’s economy between 1971 and 2020.

The study develops an index of fiscal vulnerability, an index of financial stress and an index of macroeconomic policies. The fiscal vulnerability index is based on the patterns of fiscal indicators resulting from past trends of the selected variables in Pakistan’s economy. The financial stress in Pakistan is caused from the financial disorders that are acknowledged in the composite index, which is based on variables with the potential to indicate periods of stress stemming from the foreign exchange market, the securities market and the monetary policy components. The macroeconomic policies index is developed to analyze the mechanism through which fiscal vulnerability and financial stress have influenced macroeconomic policies in Pakistan. The causal association between fiscal vulnerability, financial stress and macroeconomic policies is analyzed using the auto-regressive distributive lags approach.

There exists a long-run relationship between the three indices, and a bi-directional causality between fiscal vulnerability and macroeconomic policies.

This study contributes to the development of a fiscal monitoring mechanism, which has the basic purpose of analyzing the refinancing risk of public liabilities. Moreover, it focuses on fiscal vulnerability from a macroeconomic perspective. The study tries to develop a framework to assess fiscal vulnerability in light of “The Risk Octagon” theory, which focuses on three risk components: fiscal variables, macroeconomic-disruption-associated shocks and non-fiscal country-specific variables. The initial contribution of this work to the literature is to develop a framework (a fiscal vulnerability index, financial stress index and macroeconomic policies index) for effective and result-oriented macro-fiscal surveillance. Moreover, empirical literature emphasized and advised developing countries to develop their own capacity mechanisms to assess their fiscal vulnerability in light of the IMF guidelines regarding vulnerability assessments. This study thus attempts to fulfill the said gap identified in literature.

This paper aims to survey the screening practices and regulatory arrangements that can be gleaned from the experience of Islamic financial indices on international stock markets. Such indices can be regarded as experiments in the demarcation of “pockets” of Sharī‘ah-compliant securities exchange, in the context of non-Sharī‘ah-compliant stock markets. They offer valuable regulatory precedent, with a view to the development of a transnational domain of Islamic financial transactions.

The paper leverages the experience of Islamic financial indices for charting the fault lines between the foundational principles of Islamic finance, and those of interest-based investment commonly accepted on international financial markets. It subsequently reviews the most salient regulatory arrangements in place for discriminating between permissible and forbidden securities and modes of trading, as implemented on Islamic financial indices. These include selection criteria for index inclusion, and Sharī‘ah committees with ex ante and ex post supervisory duties.

The paper makes a case for viewing Islamic finance indices on international capital markets as capacity-building experiments for the regulation of transnational Islamic financial flows.

The study rejuvenates the pragmatic approach towards the development of Islamic capital markets, by suggesting that incremental organisational innovations, as developed in connection with Islamic financial indices, can build institutional capacity towards an economy that abides by Islamic values.

The purpose of this study is to develop an index for financial constraints, specifically for restaurant firms, and to further validate the developed financial constraint index.

This study used logistic regression with a composite criterion based on the dividend payout ratio, KZ index and Cleary index to estimate restaurant firms’ financial constraints. Then, a fixed-effects regression was used to verify the validity of the measurement of restaurant firms’ financial constraints.

A restaurant firm’s operating profit, financial leverage, asset tangibility, sale of fixed assets and percentage change in number of employees are critical indicators for identifying financial constraints. The results indicated that in cases with positive operating cash flows, the effect of operating cash flow on capital investments continuously decreased as restaurant firms’ financial constraints increased.

This study is unique in that the specific financial and operational characteristics of restaurant firms were included in the model to determine financial constraint indicators, such as sale of fixed assets and percentage change in number of employees.

This study seeks to build a financial uncertainty index for Saudi Arabia. This index serves as a leading indicator of Saudi economic activity and helps to describe economic fluctuations and forecast economic trends.

This study adopts an extension of the Jurado et al. (2015) procedure by combining financial uncertainty factors with their net spillover effects on GDP and inflation to construct an aggregate financial uncertainty index. The authors consider 13 monthly financial variables for Saudi Arabia from January 2010 to June 2021.

The empirical results show that the constructed financial uncertainty estimates are good leading indicators of economic activity. The robustness analysis suggests that the authors’ proposed financial uncertainty estimators outperform the alternative estimates used by other existing approaches to estimate the financial conditions index.

To the best of the authors’ knowledge, this is the first attempt at constructing a financial uncertainty index for Saudi Arabia. This study extends the empirical literature, from which the authors propose a novel conceptual framework for building a financial uncertainty index by combining the approach of Jurado et al. (2015) and the time-varying connectedness network approach proposed by Antonakakis et al. (2020)

The purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market.

This paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples.

The empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility.

This paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets.

This paper aims to analyze the volatility transmission between an energy stock index and a financial stock index in emerging markets during recent high instability periods. The study considers the impact of both the period under analysis and the data frequency on the direction and intensity of the contagion, as well as the effect of the potential spillovers on the risk measures. These questions still lack definitive answers and have become more relevant in a context of financially unsettling events such as COVID-19 crises.

This study employs an extension of the dynamic conditional correlation (DCC) model that allows for the time-varying dependence relationship between the variables. This dependence is analyzed at daily, weekly and monthly basis using data from the Bloomberg platform on energy and stock market indices for emerging markets between 2001 and 2021.

The results for a sample spanning from 2001 to mid-2021 show bidirectional volatility transmission on a daily basis, whereas only evidence of volatility transmission from the financial to the energy exists for weekly and monthly frequencies. However, considering different subsamples of daily data, the authors only find volatility transmission from financial (energy) index to the energy (financial) during the Great Recession (COVID-19) as a consequence of the different source of the shock and transmission channels.

This study reveals that volatility transmission between energy and stocks in emerging markets has changed and presents a unidirectional pattern from energy to financial markets during the COVID-19 period in contrast to calm and the sub-prime crisis intervals. These results differ from previous studies, focused on global markets, that show bidirectional spillovers during this period.

With the globalization and liberalization in terms of increasing financial flows across the countries, the policy makers around the world are not independent in the context of monetary and fiscal policy initiatives. In this regard, this paper aims to attempt to quantify and capture long run, short run as well as time-varying linkages among the two financial stress indices, namely, Kansas City Financial Stress Index (KCFSI) and Indian Financial Stress Index (IFSI) across the monthly period (2004 to 2014).

Owing to the non-existence of a standardized financial stress index with regards to the Indian financial system, the study has developed an index/stress indicator using principal component analysis. Furthermore, to comprehend the linkages, the study uses bivariate Johansen cointegration model, vector error correction model, impulse response functions (IRF), variance decomposition analysis (VDA), Toda-Yamamoto’s Granger causality test and, finally, bivariate generalized autoregressive conditional heteroskedastic (BVGARCH) (1,1) model under constant conditional correlation (CCC) framework.

The results report a stochastic trend among the two indices wherein the US financial system acts as a source of a shock causing disequilibrium in the long run co-movement. About 40 per cent of the adjustments take place in one month and rest in the coming months. Both the IRF and VDA report a greater degree impact of the US financial stress on the Indian financial system. Moreover, there is a uni-directional short run causality running from the stress in the US financial system to the Indian financial stress. Furthermore, the co-movement between the US and Indian financial stress reached to its maximum significant level during the sub-prime crisis even confirmed by the Markov switching model results.

Overall, the results provide an insight to the financial market investors both domestic as well as international in their act of risk management. The financial stress prevailing in an economy further has an impact on different economic factors like foreign exchange rates, interest rates, yield curves, equity market returns and volatility. So, the empirical results support strong implications for the Indian policy makers as well as investors in the Indian financial markets.

The present study contributes to the literature in three senses. First, the study considers indices reflecting financial stress in the Indian as well as US financial system. Second, the study captures long run as well as short run linkages among the financial stress indices relating to a developed and an emerging market. Finally, the study uses CCC-BVGARCH (1,1) model to account for the time-varying co-movement among the financial stress indices. This helps in comprehending time-varying nature of the co-movement of the stress in the financial system prevalent in the respective markets.

The objective of this work is to analyse worldwide trends in financial supervision architectures. The focus is on the key issue in the debate – the single supervisor versus multiauthority model – in order to build up indexes of supervision unification, essential to perform studies on the causes and effects of various supervisory regimes. First, the paper introduces a Financial Authorities’ Concentration (FAC) Index. A comparative analysis of 69 countries confirmed that an increase in the degree of concentration of supervisory powers is evident in the developed countries, and particularly in the European Union. Secondly, the paper considers the nature of the institutions to which control responsibilities are entrusted. In particular, the role the central bank plays in the various national institutional settings is examined. An index of the central bank’s involvement in financial supervision is introduced, the Central Bank as Financial Authority (CBFA) Index. Each national institutional structure can be identified with the two above characteristics. Two models are the most frequent: (a) countries with a high level of unification of powers and weak central bank involvement (single financial authority regimes); and, (b) countries with a low level of unification of powers and strong central bank involvement (central bank dominated multiple supervisor regimes). A trade‐off therefore emerges between the degree of financial sector unification and the role of the central bank. Two possible explanations of this relationship emerged: the blurring hazard effect and the monopolistic bureau effect.

The global financial crisis of 2008 emphasized the need for monetary policy authorities to have a more comprehensive view of the conditions prevailing in the economy before deciding their policy stance. The purpose of this paper is to outline the construction of a financial conditions index (FCI) and investigate the possible co-integrating relationship between the economic growth and FCI.

The study employs the PCA methodology, with appropriate augmentations to handle the unbalanced panel data-sets and constructs a FCI for India. It tests the growth-predicting power of FCI by applying the auto regressive distributed lags approach to co-integration and verifies if the FCI is co-integrated with real GDP growth. It also discusses construction of a financial development index (FDI) which tracks the financial markets through M3, market capitalization and credit amount to residents.

The constructed FCI has a quarterly frequency and is available starting 1998q2. The long-run coefficient of FCI while predicting the real GDP growth is significant at 10 percent. The results confirm that a more-broader index FCI outperforms a narrower index FDI in growth prediction.

By showing that FCI is a better growth predictor than FDI, the study establishes the importance of including the foreign exchange markets, bond markets and stock markets while summarizing the conditions in the economy. The authors hope that the FCI would be helpful to the monetary authorities in their policy decisions.

The paper adds to the few existing studies studies dealing with FCI for Indian economy and constructs a more comprehensive index which tracks multiple markets simultaneously. It also fills the gap in literature by evaluating the correlating relationship between FCI and economic growth.