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Muslim investors must comply with the ethical injunctions prescribed for them while making financial investments. As per Islamic principles, the use of Riba (interest), Maysir (gambling) and Gharar (uncertain or contingent payoff contracts) is prohibited. This chapter provides some recent post great financial crisis evidence on the comparative performance of Islamic and conventional market indices. Islamic indices outperformed conventional market indices in terms of annualized returns except for emerging markets. In the overall period of 2007-16, it is found that Islamic indices have a lower coefficient of variation and hence higher reward to variability ratio. This suggests that Islamic indices are superior to conventional market indices adjusting for variability in returns. In most comparable Islamic and conventional indices, a strong co-movement and long-term co-integrating relationship is found. The results also highlighted causality running from conventional indices to the Islamic indices in most of the market groups, except for the S&P Global.

This paper investigates the impact of financial stress on the dynamic connectedness and hedging for oil market and stock-bond markets of the Gulf Cooperation Council (GCC).

This study uses the wavelet coherence model to examine the interactions between financial stress, oil and GCC stock and bond markets. Second, the authors apply the time–frequency connectedness developed by Barunik and Krehlik (2018) so as to identify the direction and scale connectedness among these markets. Third, the authors examine the optimal weights, hedge ratio and hedging effectiveness for oil and financial markets based on constant conditional correlation (CCC), dynamic conditional correlation (DCC) and Baba-Engle-Kraft-Kroner (BEKK)-GARCH models.

The authors have found that the correlation between the oil and stock-bond markets tends to be stable in nonshock periods, but it evolves during oil and financial shocks at lower frequencies. Moreover, the authors find that the oil market and financial stress are the main transmitters of risks. The connectedness is mainly driven by the long term, demonstrating that the markets rapidly process the financial stress spillover effect, and the shock is transmitted over the long run. Optimal weights show different patterns for each negative and positive case of the financial stress index. In the negative (positive) financial stress case, investors should have more oil (stocks) than stocks (oil) in their portfolio in order to minimize risk.

This study has gone some way toward enhancing one’s understanding of the time–frequency connectedness between the financial stress, oil and GCC stock-bond markets. Second, it identifies the impact of financial stress into hedging strategies offering important insights for investors aiming at managing and reducing portfolio risk.

This research examines the use of econometric models to predict the total net asset value (NAV) of an asset allocation mutual fund. In particular, the mutual fund case used is the Vanguard Wellington Fund (VWELX). This fund maintains a balance between relatively conservative stocks and bonds. The period of the study on which the prediction of the total NAV is based is the 24-month period of 2010 and 2011 and the forecasting period is the first three months of 2012. Forecasting the total NAV of a massive conservative allocation fund, composed of an extremely large number of investments, requires a method that produces accurate results. Achieving this accuracy has no necessary relationship to the complexity of the methods typically employed in many financial forecasting studies.

This study aims to examine the tail connectedness between the Chinese and Association of Southeast Asian Nations (ASEAN) stock markets. More specifically, the authors measure the return spillovers at three quantile levels: median (t = 0.5), lower extreme (t = 0.05) and upper extreme (t = 0.95). The connectedness at extreme upper and lower quantiles provides insightful information to investors regarding tail risk propagation, which ultimately suggests that investors adjust their portfolios according to the extreme bullish and bearish market conditions.

The authors employ the quantile connectedness approach of Ando et al. (2022) to examine the quantile transmission mechanism among the ASEAN and Chinese stock markets.

The results show significant evidence of a higher level of connectedness between Chinese and ASEAN stock markets at extreme upper and lower quantiles compared to the median quantiles, which suggests the use of a quantile-based connectedness approach instead of an average-measure-based one. Furthermore, the time-varying connectedness analysis shows that the total spillovers reach the highest peaks during the global financial crisis, the Chinese stock market crash and the COVID-19 pandemic at the upper, lower and median quantiles. Finally, the static and dynamic pairwise spillovers between the Chinese and ASEAN markets vary over quantiles as well.

This study is the first attempt to examine quantile vector autoregression (VAR)-based return spillovers between China and ASEAN stock markets during different market statuses. Besides, the COVID-19 has intensified the uncertainty in Asian countries, mainly China and ASEAN economies.

The purpose of this paper is to examine the volatility spillover and lead-lag relationship between the Chicago Board Options Exchange volatility index (VIX) and the major agricultural future markets before and during the Coronavirus disease 2019 (COVID-19) outbreak.

The methods used were the vector autoregression-Baba, Engle, Kraft and Kroner-generalized autoregressive conditional heteroskedasticity method, the Wald test and wavelet transform method.

The findings indicate that prior to the COVID-19 outbreak, there was a two-way volatility spillover impact between the majority of the sample markets. In comparison, volatility transmission between the VIX index and the agricultural future market was significantly lower following the COVID-19 outbreak, the authors observed greater coherence at higher frequencies than at lower frequencies, implying that the interdependence between the two VIX indices and the agricultural future market was stronger over a longer time-frequency domain and the VIX’s signalling effect on various agricultural future prices after the COVID-19 outbreak was significantly lower.

The authors conducted the first comprehensive investigation of the VIX’s correlation with major agricultural futures, especially during COVID-19. The findings contribute to a better understanding of the risk transmission mechanism between the VIX and major agricultural commodities futures contracts. And our findings have significant implications for investors and portfolio managers, as well as for policymakers who are concerned about the price of agricultural futures.

Study of the interdependence among economies is of considerable importance. This area includes issues such as the increasing importance of regional economic interactions, the effects of economic growth and recession in the advanced economies on emerging market countries, and financial contagion. A wide range of related terms and methodologies are used in the literature of interdependence. The purpose of this paper is to review the major concepts and various measurements of interdependence in financial markets and the real economy, serving as a reference and benchmark for future research on interdependence among specific regional or global economies.

Major measurements of interdependence are reviewed from simple approach to more complicated ones, and strengths and weaknesses of the various measurements of interdependence are discussed.

This paper surveys the various major measurements of interdependence and illustrates how they have been used to address a substantial range of issues.

The paper shows that studies of macroeconomic and financial interdependence use the same types of econometric measurements. The review and critiques of these various types of measures should be of value to those wishing to do research in these areas and also to those wishing to have a better understanding of papers that they read.

This study examines the extent to which gold and silver bubbles are correlated and which metal’s bubble spills over to the other. In addition, the overlap in bubble-like episodes for the two metals is demonstrated and the influence of crises (global financial crises, European debt crisis and the COVID-19 pandemic) on the development of these episodes is compared.

This study proposes a two-step approach. In the first step, price bubbles are identified based on the backward sup augmented Dickey–Fuller of Phillips et al. (2015a, 2015b) and modified by Phillips and Shi (2018). In the second step, the correlation in the contagion effect of the bubbles between the two precious metal prices is measured using a nonparametric regression with a time-varying coefficient approach developed by Greenaway-McGrevy and Phillips (2016).

The findings suggest that the safe-haven property of gold and silver during financial market turbulence induces excessive price increases beyond their fundamental values. Furthermore, the results indicate that bubbles are contagious among precious metal markets and flow mainly from gold to silver; these findings are associated with the period after 2005, particularly during the global financial crisis. A contagious bubble effect is not found between gold and silver during the coronavirus disease 2020 pandemic.

The results suggest that financial market participants should consider portfolio weights in precious markets in light of the bubble correlation between gold and silver, especially during crises.

To the best of the authors’ knowledge, this is the first study that explores the correlation of bubble-like episodes between gold and silver.

The purpose of this paper is to investigate the extent to which Chinese equity investors can benefit from diversifying their portfolio into Shariah-compliant (Islamic) indices. It examines three Islamic stock indices (FTSE Shariah China price index, MSCI China Islamic IMI price index and the DJ Islamic Greater China price index) and ten sectoral indices in Shanghai Stock Exchange as a sample.

The multivariate GARCH dynamic conditional correlations (MGARCH-DCC) is deployed to estimate the time-varying linkages of returns of the selected indices, covering approximately eight years daily data starting from 28 August 2009 to 29 September 2017.

In general, in terms of volatility, the results indicate that all Islamic Indices are less volatile than the conventional indices. From the correlation analysis, the results imply that Chinese conventional equity investors would benefit from Islamic stock indices, especially when they include DJ Islamic Greater China in their portfolio.

The findings of this paper may have several significant implications for the Chinese equity investors and fund managers for better understanding about co-movements of the Chinese conventional sectoral indices with the Shariah-compliant stock indices with the purpose of gaining higher risk-adjusted returns through portfolio diversification.

The paper tries to analyse empirically the impact of India's economic policy uncertainty (EPU) index on different macro-economic variables of India, like import, export, interest rate, exchange rate, inflation rate and stock market during pre-COVID-19 and COVID-19 era.

Although there exist several works where relationship and volatility among the stock markets and macro-economic indicators during the COVID-19 pandemic have been estimated, but till now none of the studies examined the effect of EPU index on different macro-economic variables in the Indian context along with the stock market due to the outbreak of COVID-19 pandemic. This is considered a noteworthy gap and hence opens up a new dimension for examination. To get a clear picture, monthly data from January, 2012 to September, 2021 have been considered where January, 2012–February, 2020 is taken as the pre-COVID-19 period and March, 2020–September, 2021 as COVID-19 period. All the data are converted into log natural. The authors applied DCC-GARCH model to investigate the impact of EPU index on volatility of selected variables over the study period across a multivariate framework and Markov regime-switching model to examine the switching over of the variables.

The results of dynamic conditional correlation - multivariate generalized autoregressive conditional heteroskedasticity (DCC-MGARCH) model indicates the presence of volatility in the dependent variables arising out of economic policy uncertainty considering the segmentation of the study period into pre-COVID-19 and COVID-19. The results of Markov regime-switching model show the variables make a significant move from low-volatility regime to high-volatility regime due to the presence of COVID-19.

It can be implied that impact of EPU in terms of volatility on the Indian Stock Market will lead to unfavourable investment conditions for the prospective investors. Even, the different macro-economic variables are to suffer from the volatility arising out of EPU across a long time horizon as confirmed from the DCC-MGARCH model.

The study is original in nature. It adds superior values from the new and significant findings from the study empirically. Application of DCC-MGARCH model and Markov regime switching model makes the study an innovative one in terms of methodology and findings.