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The present study examines the short term dynamism and long term equilibrium relationship between the stock markets of South and Central America. It also aims to capture the dynamic conditional correlations between the stock markets using weekly returns of market benchmark indices of the respective countries spanning from 2nd week of 1995 to 4th week of December 2015 are analyzed.

The Johansen and Juselius multivariate cointegration test, Granger causality test based vector error correction model (VECM) approach, and variance decomposition analysis were used to investigate the dynamic linkages between markets. GARCH-DCC is used to investigate the Correlation Dynamics.

This study identifies long run co-movements between the stock markets. Chile, Peru and Venezuela are the most dynamically interlinked. The empirical results VECM reveal that Argentina, Brazil, Chile and Venezuela stock market returns are significantly influenced by each other, suggesting a stronger linkages between national stock markets. Cointegration test confirms long-run equilibrium relationship. among the major stock markets of the region. The findings from GARCH-DCC provide evidence consistent with increasing market integration. Stocks exhibit asymmetries in conditional correlations. The results demonstrate that correlations are higher toward the end of the sample period than in the early phase.

On the basis of the results produced by the study, we conclude that there exist opportunities for diversification and investors will benefit from reduction of diversifiable risk among the South and Central American countries in general, but in particular Chile, Peru and Venezuela have not shown the same outcome.

This study has been conducted for a longer period of time and also uses various tools to investigate the dynamic linkages between markets.VAR, VECM, Cointegration and GARCH-DCC altogether in a single study is a rare piece of work.

The purpose of this paper is to examine the potential gains in hedge ratio calculation for agricultural commodities by incorporating market linkages and prices of related commodities into the hedge ratio estimation process.

A vector autoregressive multivariate generalized autoregressive conditional heteroskedasticity (VAR‐MGARCH) model is used to construct a time‐varying correlation matrix for commodity prices across linked markets and across linked commodities. The MGARCH model is estimated using a two‐step approach, which allows for a large system of related prices to be estimated.

In‐sample and out‐of‐sample portfolio variance comparison among no hedge, bivariate GARCH, and MGARCH models indicates that hedge ratios estimated using the MGARCH approach reduce agricultural producers' and commercial consumers' risks in futures market participation.

The application is limited to an examination of Montana wheat markets.

Agricultural producers who use futures markets to reduce market risk will have a better method for determining hedging positions, because MGARCH estimated hedge ratios incorporate more information than hedge ratios estimated using existing practices.

Portfolio variance reduction is analogous to utility improvement for agricultural producers. More efficient hedging strategies can lead to better implementation of futures markets and increased social welfare.

This research substantially extends current literature on agricultural hedge strategies by illustrating the advantages of using an hedge ratio estimation approach that incorporates important information about prices at linked markets and prices of other commodities. Providing evidence that market portfolio variance can be lowered using the multivariate estimation approach, the research offers commercial agricultural producers and consumers a practical tool for improving futures market strategies.

In September‐October 2008 the Russian stock markets came under severe strain amidst the global financial crisis. During this time the Russian government intervened several times to halt the trade to impede the continuous slide. The government justified its actions owing to the argument that the crisis was due to a trickledown effect from the financial crisis in the USA and the other developed markets. The purpose of this paper is to put to test the government's claim by exploring the level of integration between Russia and the USA and European equity markets.

The study employs Markov Regime Switching Model for tracking structural breaks in the time series. This method divides the data into three periods, i.e. pre crisis, during crisis and post crisis. Next the Multivariate GARCH‐DCC model technique is used to establish the time varying linkages in order to verify the contagion effect. In the final step the Markowitz mean‐variance framework is used to position each individual index portfolio with respect to the efficient frontier to analyze the impact of crisis as well as Russian government intervention.

The findings suggest that the Russian equity market is weakly integrated with US and strongly integrated with European markets. The results correspond to the underlying financial and economic linkages between Russia, the US and Europe. When examined in a portfolio setup, the results show sudden fall in correlation among the Russian, US and European equity markets suggesting weak linkages among these markets. Finally, the Markowitz Efficient frontier indicates dramatic rise in volatility on the day intervention began and ended which signifies the increased uncertainty among the investors owing to Russian government ad hoc interventions.

The paper attempts to examine the Russian government intervention in the backdrop of financial crisis 2008 and concludes that the government intervention essentially increased the uncertainty in the local as well as international markets. Therefore, it is essential that the government should avoid direct intervention in its stock market.

The purpose of this paper is to examine empirically the impact of COVID-19 pandemic news in USA and in China on the dynamic conditional correlation between Bitcoin and Gold.

This paper offers a crucial viewpoint to the predictive capacity of COVID-19 surprises and production pronouncements for the dynamic conditional correlation (DCC) among Bitcoin and Gold returns and volatilities using generalized autoregressive conditional heteroskedasticity-DCC-(1,1) through the period of study since July 1, 2019 to June 30, 2020. To assess the unexpected impact of COVID-19, this study pursues the Kuttner’s (2001) methodology.

The empirical findings indicate strong important correlation among Bitcoin and Gold if COVID-19 surprises are integrated in variance. This study validates the financialization hypothesis of Bitcoin and Gold. The correlation between Bitcoin and Gold begin to react significantly further in the case of COVID-19 surprises in USA than those in China.

This paper contributes to the literature on assessing the impact of COVID-19 confirmed cases surprises on the correlation between Bitcoin and Gold. This paper gives for the first time an approach to capture the COVID-19 surprise component. Also, this study helps to improve financial backers and policymakers' comprehension of the digital currencies' market elements, particularly in the hours of amazingly unpleasant and inconspicuous occasions.

Systemic risk has been a cause of concern for the bank regulatory authorities worldwide since the global financial crisis. This study aims to identify systemically important banks (SIBs) in India by using SRISK to measure the expected capital shortfall of banks in a systemic event. The sample size comprises a balanced data set of 31 listed Indian commercial banks from 2006 to 2019.

In this study, the authors have used SRISK to identify banks that have a maximum contribution to the systemic risk of the Indian banking sector. Leverage, size and long-run marginal expected shortfall (LRMES) are used to compute SRISK. Forward-looking LRMES is computed using the GJR-GARCH-dynamic conditional correlation methodology for early prediction of a bank’s contribution to systemic risk.

This study finds that public sector banks are more vulnerable to macroeconomic shocks owing to their capital inadequacy vis-à-vis the private sector banks. This study also emphasizes that size should not be used as a standalone factor to assess the systemic importance of a bank.

Systemic risk has attracted a lot of research interest; however, it is largely limited to the developed nations. This paper fills an important research gap in banking literature about the identification of SIBs in an emerging economy, India. As SRISK uses both balance sheet and market-based information, it can be used to complement the existing methodology used by the Reserve Bank of India to identify SIBs.

The purpose of this paper is to quantify the extent to which the Malaysia-based equity investors can benefit from diversifying their portfolio into the conventional and Islamic Southeast Asian region and the world’s top ten largest equity indices (China, Japan, Hong Kong, India, the UK, the USA, Canada, France, Germany and Switzerland).

The multivariate GARCH-dynamic conditional correlation is deployed to estimate the time-varying linkages of the selected conventional and Islamic Asian and international stock index returns with the Malaysian stock index returns, covering approximately eight years daily starting from 29 June 2007 to 30 June 2016.

In general, in terms of volatility, the results indicate that both Asian and international Islamic stock indices are more or less volatile than its conventional counterparts. From the correlation analysis, we can see that both the conventional and Islamic MSCI indices of Japan provide more diversification benefits compared to Southeast Asian region, China, Hong Kong and India. Meanwhile, in terms of international portfolio diversification, the results tend to suggest that both the conventional and Islamic MSCI indices of the USA provide more diversification benefits compared to the UK, Canada, France, Germany and Switzerland.

The findings of this paper may have several significant implications for the Malaysia-based equity investors and fund managers who seek for the understanding of return correlations between the Malaysian stock index and the world’s largest stock market indices in order to gain higher risk-adjusted returns through portfolio diversification. With regard to policy implications, the findings on market shocks and the extent of the interdependence of the Malaysian market with cross-border markets may provide some useful insights in formulating effective macroeconomic stabilization policies in the efforts of preventing contagion effect from deteriorating the domestic economy.

This paper aims to analyse the opportunity of an exclusive investment in the DJ Islamic indexes. The objective is to characterize the links between MENA region index with seven DJ Islamic indexes.

A co-movement analysis was conducted to assess whether there is a safe investment during crisis. The VECM verifies the existence of a long run association. The MGARCH-DCC characterizes the dynamic links. The wavelet coherence detects a correlation in a time-frequency domain, which is relevant to set up a diversification strategy based on investment horizons.

Despite the existence of a long run association between the Islamic indexes, diversification opportunities are present. The MGARCH-DCC results recommend including the USA, Canada and Emerging Markets indexes with the Mena index to get diversification benefits. The Wavelet coherence confirms these results for 0 to 16 days holding period and more than six-months’ investment horizons. Hence, MENA portfolio managers should not invest in Europe, UK and Emerging Markets indexes.

This study focused only on the bivariate correlation analysis without taking into consideration multivariate relationships. Future research should use multiple wavelet coherence and explore S&P Shariah indexes.

This work is important for investors searching for assets governed by sharia rules, who reject resorting to conventional markets, and policy makers dealing with coordination costs. They would be able to formulate strategies based on the different indexes’ relationships.

This paper enriches the limited stream of literature focusing only on Islamic indexes. Due to the important development of Islamic Finance in each MENA country, the authors shed the light on this Region’s index.

Corporate treasurers manage the currency risk of their organization by hedging through futures contracts. The purpose of this paper is to evaluate the effectiveness of hedging by US currency futures contracts by taking into account the efficiency of the currency market.

The static models for calculating hedge ratio are as popular as dynamic models. But the main disadvantage with the static models is that they do not consider important properties of time series like autocorrelation and heteroskedasticity of the residuals and also ignore the cointegration of the market variables which indicate short-run market disequilibrium. The present study, therefore, measures the hedging effectiveness in the US currency futures market using two dynamic models – constant conditional correlation multivariate generalized ARCH (CCC-MGARCH) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH).

The study finds that both the dynamic models used in the study provide similar results. The relative comparison of CCC-MGARCH and DCC-MGARCH models shows that CCC-MGARCH provides better hedging effectiveness result, and thus, should be preferred over the other model.

The findings of the study are important for the company treasurers since the new updated Indian accounting standards (Ind-AS), applicable from the financial year 2016–2017, make it mandatory for the companies to evaluate the effectiveness of hedges. These standards do not specify a quantitative method of evaluation but provide the flexibility to the companies in choosing an appropriate method which justifies their risk management objective. These results are also useful for the policy makers as they can specify and list the appropriate methods for evaluating the hedge effectiveness in the currency market.

Majorly, the studies on Indian financial market limit themselves to either examining the efficiency of that market or to evaluate the effectiveness of the hedges undertaken. Moreover, most of such works focus on the stock market or the commodity market in India. This is one of the first studies which bring together the concepts of efficiency of the market and effectiveness of the hedges in the Indian currency futures market.

This paper aims to investigate the impact of oil price shocks on the Turkish sovereign yield curve factors.

To extract the latent factors (level, slope and curvature) of the Turkish sovereign yield curve, we estimate conventional Nelson and Siegel (1987) model with nonlinear least squares. Then, we decompose oil price shocks into supply, demand and risk shocks using structural VAR (structural VAR) models. After this separation, we apply Engle (2002) dynamic conditional correlation GARCH (DCC-GARCH (1,1)) method to investigate time-varying co-movements between yield curve factors and oil price shocks. Finally, using the LP (local projections) proposed by Jorda (2005), we estimate the impulse-response functions to examine the impact of different oil price shocks on yield curve factors.

Our results demonstrate that the various oil price shocks influence the yield curve factors quite differently. A supply shock leads to a statistically significant increase in the level factor. This result shows that elevated oil prices due to supply disruptions are interpreted as a signal of a surge in inflation expectations since the cost channel prevails. Besides, unanticipated demand shocks have a positive impact on the slope factor as a result of the central bank policy response for offsetting the elevated inflation expectations. Finally, a risk shock is associated with a decrease in the curvature factor indicating that risk shocks influence the medium-term bonds due to the deflationary pressure resulting from depressed economic conditions.

Our results provide new insights to understand the driving forces of yield curve movements induced by various oil shocks to formulate appropriate policy responses.

The study contributes to the literature by two main dimensions. First, the recent oil shock identification scheme of Ready (2018) is modified using the “geopolitical oil price risk index” to capture the changes in the risk perceptions of oil markets driven by geopolitical tensions such as terrorism and conflicts and sanctions. The modified identification scheme attributes more power to demand shocks in explaining the variation of the oil price compared to that of the baseline scheme. Second, it provides recent evidence that distinguishes the impact of oil demand and supply shocks on Turkey's yield curve.

The purpose of this paper is to measure the effectiveness of the hedging with futures currency contracts. Measuring the effectiveness of hedging has become mandatory for Indian companies as the new Indian accounting standards, Ind-AS, specify that the effectiveness of hedges taken by the companies should be evaluated using quantitative methods but leaves it to the company to choose a method of evaluation.

The paper compares three models for evaluating the effectiveness of hedge – ordinary least square (OLS), vector error correction model (VECM) and dynamic conditional correlation multivariate GARCH (DCC-MGARCH) model. The OLS and VECM are the static models, whereas DCC-MGARCH is a dynamic model.

The overall results of the study show that dynamic model (DCC-MGARCH) is a better model for calculating the hedge effectiveness as it outperforms OLS and VECM models.

The new Indian accounting standards (Ind-AS) mandates the calculation of hedge effectiveness. The results of this study are useful for the treasurers in identifying appropriate method for evaluation of hedge effectiveness. Similarly, policymakers and auditors are benefitted as the study provides clarity on different methods of evaluation of hedging effectiveness.

Many previous studies have evaluated the efficiency of the Indian currency futures market, but with rising importance of hedging in the Indian companies, Reserve Bank of India’s initiatives and encouragement for the use of futures for hedging the currency risk and now the mandatory accounting requirement for measuring hedging effectiveness, it has become more relevant to evaluate the effectiveness of hedge. To the authors’ best knowledge, this is one of the first few papers which evaluate the effectiveness of the currency future hedging.