Volatility Linkages Research Articles

An empirical examination of correlation dynamics between commodity and equity derivative indices: evidence from India using DCC-GARCH models

This empirical study investigates the time-varying co-movements and volatility linkages between equity-commodity indices and inter-commodity indices. This paper deploys DCC-GARCH framework. Three versions of GARCH namely standard, threshold and exponential with both symmetric and asymmetric versions of dynamic conditional correlations (DCC) have been used. This study considers equity index Nifty 50, non-agricultural commodity indices MCX Energy and MCX Metal along with agricultural commodity indices Dhaanya and MCX Agri. Our results revealed that the combined portfolio of commodities-equity has low or negative correlations, which provide better diversification property rather than a portfolio without commodities. However, we notice a steep decline in time-varying correlations of equity with non-agricultural commodity portfolio since 2013. The mixed portfolio of the agricultural commodity with non-agricultural commodity can also offer diversifying benefits. We found high volatility shifts in time-varying co-movements of Nifty 50-MCX Agri pair. On the other hand, we observed an increasing trend in the co-movements of Nifty 50-Dhaanya, it indicates the interdependency of these two markets. Non-agricultural commodity pair (MCX Energy-MCX Metal) and agricultural commodity pair (MCX Agri-Dhaanya) fail to offer better-diversifying properties. This study provides an essential insight to policymakers, portfolio managers, domestic and international investors, risk analysts and financial researchers in an emerging market.

Returns and Volatility Linkages of Nifty 50 with Major World Indices

The present study examines the linkages between equity indices of India, US, UK, China, Hong Kong, Korea and Japan. Cointegration analysis of Johansen-Juselius with daily data from January 2008 to December 2018 suggests that there is one cointegrating vector as per the Trace statistic. Also, results of pairwise cointegration test indicate that India is cointegrated with US and China. Results of granger causality reveal that past returns of stock index in one country influence future returns in other countries, except for India-US, India-UK, Hong Kong-India and Japan-India. Results of granger causality on conditional variance series show there is two-way volatility spillovers between the markets of India-US and India-Japan. Also, there is unidirectional volatility spillover from India to Hong Kong. The findings of the present study have useful implications for economist, money managers and investors.

Spatial connectedness of volatility spillovers in G20 stock markets: Based on block models analysis

This paper investigates the spatial connectedness of volatility spillovers in G20 stock markets. For this purpose, we apply GARCH–BEKK model to estimate volatility spillover and construct volatility networks. The results show that the spatial connectedness is time-varying, and the turmoil periods intensify volatility linkages. Further, we find that volatility networks can be divided into four different blocks by block models. And the volatility in each block has obvious “rich-club”. In the world trade friction, the source of the volatility risk is the country that is levied by the US tariff, and the volatility risk will eventually spread to the US.

Volatility forecasting with bivariate multifractal models

AbstractThis paper examines volatility linkages and forecasting for stock and foreign exchange markets from a novel perspective by utilizing a bivariate Markov‐switching multifractal model that accounts for possible interactions between stock and foreign exchange markets. Examining daily data from major advanced and emerging nations, we show that generalized autoregressive conditional heteroskedasticity models generally offer superior volatility forecasts for short horizons, particularly for foreign exchange returns in advanced markets. Multifractal models, on the other hand, offer significant improvements for longer horizons, consistently across most markets. Finally, the bivariate multifractal model provides superior forecasts compared to the univariate alternative in most advanced markets and more consistently for currency returns, while its benefits are limited in the case of emerging markets.

Information and volatility linkages across energy and financial markets

This study examines information and volatility linkages across energy and financial markets. In a world economy so connected, the impacts of climate change are likely to be transmitted through interlinked global markets. Hence, uncovering and understanding the interaction across these markets is a fundamental concern during the energy transition as it helps to understand how to strengthen incentives to facilitate energy investments. Based on the relation between information flows and volatility, this study employs a simple correlation approach based on implied volatility measures and the trading model of Fleming et al. to measure the common information linkages, as gauged by the correlation of return volatilities. The results suggest that volatility linkages across these markets are strong due to common information sharing and cross-market hedging. JEL Classification: G12, G14

Price and Volatility Linkages Between Indian Stocks and Their European GDRs

This article tests for price and volatility linkages between Indian global depositary receipts (GDRs) traded in Luxembourg/London and their underlying shares traded in Mumbai. The relationship is studied between the GDR price and the domestic share price along with the appropriate exchange rates, the foreign stock index and the domestic stock index using the vector autoregression (VAR) and dynamic conditional correlation (DCC) specification of multivariate generalised autoregressive conditional heteroscedasticity (GARCH) models. VAR results indicate a similarity between the two prices of scrips: one trading in Mumbai and the other trading in Luxembourg (London). Further, DCC-GARCH model outcomes point to, by and large, a high-dynamic correlation between Indian GDRs traded in Luxembourg/London and their underlying stocks listed in Mumbai. Thus, the price and volatility linkages between the Indian stock and its European counterpart are invariant with respect to the choice of the foreign stock exchange. Such a similarity in findings, notwithstanding the difference in degree of information disclosure as well as listing requirements at London and Luxembourg, is perhaps indicative of the stock-exchange-invariant nature of law of one price. JEL Classification: G15, C22

International Interdependence between Cash Crop and Staple Food Futures Price Indices: A Dynamic Assessment

Abstract:This study examines the price level and volatility interaction between international staple food and cash crop futures price indices. Understanding the relationship between these commodities bears significant implications for low-income food deficit countries that depend on cash crops to finance food import bills. We use a wavelet analysis to decompose the price indices and then apply a BEKK-MGARCH (Baba, Engle, Kraft and Kroner–multivariate generalized autoregressive conditional heteroskedasticity) approach to analyze the relationship across timescales. Results indicate the level of correlation and volatility linkages are strongest at lower frequencies (longer run) than at higher timescales (short run), with information running from staple food to cash crop markets.

The volatility surprise of leading cryptocurrencies: Transitory and permanent linkages

There is scarce literature examining the volatility linkages among leading cryptocurrencies, and none exists on the linkages among unexpected volatility, called ‘volatility surprise’. To address this literature gap, we build on the concept of volatility surprise and examine the causal linkages among the volatility of leading cryptocurrencies via the frequency-domain test of Bodart and Candelon (2009), discriminating between transitory and permanent causalities. Permanent shocks are more important in explaining the Granger-causality that does not necessarily emanate from the largest, Bitcoin, over short horizons, whereas transitory shocks dominate the causality across smaller cryptocurrencies over long horizons.

The volatility linkage between energy and agricultural futures markets with external shocks

This paper investigates the volatility linkage between energy and agricultural futures returns and how this linkage responds to external macroeconomic shocks. A framework combining the VARMA-BEKK-GARCH model and the Permanent-Transitory decomposition technology is employed to detect the volatility transmission, to decompose the volatility linkage into permanent and transitory components, and to examine the underlying determinants of the transitory volatility linkage. We have the following findings. A bidirectional volatility linkage between energy and agricultural futures returns exists and becomes more pronounced in recent years. The bidirectional linkage results from the co-movement effect induced by external shocks rather than from the substitution effect induced by the biofuel industry, and is not weakened by the shale gas revolution. Serving as proxies for external shocks from the world economy, trade, and financial markets, the CRB, BDI, and USDX indices provide strong explanatory power for the transitory volatility linkage, and the futures of these indices can be used to effectively and inexpensively hedge against the risks of the portfolios involving energy and agricultural futures.

Risk spillovers and portfolio management between precious metal and BRICS stock markets

Using the daily dataset from January 3, 2001 to December 28, 2017, we explore the risk spillovers between the BRICS stock markets and precious metal markets by means of the DCC-GJR-GARCH model. The dynamic volatility linkages between stock and precious metal sectors are long-persistence and fluctuate greatly during the sample period. In some sample period, the conditional correlation is negative, indicating that investors may hedge their risks from a diversified portfolio. As for the portfolio implications, both the value of optimal weight and hedge ratio is high with severe fluctuations for each market pairs, meaning that portfolio managers should adjust their investment structure based on different market conditions. After the global financial crisis, the hedging capability of precious metal sectors turns different among BRICS stock markets. Precious metal can hedge the risks of India and China stock markets more effective but not in Brazil and Russia markets. Our results may have some implications for portfolio managers and investors to reduce their risks.

Separating BRIC using Islamic stocks and crude oil: dynamic conditional correlation and volatility spillover analysis

This paper explores the dynamic conditional correlation and volatility linkage between Islamic indexes and oil for BRIC countries. Correlations between these assets increase during the global financial crisis for India and China but not for Brazil and Russia. The volatility error forecast variance of all five indexes comes from spillover but is much lower compared to volatility spillover between conventional indexes and oil. Hedging performance of Islamic indexes are superior in India and China compared to conventional indexes in emerging markets. An optimal minimum-variance portfolio without reducing expected return can be achieved by investing in lower weights of BRIC Islamic indexes and oil compared to conventional indexes.

Return and volatility spillover across equity markets between China and Southeast Asian countries

Purpose This paper aims to study the daily returns and volatility spillover effects in common stock prices between China and four countries in Southeast Asia (Vietnam, Thailand, Singapore and Malaysia). Design/methodology/approach The analysis uses a vector autoregression with a bivariate GARCH-BEKK model to capture return linkage and volatility transmission spanning the period including the pre- and post-2008 Global Financial Crisis. Findings The main empirical result is that the volatility of the Chinese market has had a significant impact on the other markets in the data sample. For the stock return, linkage between China and other markets seems to be remarkable during and after the Global Financial Crisis. Notably, the findings also indicate that the stock markets are more substantially integrated into the crisis. Practical implications The results have considerable implications for portfolio managers and institutional investors in the evaluation of investment and asset allocation decisions. The market participants should pay more attention to assess the worth of across linkages among the markets and their volatility transmissions. Additionally, international portfolio managers and hedgers may be better able to understand how the volatility linkage between stock markets interrelated overtime; this situation might provide them benefit in forecasting the behavior of this market by capturing the other market information. Originality/value This paper would complement the emerging body of existing literature by examining how China stock market impacts on their neighboring countries including Vietnam, Thailand, Singapore and Malaysia. Furthermore, this is the first investigation capturing return linkage and volatility spill over between China market and the four Southeast Asian markets by using bivariate VAR-GARCH-BEKK model. The authors believe that the results of this research’s empirical analysis would amplify the systematic understanding of spillover activities between China stock market and other stock markets.

Volatility Linkages between Agricultural Commodity Prices, Oil Prices and Real USD Exchange Rate

This study examines the dynamic nexus betwixt oil prices, twenty-two world agricultural commodity prices and given the evolution of the relative strength of the US dollar in a panel setting. We use panel cointegration and Panel Granger causality methods for a panel of twenty-two agricultural products based on annual observations ranging from 1980 to 2015. The empirical results provide a strong evidence of long-term relationship between Agricultural Commodity Prices, Oil Prices and Real USD Exchange Rate. Contrary to the findings of many studies in the literature that report neutrality of agricultural prices to oil price changes, we find strong support of bi-directional causal linkages among Agricultural Commodity Prices, Oil Prices and Real USD Exchange Rate. The long-run causality analysis thereby implies that the oil prices and the dollar have a predictive power to forecast the agricultural prices, which could be a good tool to prioritize the allocation of resources across industries to ensure agricultural scenario in general and economic outcomes.

Return and volatility linkages among International crude oil price, gold price, exchange rate and stock markets: Evidence from Mexico

This study investigates the dynamic relationship among international oil prices, international gold prices, exchange rate and stock market index in Mexico. Mexico is a major oil and gold exporting country and at the same time a major importer of petroleum products. ARDL Bound testing cointegration approach has been used on daily data ranging from January 2006 to April 2018. Findings of the study suggest that international gold prices positively affect the stock price of Mexico while oil price affects them negatively. Oil prices negatively influence exchange rate in the long and gold price do not have any significant impact on the exchange rate. The finding of this research have important implications and also provides some signals to monetary and fiscal policies, considering the pressure crude oil prices create on the stock markets and exchange rates.

Return and volatility spillovers in the presence of structural breaks: evidence from GCC Islamic and conventional banks

The dynamics of return and volatility spillover indices were investigated to reveal the strength and direction of transmission that occurred during a financial crisis. The focus of this study was especially placed on the 2007 US subprime mortgage crisis, the global financial crisis, the European sovereign debt crisis, and the dramatic collapse of oil prices since 2014. The paper uses the Diebold and Yilmaz (Economic Journal 119(534): 158–171, 2009, International Journal of Forecasting 28(1): 57–66, 2012) spillover index behavior. Assuming one structural break, return and volatility linkages for Islamic banks in the GCC were stronger than for conventional banks. When multiple breaks were allowed, the spillover index was found to be highly sensitive to various economic events. Overall, the findings of this study provide new insights into the behavior of the Islamic and conventional banks stock returns and volatility spillovers, which may improve investment decisions and the trading strategies portfolio of investors.

Price and Volatility Linkages between International REITs and Oil Markets

This study analyzes price and volatility transmissions between nineteen real estate investment trusts (REITs) markets and the oil market. The REITs data represents a variety of countries at different stages of their development and the expanded analytical approach includes accounting for structural shifts as gradual processes – as opposed to strictly abrupt processes typically assumed in literature. Oil prices are found to primarily predict REITs prices in mature REITs markets, but the feedback from REITs to oil prices is weak. From the perspective of volatility, strong evidence of bidirectional transmission in majority of the markets is observed. This study further demonstrates the importance of accounting for gradual (smooth) structural shifts for price transmission analysis.

Measuring volatility linkage, clustering and sensitivity to external shocks in Nigerian stock index

Recent events in the global economy have further exposed the fear and uneasiness in the minds of investors around the world. The resort to protectionist policies by nations around the world as reaction to the attempt by US President Donald Trump to use higher tariffs to increase his country's share of global trade has made global investors seek safe havens. This paper measures stock market volatility and linkages among three stock markets. EGARCH and TGARCH models were employed in analysing univariate volatility in the indices, while bivariate GARCH (diagonal BEKK) was employed in measuring returns linkages. The result of the analysis shows that markets exhibit evidence of asymmetry and persistence in volatility; volatility from previous periods significantly affects current period and markets react with speed to news of volatility. In terms of portfolio diversification, NSE-IST provides better opportunity followed by NSE-JSE and then JSE-IST.

Measuring volatility linkage, clustering and sensitivity to external shocks in Nigerian stock index

Measuring volatility linkage, clustering and sensitivity to external shocks in Nigerian stock index

Domestic and International Information Linkages for the US Dollar/Indian Rupee Contracts: An Empirical Study

This study examines price discovery and volatility linkages between USD/INR spot and futures contracts in India and between USD/INR futures contracts on National Stock Exchange of India Limited (NSE), India and on three international exchanges, namely Singapore Exchange (SGX), Dubai Gold and Commodity Exchange (DGCX) and Chicago Mercantile Exchange (CME), from 29 August 2008 to 30 March 2015. Findings show that, at domestic level, the futures dominate spot in the Indian currency market; these findings are stronger than those in an earlier study, indicating improved pricing as well as hedging efficiency in the Indian currency market. At international level, NSE is dominated by both CME and DGCX in price discovery and in short-term volatility spillovers, while NSE dominates both exchanges in long-term volatility spillovers. Further, NSE dominates SGX in the international information process. The dominance of CME and DGCX over NSE may be on account of their several advantages such as longer trading hours, operations being open even after NSE has shut business, much lower trading costs as well as lower regulatory restrictions. The study provides several significant policy suggestions for improving efficiency of the Indian currency market and is also relevant for foreign portfolio investors (FPIs), domestic investors, researchers and academicians. It contributes to literature on information transmission relating to currency markets in emerging economies.

Time - Varying Correlations, Causality, and Volatility Linkages of Indian Commodity and Equity Markets : Evidence from DCC - GARCH

Time - Varying Correlations, Causality, and Volatility Linkages of Indian Commodity and Equity Markets : Evidence from DCC - GARCH