Volatility Linkages Research Articles

Return and volatility linkages between CO2 emission and clean energy stock prices

The emission of CO2 has emerged as one of the key factors behind the significant growth of clean energy sources that are less carbon-intensive than conventional energy bases. However, investigating the link between the carbon emission market and the market of clean energy stocks remains extremely understudied. Accordingly, this study examines daily return and volatility linkages between the European Union Allowance (EUA) prices and clean energy stock returns. Employing the bivariate VAR-GARCH approach, we document that variations in the EUA prices affect the renewable energy stock returns positively, though the association is usually found to be statistically insignificant. Our findings further indicate a significant volatility linkage between emission and European clean energy price indexes. Such findings, however, do not hold for the US market, suggesting that emission return and volatility shocks are country- or region-specific. Further results show that the average correlations between emission and stock prices is very low and hence portfolio diversification benefits seem to be attainable if investors hold assets in the EUA and clean energy equity markets.

An Investigation of Return and Volatility Linkages among Stock Markets: A Study of Emerging Asian and Selected Developed Countries

This article investigates returns and volatility linkages among stock markets, including emerging Asian (e.g., India, China, Bangladesh, Malaysia, Philippine, and South Korea) stock markets and developed (e.g., United States, United Kingdom, Japan, and Singapore) stock markets. During the sample period, these emerging markets have experienced both rapid growth and major turmoil. Firstly, the Generalized Autoregressive Conditional Heteroskedastic (GARCH) family models are used, and the correlation in conditional variances is calculated to show the relationship in the volatilities of the returns in these markets. Then, the cross-correlation function tests are conducted to investigate the causality patterns of the stock returns and volatility. Finally, the Vector Autoregressive (VAR) model is used to study the transmission dynamics in the presence of unexpected shocks. The evidence suggests that both the returns and volatility linkages exist between the emerging Asia and the developed stock markets. From causality test, it is found that both returns and return variances linkages exist between the emerging Asian and selected developed countries. Nevertheless United States influences the other countries most on both the mean and variance patterns. In addition, the volatilities to unexpected shocks in various markets, especially, come from neighboring country markets and more developed country markets.

Real estate's information and volatility links with stock, bond and money markets

AbstractWe examine real estate's information and volatility linkages with stock, bond and money markets. Based on the theory that the volatility of prices directly reflects of the rate at which information flows to the market (Kyle, ; Ross, ), we propose that information linkages across markets are revealed in the correlations of their volatilities, rather than correlations of returns. Applying an implied volatility correlation approach and the Generalized Method of Moments (GMM) estimation of Fleming et al. () stochastic volatility model, we find strong information and volatility linkages across the four markets.

Domestic and International Information Linkages between Gold Spot and Futures Markets: An Empirical Study for India

This article examines information linkages between gold spot market in India and gold futures at India’s Multi Commodity Exchange (MCX) and five international platforms [i.e., Commodity Exchange (COMEX), Dubai Gold and Commodity Exchange (DGCX), Tokyo Commodity Exchange (TOCOM), Hong Kong Exchange (HKE) and Singapore Mercantile Exchange (SMX)] from August 2008 to March 2015. Cointegration procedure and vector error correction model (VECM), supported by Granger causality, are employed to study price discovery process, and bivariate EGARCH-BEKK model is used to examine volatility spillover process. At domestic level, spot market dominates the futures in information transmission process. Internationally, DGCX leads all other exchanges in price discovery process, while COMEX leads in volatility spillovers. In price discovery, MCX leads only TOCOM till August 2013, while price discovery is absent thereafter. In volatility spillovers, MCX dominates TOCOM and HKE till this period and only HKE afterwards. Thus, information linkages between MCX and international exchanges appear to have been impacted severely since August 2013. The study highlights the need to re-establish price and volatility linkages between Indian and international exchanges, and also provides significant suggestions for policymakers. The study is relevant for investors, researchers and the academia. It contributes to market efficiency and information transmission literature for commodity markets.

Volatility spillovers between foreign exchange and stock markets in industrialized countries

This paper empirically analyses the evidence of intra-spillovers and inter-spillovers between foreign exchange and stock markets in the seven economies which constitute the majority of foreign exchange transactions (i.e. the United Kingdom, the United States, the Euro area, Australia, Switzerland, Canada, and Japan). Daily data during the period 1 January 1990 to 31 December 2015 and during the pre-global and post-global financial crisis periods is used. To that end, we employ two econometric methodologies: the C-GARCH methodology and the SVAR framework. Results suggest that: (i) permanent and transitory components of the conditional variance exhibit peaks in volatility during episodes of growing economic and financial instability; (ii) the long-run volatility relationships are stronger than the short-run volatility linkages with a reinforcement during the post-global financial crisis period; (iii) the presence of intra-spillovers and inter-spillovers increases substantially during the post-global financial crisis period and (iv) the stock markets play a dominant role in the transmission of long-run and short-run volatility in all samples, except for the period after the global financial crisis, where the foreign exchange markets are the main long-run volatility triggers.

International financial integration: Stock return linkages and volatility transmission between Vietnam and advanced countries

This paper investigates the interdependence between the Vietnamese stock market and other influential equity markets in terms of return linkage and volatility transmission covering the period including pre, during and post the 2008 Global Financial Crisis. A VAR model is utilized to estimate the conditional return linkage among these indices and a GARCH-BEKK model is employed to investigate the volatility transmission. We find evidence of statistically significant correlation, return spillover and volatility linkage between Vietnamese stock market with other leading equity markets of the US, Hong Kong and Japan. Moreover, we find that during the financial crisis, stock markets become more interrelated.

Time-varying synchronization and dynamic conditional correlation among the stock market returns of leading South American economies

PurposeThe purpose of this paper is to capture the pattern of return volatility and information spillover and the extent of conditional correlation among the stock markets of leading South American economies. It also examines the connectedness of market returns within the region.Design/methodology/approachThe time series properties of weekly stock market returns of benchmark indices spanning from the second week of 1995 to the fourth week of December 2015 are analyzed. Using univariate auto-regressive conditional heteroscedastic, generalized auto-regressive conditional heteroscedastic, and dynamic conditional correlation multivariate GARCH model approaches, the study finds evidence of returns and volatility linkages along with the degree of connectedness among the markets.FindingsThe findings of this study are consistent with increasing market connectedness among a group of leading South American economies. Stocks exhibit relatively fewer asymmetries in conditional correlations in addition to conditional volatility; yet, the asymmetry is relatively less apparent in integrated markets. The results demonstrate that co-movements are higher toward the end of the sample period than in the early phase. The stock markets of Argentina, Brazil, Chile, and Peru are closely and strongly connected within the region followed by Colombia, whereas Venezuela is least connected with the group.Practical implicationsThe implication is that foreign investors may benefit from the reduction of the risk by adding the stocks to their investment portfolio.Originality/valueThe unique features of the paper include a large sample of national stock returns with updated time series data set that reveals the time series properties and empirical evidence on volatility testing. Unlike other studies, this paper uncovers the relation between the stock markets within the same region facing the same market condition.

Dynamic Volatility Linkages between Developed and Emerging Stock Markets: A MMV-GARCH Approach

This paper investigates the short-run and long-run volatility linkage structures among developed and emerging stock markets using a multivariate multiplicative volatility GARCH (MMV-GARCH) model, which fulfills the assumption of a constant unconditional covariance matrix. The empirical results show that in the long-run volatility linkages, both developed and emerging markets are affected by the subprime mortgage crisis, but the developed stock markets are more sensitive to global financial perturbations. Moreover, the concern that the volatility linkages in stock markets are more significant after the subprime mortgage crisis is unfounded. In the short-run volatility linkages, the developed stock markets present stronger volatility correlation than the emerging markets.

Volatility Transmission between Oil and LME Futures

This paper investigates the volatility transmission between oil and base metals to assess the possibility of hedge strategy across commodity markets. In order to identify the volatility linkage of oil to the base metals, the bivariate GARCH model is applied using daily returns data period over 2000-2016. It is found that evidence of volatility transmission between oil and base metals is somewhat strong with a 1% significant level. This result suggests the investment idea of commodity hedging strategy of cross-market is important.

Implied volatility linkages between the U.S. and emerging equity markets: A note

This paper investigates stock market integration among the U.S. and two leading emerging markets—China and Brazil—using their implied volatility indexes published by the Chicago Board of Options Exchange (CBOE). Employing ARDL bound tests, we find strong evidence of long-run transmission of uncertainty from the U.S. market to other markets. Additionally, results from a bivariate VAR-GARCH model indicate high correlations among the equity markets, which may diminish the gains from portfolio diversification between the U.S. market and the emerging markets under study. Finally, the Toda-Yamamoto version of the Granger causality test also suggests significant links among the volatility indexes under study.

Volatility Spillover from the Fear Index to Developed and Emerging Markets

ABSTRACTThis article examines cross-market volatility linkages among the fear index (VIX), the developed-market index (VXEFA), and the emerging-market index (VXEEM). Analysis on the first moments of volatilities reveals that the fear index has a leading role and has information content for VXEFA and VXEEM. A shock to the fear index spillovers to VXEFA and VXEEM and contributes 57.07% and 63.77% to their shocks, respectively. Further analysis on the second moments of volatilities confirms that the volatility indices are highly dynamically correlated while the fear index drives the correlation dynamics with the VXEEM. Correlations increase in turbulent periods and decrease in tranquil periods.

REVISITING THE SIZE EFFECT IN THE BOVESPA

ABSTRACT The size effect has been analyzed in numerous stock markets using different approaches. However, there are few studies focused on its practical applicability. In this context, the aim of this study is two-fold. First, we examine price and volatility linkages among large, medium, and small firms employing a multivariate VAR-BEKK model. Second, we provide the out-of-sample performance of optimal portfolios constructed on the basis of time-varying return and volatility forecasts from this specification approach. Our overall results show that optimal portfolios are primarily composed of medium and small firms. Moreover, our findings reveal that using this technique, it is possible to reduce risk and outperform the naïve rule, which is usually employed by foreign investors interested in the Brazilian stock market. These findings are relevant not only for academics but also for practitioners because it is important an in-depth knowledge of stock market patterns in order to develop correct trading strategies.

Volatility Spillovers and Linkages in Asian Stock Markets

ABSTRACTDiebold–Yilmaz spillover indexes are computed for weekly return volatilities based on daily benchmark stock indexes of the US, the UK, and 10 Asian countries. We found (i) the strengthening of overall volatility spillovers is not a temporary surge but persisted after the crisis; (ii) the susceptibility of individual Asian stock markets to inward volatility transfers is linked to its degree of openness; and (iii) the Asian bourses are becoming more important emitters of financial shocks since the crisis. Rolling regressions on volatility linkages reveal the relative dominance of the US over the Japanese and Chinese bourses, and the level of influence on Asian stock markets from the Chinese bourse has risen to that of Japan.

On the relationship between oil and equity markets: evidence from South Asia

PurposeThe purpose of this paper is to investigate the volatility linkage between global oil market and major South Asian equity markets.Design/methodology/approachIn order to serve the purpose, the authors employ a recently developed vector autoregressive-generalized autoregressive conditional heteroskedastic model to examine whether shocks and volatility spill over from the oil market to various equity markets under consideration.FindingsThe findings of the empirical analysis suggest that all the markets studied do receive volatility from the oil market. Not surprisingly, the authors do not find any significant evidence of volatility transmission from the equity markets to the global oil market. Additionally, while computing the optimal portfolio weights and hedge ratios, the authors document that inclusion of oil in the portfolio of stocks tends to reduce the risk of the resultant portfolio.Originality/valueFully original.

Modeling volatility linkages between Shanghai and Hong Kong stock markets before and after the connect program

Based upon ARMA-t-BEKK-AGARCH models, this paper investigates the volatility linkages between Shanghai and Hong Kong stock market before and after the Program. Shocks spillover is found to be unidirectional from Hong Kong to Shanghai market before the Program and after the Program. Volatility transmission persistence bears the major change of volatility linkage between the two markets; it changes from being significantly bidirectional before the Program to be insignificant thereafter. Asymmetries of shocks spillover are also identified between the two markets both before and after the Program. Dynamic conditional variance and covariance matrices are examined and used to construct hedge ratios and portfolio weights. Finally, correspondent suggestions are given for investors and policy makers.

Intensity of Volatility Linkages in Islamic and Conventional Markets

Characteristics of Islamic finance, such as a smaller set of shared information and a lower degree of cross-market hedging, reduce volatility linkages (correlations) between Islamic and conventional stocks, bonds and bills. We use a stochastic volatility model in a Generalized Methods of Moments framework as well as other volatility proxies to estimate volatility linkages. We are the first to document that including at least one Islamic asset lowers volatility linkages by up to 7.17 percentage points, after controlling for country and asset-specific characteristics. Results are stronger during financial crises and are not driven by the oil sector.

Oil and non-energy commodity markets: An empirical analysis of volatility spillovers and hedging effectiveness

AbstractAlthough a large number of empirical papers have examined the price spillover in global oil and non-energy commodity markets, very little is known about the volatility transmission between these two markets. The present study aims to conceal this gap by investigating the volatility cross effects between oil and three different non-energy commodity markets. Using the bivariate VAR-GARCH models, we do not find any evidence of volatility linkage between oil and agricultural product markets during the sample period used. We, however, document that oil market sends volatility to both metal and non-energy aggregate markets. This finding is not surprising, since petroleum-related products are one of the major production inputs in metal industries and hence the production process of metals largely depends on the crude oil market. Since various financial assets are traded on the basis of commodity markets, our results are beneficial for portfolio diversification and hedging decisions. Policy-makers could a...

Co-movement measure of information transmission on international equity markets

Recently, Bhatti and Nguyen (2012) used EVT and various stochastic copulas to study the cross-country co-movements diversification and asset pricing allocation. Weiss (2013) observed that Dynamic Conditional Correlation (DCC) models outperform various copula models. This paper attempts to contribute to the literature on multivariate models for capturing forward and backward return co-movement, spillover effects and volatility linkages. It reflects cross-country forward and backward co-movements more clearly among various coupled international stock markets relating to information transmission and price discovery for making investment decisions. Given the reality of fat-tail or skewed distribution of financial data, this paper proposes the use of VECM-DCC and VAR-DCC models which capture dynamic dependences between the Australian and other selected international financial stock markets. We observe that the return co-movement effects between Australian and Asian countries are bidirectional ((AUS ↔ Hong Kong), (AUS ↔ Japan)) with the exception of Taiwan (AUS → Taiwan). We also observe that the volatility spillover between the Australian and both the UK and the US markets are bidirectional with a larger volatility spillover from both toward the AUS market. Further, the UK market has a higher volatility spillover on the Australian market compared to the US market and the US market has a higher volatility spillover on the UK than that of the Australian market.

Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models

Objective of this study is to empirically investigate the time varying co-movements between crude oil and Indian stock market returns both at aggregate and sector level. This study uses weekly closing prices for Brent Crude, BSE-Sensex and seven sector indices of Bombay Stock Exchange namely Automotive, Energy, Financial, Industrial, Metal, Oil & Gas and Power as data input. The data span of this study runs from January 1, 2006 to Feb 28, 2015, which encompasses the booming, recessionary and the recovering phase of global as well as Indian economy. The paper deploys VAR-DCC-GARCH framework. Three versions of GARCH namely standard, threshold and exponential and both symmetric and asymmetric versions of dynamic contemporaneous correlations have been used. Results of the study indicate that direct volatility spill over from oil market to Indian stock market is not significant at the aggregate level; however, it is significant in case of auto, power and finance sector. Parameter of dynamic correlations and volatility were significant thereby providing empirical evidence of the time varying differential dependence of Indian stock sector indices on oil price fluctuations. Outcomes of this study highlights that investors attempting to diversify their investments should always consider dynamic volatility and correlation linkages so as to maximize returns and minimize risk.

Multivariate market risk evaluation between Malaysian Islamic stock index and sectoral indices

Without an efficient financial risk management, it may cause massive consequences to a financial institution as well as individual. Therefore, developing a methodology which gives precise estimates to reduce the exposure of risk to a minimum is of great importance. This paper uses an asymmetric BEKK-GARCH model to examine the return and volatility linkages between the FTSE Bursa Malaysia Emas Shariah (FBMS) index and the sectoral indices under a normal market. The findings suggest that the FBMS plays a leading role in the mean return spillover effect. There is a strong evidence of significant transmission of past shocks, volatilities and leverage effects are observed on the current conditional variance-covariance in all the pair-wise models. These empirical results are helpful in quantifying the cross-market risk evaluation, risk minimizing weight and cross-market hedge ratio for strategizing appropriate portfolio selection.