Variance Spillovers Research Articles

Quantile-based spillover connectedness among stochastic volatilities of ESG equities, Islamic and conventional stocks with implications for portfolio management

PurposeThis study aims to investigate the relationship between stock markets, environmental, social and governance (ESG) factors and Shariah-compliant in an integrated framework.Design/methodology/approachThe authors employ the multivariate factor stochastic volatility (mvFSV) framework to extract the volatility of the different sectoral indices. Based on this evidence, the authors employ the quantile vector autoregressive (QVAR) approach to examine the dynamic spillover connectedness among the aforementioned indices.FindingsThe study emphasizes the following major findings: (1) significant time-varying spillover connectedness across quantiles, (2) bidirectional and asymmetric spillover effect among the ESG index and the other sectoral indices, (3) the strength of spillover connectedness is time-varying across quantiles, (4) based on the perspective of portfolio optimization, ESG market is a significant strong forecasting contributor to conventional and Shariah-compliant markets, (5) overall, the findings point out serious quantile pass-through effect among ESG index and the other sectoral indices during the COVID-19 health crisis.Originality/valueThis study extends the previous literature in the following ways. First, to the best of the researchers’ knowledge, none of the existing studies have investigated the relationship between stock markets, ESG factors and Shariah-compliant in an integrated framework. Second, this study extends the previous scholarships by applying the mvFSV. Third, the authors propose a new rolling version to estimate dynamic spillovers, namely the rolling-window quantile VAR method. This approach provides a great advantage in computing the dynamics of return and variance spillover between variables in terms not only of the overall factor but also of the net (pairwise) aspect.

Economic policy uncertainty and industry risk on China’s stock market

We propose a dynamic mixture Copula with time-varying weight, which is endowed with generalized autoregressive score dynamics. Based on this model, we portray the lower-tail dependence between the return of WIND first-level industry and CSI-300 index as a proxy variable for the industry risk in China’s stock market, and use the VAR-GARCH-in-mean model based on BEKK-GARCH to deconstruct the different impact of the economic policy uncertainty (EPU) on industry risk of the first and second moments in terms of four policy categories, namely fiscal policy, monetary policy, trade policy, and foreign exchange rate and capital account policy. The results are followed. Firstly, the risk of Consumer Discretionary is averagely the highest, while the risk of Utilities remains the lowest. Secondly, category-specific EPU has no significant mean spillover to the risk of overall industries, while the variance spillover is significant for all the cases. Thirdly, except for Real Estate, the GARCH-in-mean effect is not significant of EPU on industry risks. Further more, all those three kinds of impact show industrial heterogeneities. To avoid systemic risks, we advise that the issue of economic policy should be forward-looking, consistent, and targeted, especially for sensitive industries.

Estimation of the spillover effect between patents and innovation using the GARCH–BEKK model

AbstractThis study examines the mean and variance spillovers between patents filed and total factor productivity in Pakistan during the period lasting from 1964 to 2015. Using the multivariate generalized autoregressive conditionally heteroskedastic–Baba, Engle, Kraft and Kroner (GARCH–BEKK) model, we find no evidence of mean spillover effects between patents filed and productivity growth. However, the results support the existence of the variance spillover effect, which illustrates that the innovations may affect productivity in the long‐run. Moreover, bidirectional causality in the mean and variance between innovation and productivity growth is non‐existent. We find that R&D/GDP, skilled labour force and economic freedom are the significant factors affecting technological advancements in the country. We also determine that R&D/GDP and economic freedom are the important factors affecting patent activities in Pakistan. Our findings suggest that the government needs to emphasize the regulations of the patent system to safeguard the interests of investors, which ultimately promotes economic growth.

Measuring Spot Variance Spillovers when (Co)variances are Time‐varying – The Case of Multivariate GARCH Models

AbstractWe propose global and disaggregated spillover indices that allow us to assess variance and covariance spillovers, locally in time and conditionally on time‐t information. Key to our approach is the vector moving average representation of the half‐vectorized ‘squared’ multivariate GARCH process of the popular BEKK model. In an empirical application to a four‐dimensional system of broad asset classes (equity, fixed income, foreign exchange and commodities), we illustrate the new spillover indices at various levels of (dis)aggregation. Moreover, we demonstrate that they are informative of the value‐at‐risk violations of portfolios composed of the considered asset classes.

Testing the Dynamic Linkages of the Pakistani Stock Market with Regional and Global Markets

This article examines the dynamic linkages between Pakistan’s emerging stock market and (i) the US market and (ii) the regional markets of India and Japan. Using data for the daily returns and volatility spillovers of three market pairs (Pakistan-US, Pakistan-Japan and Pakistan-India), the study estimates a series of bivariate asymmetric VARMA(1,1)-GARCH(1,1) models. It also fits multivariate asymmetric VARMA(1,1)-GARCH(1,1) models for two groups of markets: Pakistan-India-US and Pakistan-India-Japan. Based on the mean spillovers, the results suggest that the global and regional equity markets (Granger) cause the Pakistani market. There are unidirectional volatility spillovers to Pakistan from the US and Japan, while India is the only regional market with a significant cross-asymmetric effect on Pakistan. In the multivariate case, the regional and global markets have significant joint mean and variance spillovers and asymmetric effects on the Pakistani market. This indicates a weak degree of integration between the Pakistani market and the global and regional markets, implying that local risk factors – either firm-specific or country-specific – explain the expected returns on investment in the Pakistani stock market.

Measuring Spot Variance Spillovers When (Co)Variances are Time-Varying - The Case of Multivariate GARCH Models

We propose global and disaggregated spillover indices that allow us to assess variance and covariance spillovers, locally in time and conditionally on time-t information. Key to our approach is the vector moving average representation of the half-vectorized 'squared' multivariate GARCH process of the popular BEKK model. In an empirical application to a four-dimensional system of broad asset classes (equity, fixed income, foreign exchange and commodities), we illustrate the new spillover indices at various levels of (dis)aggregation. Moreover, we demonstrate that they are informative of the value-at-risk violations of portfolios composed of the considered asset classes.

A variance spillover analysis without covariances: What do we miss?

We evaluate the relevance of covariances in the transmission mechanism of variance spillovers across the US stock, US bond and gold markets from July 2003 to December 2012. For that purpose, we perform a comparative spillover analysis between a model that considers covariances and a model that considers only variances. Our results emphasise the importance of covariances. Including covariances leads to an overall increase of the spillover level and detects the beginnings of the financial crisis and of the US debt ceiling crisis earlier than the spillover measure that considers only variances. Even for the low-dimensional system that we consider, one misses important variance spillover channels when covariances are excluded.

On the spillovers between patents and innovation in Japan

This article investigates the mean and variance spillovers between patent applications and total factor productivity (TFP) in Japan. First, we find a stationary cointegrating relationship between patent applications and TFP in the long run. This result suggests an increase in patent applications directly leads to an increase in innovation. Second, we also obtain evidence of significant bidirectional causality in mean and variance between patent applications and TFP. These finding indicates that there exists a bidirectional mean and volatility spillover effects between patents and innovations in the Japanese context. The results of our investigation can assist policymakers in taking decisions regarding the regulation of Japan’s patenting system.

A Variance Spillover Analysis Without Covariances: What Do We Miss?

We evaluate the relevance of covariances in the transmission mechanism of variance spillovers across the US stock, US bond and gold markets from July 2003 to December 2012. For that purpose, we perform a comparative spillover analysis between a model that considers covariances and a model that considers only variances. Our results emphasize the importance of covariances. Including covariances leads to an overall increase of the spillover level and detects the beginnings of the financial crisis and of the US debt ceiling crisis earlier than the spillover measure that considers only variances. Even for the low-dimensional system that we consider, one misses important variance spillover channels when covariances are excluded.

Switching volatility and cross-market linkages in public property markets

The primary contribution of this study is to examine the changes in cross-market relationship in international public property markets from a volatility regime switching perspective from January 1990 to January 2012. We find that global developed public property markets can be adequately characterised by a SWARCH model. In particular, most of the persistence in real estate stock price volatility can be attributed to the persistence of low-, medium- and high-volatility regimes in international developed public property markets. Moreover, there is a significant volatility increase during the crises periods for all markets examined. However, the identified high-volatility regime appears short-lived. Based on the SWARCH results, we find that the dynamic linkages among the markets are positively dependent on volatility regime. Specifically, the market correlations, foreign market influence, aggregate variance spillover index and variance–covariance matrix have intensified as market volatility increases during this period. Moreover, the evolution of the cross-market linkages among the sample public property markets is influenced significantly by both a time trend and a volatility regime factor that are independent of the influences of the global stock market and national stock markets. Our results imply that risk-reduction via international diversification in public property markets may only hold true in low-volatility periods. Consequently, portfolio managers need to understand and implement volatility state-dependent optimal asset allocation in order to better advise their clients.

Measuring Persistence in Volatility Spillovers

This paper analyzes volatility spillovers in multivariate GARCH-type models. We show that the cross-effects between the conditional variances determine the persistence of the transmitted volatility innovations. In particular, the effect of a foreign volatility innovation on a conditional variance is even more persistent than the effect of an own innovation unless it is offset by an accompanying negative variance spillover of sufficient size. Moreover, ignoring a negative variance spillover causes a downward bias in the estimate of the initial impact of the foreign volatility innovation. Applying the concept to portfolios of small and large firms, we find that shocks to small firm returns affect the large firm conditional variance once we allow for (negative) spillovers between the conditional variances themselves.

Measuring Persistence in Volatility Spillovers

This paper analyzes volatility spillovers in multivariate GARCH-type models. We show that the cross-effects between the conditional variances determine the persistence of the transmitted volatility innovations. In particular, the effect of a foreign volatility innovation on a conditional variance is even more persistent than the effect of an own innovation unless it is offset by an accompanying negative variance spillover of sufficient size. Moreover, ignoring a negative variance spillover causes a downward bias in the estimate of the initial impact of the foreign volatility innovation. Applying the concept to portfolios of small and large firms, we find that shocks to small firm returns affect the large firm conditional variance once we allow for (negative) spillovers between the conditional variances themselves.

Equity and CDS sector indices: Dynamic models and risk hedging

The recent financial crisis had a substantial impact on equity and bond markets, as well as on the performances of managed portfolios which have been hit by the decrease of both indices. Nevertheless, the availability of indices monitoring the equity market volatility, the VIX index, credit markets default risk, and CDS indices, allows for the construction of hedging strategies. In this paper, we take the point of view of an equity investor who wants to hedge the equity risk by taking positions either on the VIX index or on CDS indices. In deriving the hedge ratios, we consider the joint dynamic of variables taking into account mean relations, variance spillovers, and asymmetry, as well as correlation changes over time. Our analysis is based on sectorial indices and shows the advantages of hedging and the impact of a model specification.

Equity and CDS Sector Indices: Dynamic Models and Risk Hedging

The recent financial crisis had a substantial impact on equity and bond markets, as well as on the performances of managed portfolios which have been hit by the decrease of both indices. Nevertheless, the availability of indices monitoring the equity market volatility, the VIX index, credit markets default risk, and CDS indices, allows for the construction of hedging strategies. In this paper, we take the point of view of an equity investor who wants to hedge the equity risk by taking positions either on the VIX index or on CDS indices. In deriving the hedge ratios, we consider the joint dynamic of variables taking into account mean relations, variance spillovers, and asymmetry, as well as correlation changes over time. Our analysis is based on sectorial indices and shows the advantages of hedging and the impact of a model specification.

Market linkages, variance spillovers, and correlation stability: Empirical evidence of financial contagion

To model the contemporaneous relationships among Asian and American stock markets, a simultaneous equation system with GARCH errors is introduced. In the estimated residuals, the correlation matrix is analyzed over rolling windows and using a correlation matrix distance, which allows a graphical analysis and the development of a statistical test of correlation movements. Furthermore, a methodology that can be used to identify turmoil periods on a data-driven basis is presented. The previous results are applied in the analysis of the contagion issue between Asian and American stock markets. The results show some evidence of contagion, and the proposed statistics identify, on a data-driven basis, turmoil periods consistent with the ones currently assumed in the literature.

Risk Contagion Among International Stock Markets

We develop a model of stochastic volatility with jump to analyze how the local equity markets of the European countries are affected by the regional equity market (other European equity markets) and the US equity market. Our approach simultaneously investigates all the three aspects of the interactions between markets, i.e. the correlation, the variance spillover and the jump spillover. We separate three sources of shocks to each European equity market; the shocks from the US market, the shocks from the regional market and the idiosyncratic or local shocks. The key advantage of this approach comparing to the earlier approaches is that it enables us to identify jumps and investigate risk spillover during distress periods. The model allows for time-varying parameters by relating the spillover parameters to the countries' degree of integration. We use Wavelet to filter out all the short-term variations in the variables measuring country integration. Our results show that the US contributions to the country variances lie in general below the contributions from the regional (European) market. We also find that the impact of the regional market on the local European equity markets has increased in pace with the development of the European Union. Finally, the relationship between the correlation and the estimated variances show that a US investor does not gain much from diversification abroad in high volatility periods, since the uncertainty in the US market generally contaminates the other markets. Nevertheless, for most European countries, the relative benefit of the international diversification increases in the high volatility periods.

Market Linkages, Variance Spillovers and Correlation Stability: Empirical Evidences of Financial Contagion

We propose a simultaneous equation system with GARCH errors to model the contemporaneous relations among Asian and American stock markets. On the estimated residuals, we evaluate the correlation matrix over rolling windows and introduce a correlation matrix distance, which allows both a graphical analysis and the development of a statistical test of correlation movements. Furthermore, we introduce a methodology that can be used for identifying turmoil periods on a data-driven basis. We employ the previous results in the analysis of the contagion issue between Asian and American stock markets. Our results shows some evidence of contagion and the proposed statistics identifies, on a data-driven basis, turmoil periods consistent with the ones currently assumed in the literature.

Global regional sources of risk in equity markets: Evidence from factor models with time-varying conditional skewness

We examine the influence of global and regional factors on the conditional distribution of stock returns from six Asian markets, using factor models in which unexpected returns comprise global, regional and local shocks. The models allow for conditional heteroskedasticity and time-varying conditional skewness, and are used to measure mean, variance, and skewness spillovers. We find that incorporating time-varying conditional skewness improves the fit of our spillover models, and can alter measurements of variance spillovers. However, time-varying conditional skewness is mostly a local phenomenon; with exceptions, there is little spillover in skewness from global and regional factors.

Variance Spillover and Skewness in Financial Asset Returns

AbstractBond and stock returns have been observed in the literature to exhibit unconditional skewness and temporal persistence in conditional skewness. We demonstrate that observed persistence in conditional third central moments can be due to the spillover of conditional variance dynamics. The confounding of true skewness and a variance spillover effect is problematic for financial modeling. Using market data, we empirically demonstrate that a simple standardization approach removes the variance‐induced skewness persistence. An important implication is that more parsimonious return and asset pricing models result if skewness persistence need not be modeled.

Variance Spillover and Skewness in Financial Asset Returns

Bond and stock returns have been observed in the literature to exhibit unconditional skewness and temporal persistence in conditional skewness. We demonstrate that observed persistence in conditional third central moments can be due to the spillover of conditional variance dynamics. The confounding of true skewness and a variance spillover effect is problematic for financial modeling. Using market data, we empirically demonstrate that a simple standardization approach removes the variance-induced skewness persistence. An important implication is that more parsimonious return and asset pricing models result if skewness persistence need not be modeled.