Magnitude Of Volatility Spillovers Research Articles

Connectedness and directional spillovers in energy sectors: international evidence

ABSTRACT This paper provides a comparative analysis of how the energy-sector stocks of 20 regional blocs (Americas, Australasia, BRIC, Southeast Asia, Scandinavia, Southern Europe, Far East, Europe, European Union, Emerging Europe, Asia, G7, G12, Economic and Monetary Union (EMU), CCARBNS, Latin America, North America, PIIGS, Asia-Pacific and NORCS) are connected from 5 July 1994 to 21 April 2020. It uses various techniques: Diebold and Yilmaz (2014)(DY 2014, hereafter) spillover indices and TVP-VAR, LASSO-VAR. Our main results are as follows: First, the DY approach results show that the biggest net contributor of volatility is the CCARBNS region, followed by the G12 and G7 regions, while the biggest receiver of volatility is the Southeast Asia region. Second, the TVP-VAR and LASSO-VAR results reveal that Scandinavia, Far East, and America’s regions are net receivers of energy shocks, with net transmitters being CCARBNS, G7, G12 and Emerging European regions. Third, during the 2007–2008 financial crisis and recent COVID-19 outbreak, energy stock market spillovers have reached unprecedented high levels. Fourth, the world policy uncertainty greatly influenced the magnitude of volatility spillovers across regional energy stock markets.

The effects from the international crude oil returns to Asian frontier oil and gas company stock returns

Asian frontier markets present compelling investment opportunities for investors seeking higher returns and low correlation with traditional assets. As such, it is important for financial market participants to understand the volatility transmission mechanism across these markets in order to make better portfolio allocation decisions. This study investigates the magnitude of return and volatility spillovers from the international crude oil markets on the Asian frontier oil and gas stock markets. In particular, we construct mean return and volatility spillover models to discuss whether regional (DSE, CSE, HNX, HOSE) and global (ICE) market impacts are crucial for the determination of oil & gas stock returns in Bangladesh, Sri Lanka, and Vietnam by employing ARMA(1,1)-GARCH(1,1) model. Using daily returns from January 4, 2010 to December 31, 2019, the findings of this paper show that the Brent oil and WTI crude oil markets influence the Sri Lanka and Vietnamese oil and gas stock markets. WTI price changes, however, have a relatively minor impact on Sri Lanka companies. For Bangladesh, it is noticeable that none of the spillover effects is statically significant. The results are explained by different levels of the reform process in the energy sector as well as by the importance of oil in these markets. In general, these frontier markets, especially the Bangladesh and Sri Lanka may offer promising diversification benefits due to low correlations with developed equity markets. These results are important for economic policymakers and investors in understanding the magnitude of volatility spillover effects of the international crude oil on these markets. Investors can use this information to make better portfolio allocation decisions to reduce risks and enhance returns.

Volatility interdependence on foreign exchange markets: The contribution of cross-rates

• The volatility interdependence of 21 bilateral exchange rates among 7 major currencies is examined. • We focus on the volatility interdependence between the USD (EUR) rate and its cross-rate. • The spillover index is estimated to identify the direction and magnitude of volatility spillovers. • Wavelet analysis is used to identify localized correlations of volatilities in time-frequency space. • We find significant contributions of cross-rates to the volatility interdependence in FX markets.

VOLATILITY SPILLOVER BETWEEN SPOT AND FUTURES MARKET OF HIGHLY TRADED COMMODITIES IN INDIA: The DCC-GARCH Approach

This study intends to examine the volatility spillover effects and measure the time-varying correlations between futures and spot prices of thirteen highly traded commodities traded on Multi Commodity Exchange (MCX) of India. The research uses Exponential GARCH proposed by Nelson (1991) to explore the direction and magnitude of spillover effects between futures and spot commodity market and employs Dynamic Conditional Correlation (DCC) GARCH proposed by Engle (2002) to demonstrate the time varying conditional correlation between heteroscedastic coefficients of the futures and spot markets. Empirical results show that significant and asymmetric bi-directional volatility spillover effects exist in case of most of the selected commodities, even though, the magnitude of volatility spillover is found larger in the direction from futures market to spot market. The dynamic correlation between the conditional variance of the spot and future markets is found to be significant in case of all the commodities except Silver and Copper. It proves that significant volatility spillover effect is present between spot and futures markets of selected commodities. Understanding of volatility transmission and interrelationship between spot and futures commodity market will help investors make right investment decisions, portfolio optimization and financial risk management. Policy makers and regulators can use this knowledge in planning and implementing appropriate regulatory framework. Much of the earlier research focuses on inter market volatility spillover taking into consideration two or more different financial markets. This study focuses on intra market volatility spillover by studying the interactions of spot-futures prices of commodities. Also, considering the time-varying nature of conditional correlations, this study employs EGARCH and multivariate GARCH (DCC) to capture the volatility spillover effects instead of univariate GARCH or standard linear VAR models.

On the volatility transmission between oil and stock markets: a comparison of emerging importers and exporters

This paper examines the volatility transmissions between the oil and stock markets by performing causality-in-variance tests across a number of emerging (oil) importing and exporting nations. The volatility spillover causality tests generally rule out country-to-oil effects, suggesting unidirectional volatility transmissions from oil prices to emerging stock markets, particularly in the case of the net exporting nations of Kuwait, Saudi Arabia and UAE. We also observe significant volatility spillovers from oil prices to emerging importers during the post-global financial crisis period. The findings suggest that the information on oil market volatility combined with the magnitude of volatility spillovers can be utilized towards modeling and monitoring volatility shocks in emerging stock markets.

Onshore and offshore market for Indian rupee: recent evidence on volatility and shock spillover

The article empirically examines the onshor-offshore linkages of the Indian rupee using recently developed multivariate GARCH technique. The empirical results show that the offshore non-deliverable forward market does not have mean spillover impact on onshore spot, forward and futures markets while shocks and volatilities in the non-deliverable forward market influence the onshore markets. A key finding of the study is that the magnitude of volatility spillover from non-deliverable forward to spot market has accentuated after the introduction of currency futures in India. This development could be attributable to large arbitrage between futures and non-deliverable forward market in the more recent period. The finding has critical implications for exchange rate policy and management in the Indian context. There is need for close monitoring of both the onshore and offshore markets.

Cross-border transmission of stock price volatility: evidence from the overlapping trading hours

Using high-frequency (5-minute returns) data, the transmission pattern of intraday volatility among three international stock markets (i.e., the United States, the United Kingdom, and Canada) during their overlapping trading hours (9:30–11:30 a.m. New York time). The major findings are as follows. First, the conditional variance of a domestic market is affected not only by the volatility surprises of its own market, but also by those of foreign markets. This finding holds for the United States as well as for Canada and the United Kingdom, implying that the information contained in the volatility surprises of each national market is clearly transmitted to other national markets. The volatility spillover is not unidirectional. Second, the magnitude of volatility spillover does not decrease monotonically as the lag length increases, indicating that the effect of a foreign volatility shock on the conditional variance of the domestic market tends to persist.