State transformation of information spillover in asset markets and effective dynamic hedging strategies

This paper aims to develop a strategy to effectively and dynamically hedge risk by considering regime transitions of spillover effects between assets. We take six assets (stocks, bonds, real estate, currency exchange, crude oil, and gold) that are commonly used to construct investment portfolios as examples and analyze asset price data between September 2002 and January 2022. In doing so, we aim to examine the information spillover of different asset prices in both bear and bull market environments to determine whether state transformation affects dynamic hedging effectiveness. Using Markov-Switching Factor-Augmented Vector Autoregression (MS-FAVAR), we construct a regimen-switching model using variables from finance and economic conditions as endogenous variables to define the state transformations of the information spillover. Empirical results reveal that the MS-FAVAR model highlights changes in information spillover during a financial crisis/economic recession. Using dynamic-weighted hedging portfolios constructed with different indicators, we find that hedging effectiveness and volatility vary depending on the state of information spillover between different asset markets and that bear markets significantly impacted hedging effectiveness. Results also show that the panic sentiment (the fear index) explains the probability of a bear market. It is suggested that the state transformation of information spillovers should be monitored periodically, and hedging portfolios should be dynamically adjusted (bear or bull market) with shifting fear sentiment.     

Dynamic volatility spillovers across oil and natural gas futures markets based on a time-varying spillover method

This paper analyzes dynamic volatility spillovers between four major energy commodities (i.e., crude oil, gasoline, heating oil and natural gas) in the oil-natural gas future markets. We construct a time-varying spillover method by combining the TVP-VAR-SV model and the spillover method of Diebold and Yilmaz (2009, 2012, 2014). We use the spillover method to obtain time-varying total, directional and pairwise volatility spillover indices. Our results summarize as follows: (1) The volatility spillover indices present peaks and troughs during some periods, such as shale gas revolution, financial crisis, and oil price crash; (2) After the U.S. shale gas revolution, the size of volatility spillover from natural gas future market has reduced sharply, but volatility doesn't decouple from the other three oil future markets; (3) The directional spillover is asymmetric. The crude oil and heating oil futures market are main net transmitter of volatility risk information, while the gasoline and natural gas futures markets are the net receiver; (4) For natural gas future market, the pairwise volatility spillover from crude oil future market has the most significant influence.     

Extreme quantile spillovers and drivers among clean energy,electricity and energy metals markets

This paper examines return and volatility spillover effects among the clean energy (electric vehicles, solar and wind), electricity and 8 energy metals (silver, tin, nickel, cobalt, lead, zinc, aluminum and copper) markets and their drivers under the conditions of the mean and extreme quantiles. The results show moderate spillovers among the clean energy, electricity and energy metals markets, and greater connectivity among the three markets under extreme quantile conditions. Among them, the clean energy markets always play the role of the transmitter, and the electricity market always plays the role of the receiver of spillover effects. In addition, the return and volatility spillovers among the three markets have remarkable time-varying features, and they increase dramatically when extreme events occur, especially under extreme quantile conditions. Finally, we reveal the drivers of return and volatility spillovers among these markets by the OLS and quantile regression methods. The COVID-19 and the Arca Tech 100 (PSE) index are found to be important drivers.     

Returns and volatilities of energy futures markets: Roles of speculative and hedging sentiments

This study examines how speculative and hedging sentiments influence the returns and volatilities of energy futures markets. We construct speculative and hedging sentiment indices based on the weekly data of fund and commercial positions of four energy futures: crude oil, heating oil, gasoline, and natural gas, traded on the New York Mercantile Exchange (NYMEX) from 15 January 2013 to 5 February 2019. Our study demonstrates that speculative sentiment generates greater market fluctuations in the energy futures markets than hedging sentiment; and, further, speculative sentiment stimulates a reversal effect on the returns of crude oil futures. Moreover, speculative sentiment exerts positive systemic risk compensation on the four futures' returns, whereas hedging sentiment alleviates volatilities in the energy futures markets. Most notably, distinguishing it from the leverage effect in stock markets, the speculative sentiment in the energy futures markets is influenced more by good than by bad news; while hedging sentiment exhibits emotional neutrality, as opposed to its impact on stock markets as reported in the literature. Additionally, the positive hedging sentiment in crude oil futures demonstrates significant systemic risk compensation, whereas the three other futures do not have an influence, confirming the prevalence of speculation in hedging transactions in crude oil futures. Our further analysis shows cross-market volatility spillover effects, among which speculative sentiment inherent in crude oil futures causes volatility spillovers to the three other futures, while hedging sentiment has no such effect. Our study has implications for overseeing international energy futures markets, providing regulators with evidence that will facilitate the development of effective strategies to strengthen market supervision.     

Hedging with Chinese Aluminum Futures: International Evidence with Return and Volatility Spillover Indices Under Structural Breaks

This paper examines the hedging performance of the Shanghai futures market, with the London futures market acting as the channel for volatility spillover. Taking into consideration structural change, basis effects, and return and volatility spillover effects, the authors find that the estimated hedging performance is not improved. Their findings suggest that the effectiveness of the hedging performance of aluminum futures contracts in China is not affected by the magnitude or direction of return and volatility spillovers. Therefore, even when the magnitude and direction of volatility spillover from other markets can be correctly predicted, the hedging performance of a futures contract cannot be significantly improved. This paper uses precise measures of return spillovers and volatility spillovers based directly on the framework of vector autoregressive variance decompositions. The study also includes an analysis of both crisis and noncrisis episodes, with modeling on bursts in spillovers.     

Which time-frequency domain dominates spillover in the Chinese energy stock market?

Previous studies detected the spillover relations among stocks and identified the spillover roles of stocks. However, due to the participants with different dealing frequencies, the spillover effects in the stock market present multiscale features, then which time-frequency domain dominates the spillover in the stock market? Take Chinese energy stocks as an example, this paper examines the return spillover effects of the energy stock market under each time-frequency domain. We find significant return spillover in the Chinese energy stock market under different time scales, and the spillover effect under the time scale of 32–64 days contributes the most to the spillover in the whole energy stock market. Then we take further research on the directional spillovers, spillovers between energy stocks and spillovers between energy industries to detect who plays leading positions under each time scale. We divide the stocks into four roles, and find that it is different role that plays a leading position under each time scale. Furthermore, a small number of spillover relationships between energy stocks carry a large part of the total spillover quantities, and coal and consumable fuel-related stocks play an important role in the spillover of Chinese energy stocks. The robustness of our results is proved by additional tests with different forecast horizons. Our paper contributes to the literature by examining the multiscale spillover effect in the Chinese energy stock market, which provides references for market participants on investment horizons choosing, stocks selection and risk aversion.     

Time-Varying Spillover and the Portfolio Diversification Implications of Clean Energy Equity with Commodities and Financial Assets

This article examines the time-varying spillover and its implications on hedging and portfolio diversification for clean energy equities (WilderHill New Energy Global Innovation Index (NEX)) with technology stocks (PSE), four energy sub-indices of Standard & Poor Goldman Sachs Commodity Index (S&P-GSCI) viz., Crude oil, Brent crude oil, Gasoline and Heating oil and three major global equities indices represented by the USA, Europe, World, Dow-Jones Islamic Market Index (DJIMI) along with USD-Euro exchange rate. We find that in a mixed portfolio set-up, the inclusion of NEX in energy portfolio provides better diversification and risk reduction benefits for hedgers and portfolio managers.     

Optimal portfolio diversification with a multi-chain regime-switching spillover GARCH model

A multi-chain regime-switching spillover GARCH (MCRSSG) model is proposed for optimal portfolio diversification. MCRSSG specifies the within-regime time-varying correlation via a multi-chain state-dependent spillover factor and quantifies the magnitude of volatility spillovers under different regime combinations. MCRSSG is applied to investigate the diversification benefit of precious metals, crude oil, and financial securities for the Korean stock market at a sector level. The empirical results reveal that the Dow Jones Islamic market US total return index provides the best diversification benefit and MCRSSG exhibits superior effectiveness for risk-adjusted return and reward-to-semivariance ratio.     

Return and Volatility Spillovers Between Large and Small Stocks in the UK

Abstract:  This paper investigates return and volatility spillover effects between the FTSE 100, FTSE 250 and FTSE Small Cap equity indices using the multivariate GARCH framework. We find that return and volatility transmission mechanisms between large and small stocks in the UK are asymmetric. In particular, there are significant spillover effects in both returns and volatility from the portfolios of larger stocks to the portfolios of smaller stocks. For volatility, there is also evidence of limited feedback from the portfolios of smaller stocks to the portfolios of larger stocks, although sub-period analysis suggests that this is to some extent period-specific. Simulation evidence shows that non-synchronous trading potentially explains some, but not all, of the spillover effects in returns, and that it explains none of the spillover effects in volatility. These results are consistent with a market in which information is first incorporated into the prices of large stocks before being impounded into the prices of small stocks.     

An international analysis of REITs and stock portfolio management based on dynamic conditional correlation models

This paper analyzes the volatility spillovers and asymmetry between REITs and stock prices for nine countries (Australia, Belgium, Germany, Italy, Japan, The Netherlands, Singapore, the United Kingdom, and the United States) using eight different multivariate GARCH models. We also analyze the optimal weights, hedging effectiveness, and hedge ratios for REIT-stock portfolio holdings with respect to the results. The empirical results indicate that dynamic conditional correlation (DCC) models provide a better fit than the constant conditional correlation models. The DCC with volatility spillovers and asymmetry (DCC-SA) model provides a better fit than the other multivariate GARCH models. The DCC-SA model also provides the best hedging effectiveness for all pairs of REIT-stock assets. More importantly, this result holds for all cases and for all models that we consider, which means that by taking spillover and asymmetry into consideration, hedging effectiveness can be vastly improved.     

Did COVID-19 change spillover patterns between Fintech and other asset classes?

This study examines the spillover effect between financial technology (Fintech) stocks and other financial assets (gold, Bitcoin, a global equity index, crude oil, and the US Dollar) during the COVID-19 crisis. Employing daily data from June 2019 to August 2020, our empirical analysis shows that the outbreak of COVID-19 exacerbated volatility transmission across asset classes, while subsequent decreases in new confirmed cases globally reduced the intensity of these spillovers. The evidence for the USD and gold supports their safe haven properties during catastrophic events, while innovative technology products as represented by a financial technology index (KFTX) and Bitcoin were highly susceptible to external shocks. These results show that when push comes to shove, the buck stops with the USD and gold and that the exorbitant privilege enjoyed by the USD prevailed during the COVID-19 pandemic.     

Do the crude oil futures of the Shanghai International Energy Exchange improve asset allocation of Chinese petrochemical-related stocks?

The Shanghai International Energy Exchange (INE) facilitates both local and international investment in Chinese petrochemical-related stocks through local crude oil futures. This study investigates whether the Chinese emerging market can better aid investors' risk hedging and asset allocation compared to two major international developed markets–the Brent and West Texas Intermediate (WTI) crude oil futures markets—and examines the pairwise risk hedging effects and multi-asset allocation performance of INE and petrochemical-related stocks. The results show that INE has higher hedge effectiveness than Brent and WTI under pairwise hedging. Further, in multi-asset allocation, the portfolios containing INE outperform other portfolios. Overall, INE results in a better diversification effect and volatility reduction than the use of WTI crude oil futures to construct multi-asset allocation with Chinese petrochemical-related stocks. However, INE performance is inferior to Brent's in terms of constructing portfolios with oil or energy stocks. Finally, our results are robust to the five factors proposed by Fama and French (2015) in asset pricing.     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.     

Directional spillover effects and time-frequency nexus between oil,gold and stock markets: Evidence from pre and during COVID-19 outbreak

The Covid-19 crisis has been spread rapidly throughout the world so far. However, how deep and long the turbulence would depend on the success of solutions taken to deter the spread of Covid-19, the impacts of government policies may be prominent to alleviate the current crisis. In this article, we investigate the spillover effects and time-frequency connectedness between S&P 500, crude oil prices, and gold asset using both the spillover index of Diebold and Yilmaz (2012) and the wavelet coherence to evaluate whether the time-varying dynamic return spillover index exhibited the intensity and direction of transmission during the Covid-19 outbreak. Overall, the present results shed light on that in comparison with the pre-Covid-19 period, and the return transmissions are more apparent during the Covid-19 crisis. More importantly, there exist significant dependent patterns about the information spillovers among the crude oil, S&P 500, and gold markets might provide significant implications for portfolio managers, investors, and government agencies.     

Volatility spillovers between WTI and Brent spot crude oil prices: an analysis of granger causality in variance patterns over time

There has been an increase in price volatility in oil prices during and since the global financial crisis (GFC). This study investigates the Granger causality patterns in volatility spillovers between West Texas International (WTI) and Brent crude oil spot prices using daily data. We use Hafner and Herwartz’s (2006) test and employ a rolling sample approach to investigate the changes in the dynamics of volatility spillovers between WTI and Brent oil prices over time. Volatility spillovers from Brent to WTI prices are found to be more pronounced at the beginning of the analysis period, around the GFC, and more recently in 2020. Between 2015 and 2019, the direction of volatility spillovers runs unidirectionally from WTI to Brent oil prices. In 2020, however, a Granger-causal feedback relation between the volatility of WTI and Brent crude oil prices is again detected. This is due to the uncertainty surrounding how the COVID-19 pandemic will evolve and how long the economies and financial markets will be affected. In this uncertain environment, commodities markets participants could be reacting to prices and volatility signals on both WTI and Brent, leading to the detection of a feedback relation.     

Volatility spillovers between oil prices and stock sector returns: Implications for portfolio management

In this article we take a recent generalized VAR-GARCH approach to examine the extent of volatility transmission between oil and stock markets in Europe and the United States at the sector-level. The empirical model is advantageous in that it typically allows simultaneous shock transmission in the conditional returns and volatilities. Insofar as volatility transmission across oil and stock sector markets is a crucial element for portfolio designs and risk management, we also analyze the optimal weights and hedge ratios for oil-stock portfolio holdings with respect to the results. Our findings point to the existence of significant volatility spillover between oil and sector stock returns. However, the spillover is usually unidirectional from oil markets to stock markets in Europe, but bidirectional in the United States. Our back-testing procedures, finally, suggest that taking the cross-market volatility spillovers estimated from the VAR-GARCH models often leads to diversification benefits and hedging effectiveness better than those of commonly used multivariate volatility models such as the CCC-GARCH of Bollerslev (1990), the diagonal BEKK-GARCH of Engle and Kroner (1995) and the DCC-GARCH of Engle (2002).     

Transmission of Stock Returns and Volatility between the U.S. and Japan: Evidence from the Stock Index Futures Markets

In this paper, we examine the nature of transmission of stock returns and volatility between the U.S. and Japanese stock markets using futures prices on the S&P 500 and Nikkei 225 stock indexes. We use stock index futures prices to mitigate the stale quote problem found in the spot index prices and to obtain more robust results. By employing a two-step GARCH approach, we find that there are unidirectional contemporaneous return and volatility spillovers from the U.S. to Japan. Furthermore, the U.S.'s influence on Japan in returns is approximately four times as large as the other way around. Finally, our results show no significant lagged spillover effects in both returns and volatility from the Osaka market to the Chicago market, while a significant lagged volatility spillover is observed from the U.S. to Japan. This revised version was published online in August 2006 with corrections to the Cover Date.     

Exchange return co-movements and volatility spillovers before and after the introduction of euro

This paper examines return co-movements and volatility spillovers between major exchange rates before and after the introduction of euro. Dynamic correlations and VAR-based spillover index results suggest significant return co-movements and volatility spillovers, however, their extend is, on average, lower in the post-euro period. Co-movements and spillovers are positively associated with extreme episodes and US dollar appreciations. The euro (Deutsche mark) is the dominant net transmitter of volatility, while the British pound the dominant net receiver of volatility in both periods. Nevertheless, cross-market volatility spillovers are bidirectional, and the highest spillovers occur between European markets.     

Dynamic volatility spillover effects between oil and agricultural products

The strong volatility spillover between crude oil and agricultural commodity markets reduces the diversification benefits and implies costly risk management process faced by portfolio managers and agricultural producers. This paper proposes a comprehensive study of their dynamic implied volatility spillover effects after the global financial crisis 2008–2009, while considering the transition between oil volatility's regimes. By using implied volatility, our analysis emphasizes on the forward-looking information that market traders usually convey in making decisions. We employ the generalized spillover indices within a fractionally integrated VAR model to capture the dynamic patterns of the volatility spillover effects alongside the Markov Switching Autoregressive model to extract the regimes of oil. Our results show new evidence that the net volatility spillover effect from crude oil to all agricultural commodities tends to decrease when crude oil remains in its low volatility regime. Conversely, this effect experiences an increasing trend when crude oil remains in its relatively high volatility regime. A dynamic strategy that combines oil and the most balanced agricultural commodity in terms of volatility transmission with oil (i.e., close-to-zero net volatility spillovers) depending on oil's regimes consistently outperforms the buy and hold strategy in terms of information ratio.     

Information connectedness of international crude oil futures: Evidence from SC,WTI, and Brent

The first Yuan (RMB) denominated crude oil futures contract, SC, was launched in the Shanghai International Energy Exchange (INE) on 26 March 2018, which is extremely meaningful for China and other Asian countries by offering a new option of oil price risk management. To identify the information connectedness among this emerging contract and those mature WTI and Brent oil futures, we provide return and volatility directional connectedness evidence among them in both the time and frequency domains. The empirical results show that, firstly the three oil futures of SC, WTI, and Brent present high degree of total connectedness in the return and volatility series, implying tight information transfer among them. Secondly, the net directional connectedness results suggest that the SC can provide competitive information on oil returns and is a net and powerful contributor to volatility shocks. In addition, from a frequency-specific perspective, we find that the SC appears to be not only a net transmitter of return shocks on the medium- and long-term frequencies but also a net transmitter of volatility shocks consistently across the whole frequency ranges. The overall evidence suggests that China's new oil futures is an active participant in the international oil futures market, and may become an important product in information transmission across international crude oil futures markets by providing effective hedging instrument for crude oil producers, refiners, consumers, and investors, especially those in Asia.