Spillovers between Bitcoin and other assets during bear and bull markets

This article contributes to the embryonic literature on the relations between Bitcoin and conventional investments by studying return and volatility spillovers between this largest cryptocurrency and four asset classes (equities, stocks, commodities, currencies and bonds) in bear and bull market conditions. We conducted empirical analyses based on a smooth transition VAR GARCH-in-mean model covering daily data from 19 July 2010 to 31 October 2017. We found significant evidence that Bitcoin returns are related quite closely to those of most of the other assets studies, particularly commodities, and therefore, the Bitcoin market is not isolated completely. The significance and sign of the spillovers exhibited some differences in the two market conditions and in the direction of the spillovers, with greater evidence that Bitcoin receives more volatility than it transmits. Our findings have implications for investors and fund managers who are considering Bitcoin as part of their investment strategies and for policymakers concerned about the vulnerability that Bitcoin represents to the stability of the global financial system.     

Does international oil volatility have directional predictability for stock returns? Evidence from BRICS countries based on cross-quantilogram analysis

While numerous studies have investigated the relationship between oil volatility and stock returns, it is surprising that little research has examined the quantile dependence and directional predictability from oil volatility to stock returns in BRICS (Brazil, Russia, India, China, and South Africa) countries. We address this issue by using the cross-quantilogram model proposed by Han et al. (2016). The empirical results show that, overall, oil volatility has a directional predictability for the stock returns in BRICS countries. When the oil volatility is in a low quantile (lower than its 0.1 quantiles), it is less likely to show either a large loss or a large gain in the stock market. In contrast, there is an increased likelihood of either large loss or a large gain in the stock market when the oil volatility is in a high quantile (higher than its 0.9 quantiles). The directional predictability from the oil volatility to stock returns depends on the net position of oil imports and exports of these BRICS countries in the oil market. The net oil exporters (Russia and Brazil) are less likely to have large gains and large losses in the stock market than are the net oil importers (India, China, and South Africa) when the oil volatility is in a low quantile. The net oil exporters are more likely to have large gains and large losses than are the net oil importers when the oil volatility is in a high quantile. The results are robust to change in the variable of oil volatility and the sample interval.     

Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks

We investigate the relationship between Bitcoin and conventional financial assets from a perspective on the connectedness of asset networks. We adopt the method of measuring connectedness proposed by Diebold and Yilmaz (2009, 2012, and 2014) in a VAR system to study the dynamic interdependence between returns in Bitcoin, stocks, oil, and gold. We find that the connectedness between bitcoin and conventional assets is weak. The separation of positive and negative returns in the Bitcoin market shows the existence of an asymmetric pattern of the spillover effects between Bitcoin and conventional assets. A rolling window analysis finds that although Bitcoin prices experience a rising link to other financial assets, the magnitude is proven to be moderate. However, connectedness via negative returns is much stronger than via positive ones and exhibits a clearly increasing trend in recent periods. Our results in application are generally robust to other popular cryptocurrencies, such as ETH and Ripple. The findings presented in this paper have important implications for financial market participants, policymakers, and researchers in light of projected increases in the adoption of Bitcoin, as well as the rapid development of cryptocurrency.     

Realized volatility transmission: The role of jumps and leverage effects

This paper is the first to employ a multivariate extension of the LHAR–CJ model for realized volatility of Corsi and Renó (2012) considering continuous and jump volatility components and leverage effects. The model is applied to financial (S&P 500), commodity (WTI crude oil) and forex (US$/EUR) intraday futures data and allows new insights in the transmission mechanisms among these markets. Besides significant leverage effects, we find that the jump components of all considered assets do not contain incremental information for the one-step ahead realized volatility. The volatility of S&P 500 and US$/EUR exchange rate futures exhibits significant spillovers to the realized volatility of WTI. Moreover, decreasing equity prices appear to increase volatility in other markets, while strengthening of the US$ seems to calm down the crude oil market.     

Oil and US stock market shocks: Implications for Canadian equities

Oil and US stock market shocks are relevant to Canadian equities because Canada is an oil exporter exposed to market developments in the wider continent. We evaluate how the relationship between Canadian stock market indices and such external shocks change under extraordinary events. To do this, we subject statistically identified oil and S&P 500 market shocks to a surprise filter, which detects shocks with the greatest magnitude occurring over a given lookback period, and an outlier filter, which detects extrema shocks that exceed a normal range. Then, we examine how the dependence structure between shocks and Canadian equities change under the extreme surprise and outlier episodes through various co-moment spillover tests. Our results show co-moments beyond correlation are important in reflecting the changes occurring in the relationships between external shocks and Canadian equities in extreme events. Additionally, the differences in findings under extreme positive and negative shocks provide evidence for asymmetric spillover effects from the oil and US stock markets to Canadian equities. Moreover, the observed heterogeneity in the relationships between disaggregated Canadian equities and shocks in the crude oil and S&P 500 markets are useful to policy-makers for revealing sector-specific vulnerabilities and provide portfolio diversification opportunities for investors to exploit.     

FINANCIAL CRISES AND INTERNATIONAL STOCK MARKET VOLATILITY TRANSMISSION

This paper examines the interplay between stock market returns and their volatility, focusing on the Asian and global financial crises of 1997–98 and 2008–09 for Australia, Singapore, the UK, and the US. We use a multivariate generalised autoregressive conditional heteroskedasticity (MGARCH) model and weekly data (January 1992–June 2009). Based on the results obtained from the mean return equations, we could not find any significant impact on returns arising from the Asian crisis and more recent global financial crises across these four markets. However, both crises significantly increased the stock return volatilities across all of the four markets. Not surprisingly, it is also found that the US stock market is the most crucial market impacting on the volatilities of smaller economies such as Australia. Our results provide evidence of own and cross ARCH and GARCH effects among all four markets, suggesting the existence of significant volatility and cross volatility spillovers across all four markets. A high degree of time‐varying co‐volatility among these markets indicates that investors will be highly unlikely to benefit from diversifying their financial portfolio by acquiring stocks within these four countries only.     

Relationships among U.S. oil prices and oil industry equity indices

The cointegration analysis suggests that the pure oil industry equity system and the mixed oil price/equity index system offers more opportunities for long-run portfolio diversification and less market integration than the pure oil price systems. On a daily basis, in the oil price systems all oil prices with the exception of the 3-month futures can explain the future movements of each other. In the mixed system, none of the daily oil industry stock indices can explain the daily future movements of the New York Mercantile Exchange (NYMEX) futures prices, whereas these prices can explain the movements of independent companies engaged in exploration, refining, and marketing. The spillover analysis of oil volatility transmission suggests that the oil futures market has a matching or echoing volatility effect on the stocks of some oil sectors and a volatility-dampening effect on the stocks of others. The policy implication is that, during times of high oil volatility, traders should choose the S&P oil sector stocks that match their tolerance for volatility and use the right financial derivative to hedge against or profit from this volatility. The day effect for volatility transmission suggests that Friday has a calming effect on the volatility of oil stocks in general. The effect for Monday is not significant.     

Oil price and automobile stock return co-movement: A wavelet coherence analysis

This paper explores possible co-movement between oil price and automobile stock return in a joint time-frequency domain. Daily price series from August 01, 1996 to June 20, 2017 is used in this analysis. The results indicate that the co-movement between oil price and automobile stock return is strong during November, 2000–December, 2002 and March, 2006–December, 2009. The co-movement is found to be more pronounced in the long-term and stock return is sensitive to the higher oil price emanating from the demand shock. This contravenes the conventional wisdom that crude oil is always counter-cyclical to the automobile stocks. For investor, this weakens the probable gain from including oil asset in a portfolio of automobile stocks as crude oil does not offer cushion against bearish automobile stock markets during the crisis period.     

Safe havens in the face of Presidential election uncertainty: A comparison between Bitcoin,oil and precious metals

Even though the empirical literature on safe haven properties of different assets with respect to financial risks is increasing, their abilities to safeguard against political risks has not been the subject of large empirical investigations. This paper uses an Empirical Mode Decomposition-based approach to look into the time-varying role of different assets (in particular, oil, precious metals and Bitcoin) as a safe haven against U.S. stocks in times of heightened uncertainty surrounding the outcome of the 2016 U.S. presidential election. Our results suggest that oil can act as an effective safe haven against political risk exposure; but such property varies over time. The abilities of gold and silver to provide positive returns during downturns have been also documented in the medium-and the long-term. Bitcoin also serves as a safe haven against U.S. stock losses but in the short-term. These findings provide useful and relevant information to investors to help ensure better asset allocation in an uncertain environment.     

Does religious faith affect household financial market participation? Evidence from China

Based on the 2013 China Household Finance Survey data, this paper investigates the impact of religious faith on household financial market participation and portfolio choice. The results show that religious faith can significantly promote household financial market participation. Besides, religious faith can increase the proportion of risky assets held by households, including equities. We also find that the need for social interaction and human capital accumulation can significantly induce religious residents to participate in financial markets and hold risky assets. Overall, our results reveal how faith affects household finance activities in China.     

Financial contagion and volatility spillover: An exploration into Indian commodity derivative market

This study measures the extent of financial contagion in the Indian asset markets. In specific it shows the contagion in Indian commodity derivative market vis-à-vis bond, foreign exchange, gold, and stock markets. Subsequently, directional volatility spillover among these asset markets, have been examined. Applying DCC-MGARCH method on daily return of commodity future price index and other asset markets for the period 2006–16, time varying correlation between commodity and other assets are estimated. The degree of financial contagion in commodity derivative market is found to be the largest with stock market and least with the gold market. A generalized VAR based volatility spillover estimation shows that commodity and stock markets are net transmitters of volatility while bond, foreign exchange and gold markets are the net receivers of volatility. Volatility is transmitted to commodity market only from the stock market. Such volatility spillover is found to have time varying nature, showing higher volatility spillover during the Global Financial Crisis and during the period of large rupee depreciation in 2013–14. These results have significant implication for optimal portfolio choice.     

Hedging and diversification across commodity assets

ABSTRACT

We investigate the conditional cross effects and volatility spillover between equity markets and commodity markets (oil and gold), Fama and French HML and SMB factors, volatility index (VIX) and bonds using different multivariate GARCH specifications considering the potential asymmetry and persistence behaviours. We analyse the dynamic conditional correlation between the US equity market and a set of commodity prices and risk factors to forecast the transmission of shock to the equity market firstly, and to determine and compare the optimal hedge ratios from the different models based on the hedging effectiveness of each model. Our findings suggest that all models confirm the significant returns and volatility spillovers. More importantly, we find that GO-GARCH is the best-fit model for modelling the joint dynamics of different financial variables. The results of the current study have implications for investors: (i) the equity market displays inverted dynamics with the volatility index suggesting strong evidence of diversification benefit; (ii) of the hedging assets gold appears the best hedge for the US equity market as it has a higher hedge effectiveness than oil and bonds over time; and (iii) despite these important results, a better hedge may be obtained by using well-selected firm sized and profitability-based portfolios.     

Return and volatility spillovers between china and world oil markets

We examine return and volatility spillovers between China and world oil markets. This topic is of great importance because China is the world's second-largest oil importer and has exhibited substantial growth in oil consumption. Extending Diebold and Yilmaz's (2012) method of catching spillover dynamics, it is found that return and volatility spillovers between China and world oil markets are bi-directional and asymmetric. The Chinese oil market is highly affected by world oil markets and exerts an influence on world oil markets, although to a lesser extent. Moreover, the volatility spillover index has increased significantly since the peak of the last financial crisis in September 2008. Although the US oil market impacts China's market most in terms of spillover, the influence of China's oil market on the world oil market has intensified in recent years.     

China's liberalizing stock market,crude oil,and safe-haven assets: A linkage study based on a novel multivariate wavelet-vine copula approach

China is the world's largest oil importer, and therefore the correlations between stock indices and highly volatile oil prices deserve close examination when investing in China's gradually liberalizing stock market. Another concern for international investors is whether safe-haven assets can reduce portfolio risks for investment in China. The paper makes two main contributions. First, we develop a novel method of examining a multivariate dependence structure by combining wavelet analysis with the vine copula model. Second, we apply the proposed methodology to study the correlations between China's liberalizing stock market, petroleum, and safe-haven assets at different frequencies. We find that the multidimensional dependence of these assets has been altered as a result of the 2008 global financial crisis. Moreover, the vine structures exhibit dependence patterns that vary over time horizons, indicating that the multidimensional dependence is sensitive to time scales.     

Diversification and optimal hedges for socially responsible investment in Brazil

This study contributes to the literature on socially responsible investing by examining the diversification potential of commodities, specifically oil, gold and clean energy together with the Brazilian Corporate Sustainability Index (ISE). Multivariate GARCH models are used to model volatility spillovers and conditional correlation in pairs of stocks containing ISE. Specifically, A-BEKK and A-DCC models with spillovers are estimated. The models’ results are used to compute and analyze the optimal weights and hedge ratios for stock portfolio holdings. The greatest benefit from diversification is obtained through the acquisition of gold and then OVX.     

How are Africa's emerging stock markets related to advanced markets? Evidence from copulas

The finance literature provides ample evidence that diversification benefits hinges on dependence between assets returns. A notable feature of the recent financial crisis is the extent to which assets that had hitherto moved mostly independently suddenly moved together resulting in joint losses in most advanced markets. This provides grounds to uncover the relative potential of African markets to provide diversification benefits by means of their correlation with advanced markets. Therefore, we examine the dependence structure between advanced and emerging African stock markets using copulas. Several findings are documented. First, dependence is time-varying and weak for most African markets, except South Africa. Second, we find evidence of asymmetric dependence, suggesting that stock return comovement varies in bearish and bullish markets. Third, extreme downward stock price movements in the advanced markets do not have significant spillover effects on Africa’s emerging stock markets. Our results, implying that African markets, with the exception of South Africa, are immune to risk spillover from advanced markets, improves the extant literature and have implications for portfolio diversification and risk management.     

Dynamic frequency connectedness between oil and natural gas volatilities

The goal of this paper is twofold. First, we study dynamic volatility connectedness between oil and natural gas over the period 1994 to 2018. Second, we examine the frequency dynamics of the transmission mechanism arising from frequency-specific responses to volatility shocks. To do so, we adopt a newly introduced approach that decomposes connectedness measures based on variance decompositions into their components at different frequency ranges. Our results summarize as follows: (a) there is a substantial variation in volatility spillovers over time; (b) the natural gas market was a net transmitter during the central part of our sample period; (c) the magnitude of spillovers was smaller after the financial crisis, but volatilities are not decoupled. (d) The volatility propagation mechanism is frequency dependent. Connectedness is typically created at low-frequencies, with volatility shocks across markets having long-lasting effects. However, during some specific periods, such as after Katrina, volatility was transmitted much faster, with shocks dissipating in the short-run.     

Volatility transmission between oil prices and banks' stock prices as a new source of instability: Lessons from the United States experience

This paper examines whether American banks' exposure to the oil industry could lead to instability in both oil and financial markets. To address this issue, we investigate volatility spillovers between oil prices and the stock prices of the four major American banks involved in the oil industry by employing the vector autoregressive fractionally integrated moving average framework. We use high-frequency data from January 3, 2006, to June 30, 2016. Our results support the existence of such volatility spillovers, as evidenced by the significant volatility responses of oil price (banks' stock price) to a shock in banks' stock price (oil price). These responses, more pronounced following the banks' exposure to the shale industry, mainly reflect the financial fragility of shale companies and their high indebtedness levels. Thus, this paper emphasises how the shale oil industry could trigger turmoil in both oil and financial markets.     

Information and capital flows: The determinants of transactions in financial assets

We show that a gravity model explains international transactions in financial assets at least as well as goods trade transactions. Our results support the hypothesis that informational asymmetries are responsible for the strong negative relationship between asset trade and distance. This result is very important for theories of asset trade, portfolio adjustments and home bias. We strengthen it by investigating the roles of explicit informational variables, as well as distance, in explaining separately cross-border trade in corporate equities, corporate bonds, and government bonds.     

Regional and copula estimation effects on EU and US energy equity portfolios

ABSTRACT

The aim of this paper is to investigate the regional interdependence structure of energy equities in the US and in the EU. Based on weekly stock prices of 28 big energy firms in the two regions from 2008 to 2019, we compare the efficiency of using bivariate or multivariate copulas to describe the dependence structure of energy equities. Furthermore, we investigate the impact of the choice between these two methods on the performance of energy equity portfolios. Our empirical results show that multivariate copulas, such as C-Vine, allow to better describe the dependence structure of energy equities. We also find that there is a stronger and more complex dependence structure among EU energy equities than among US energy equities. Our scenario analysis also shows that the dependence structure is stronger during the GFC while being weaker during the ESDC. More importantly, the correlation matrix obtained from the multivariate copula method allows to obtain optimal mean-CVaR portfolios with a higher performance than that from the bivariate copula method. More importantly, optimal portfolios constituted with multivariate copulas allow to reduce the portfolio’s sensitivity to oil prices.