Commodity market risk from 1995 to 2013: an extreme value theory approach

In this article we examine whether extreme risk has increased in the agricultural commodity market during the period 1995–2013. We add to the literature on food price volatility by analysing the tail segment of futures price return distributions. Food price variability is a concern for governments and regulators worldwide, as most nations trade in food. High food price variability can contribute to poverty and malnourishment, in particular for people in less economically developed economies. We find no indications of systematically increasing tail-risk for the commodities in our sample. Analysis of estimated shape-parameters of the Generalized Extreme Value distribution further supports the conclusion that there is no general systematic change in the extreme risk associated with these commodity investments.     

Stock market integration of emerging Asian economies: Patterns and causes

In this study, we examine the patterns and causes of stock market integration of selected emerging Asian nations against the US, Australia, China, and India for the period 1 January 2001 to 31 March 2012. We compare patterns of market integration for countries on a daily, weekly, or monthly basis using the time-varying correlation technique, namely, GARCH-dynamic conditional correlations (DCCs). In doing so, we suggest that opportunities in cross border investment vary by frequencies. We also divide daily data into subsamples and find that correlations were strongest during the global financial crisis (GFC) of 2007–09. The time varying bilateral correlations are found to be highly volatile. We also investigate the causes of identified correlations and find that apart from the GFC, the underlying economic and financial conditions have also been responsible for the higher correlations between these stock markets.     

The relationship between the Vietnam stock market and its major trading partners – TECM with bivariate asymmetric GARCH model

This study employs threshold error-correction model with bivariate Glosten–Jagannathan–Runkle-generalized autoregressive conditional heteroscedasticity model to examine the relationship between the Vietnam stock market and its major trading partners, the United States, Japan, Singapore and China. The results indicate that the Vietnam stock market and return risks are influenced by Japan and Singapore stock markets. We also find that the volatility of stock market in Vietnam and its trading countries have an asymmetrical effect. These findings could be valuable to individual investors and financial institutions holding long-run investment portfolios in the Vietnam stock market.     

Diamonds and precious metals for reduction of portfolio tail risk

ABSTRACT

We study the performance of diamonds compared to gold and other precious metals in mitigating the tail risk of a diversified equity market portfolio over the period June 2007 to October 2018. Our results display a diversification benefit of some diamond indices, which also improve the portfolio reward-to-risk ratio. To corroborate this evidence, we study the dependence structure and tail dependence of diamonds and a broad equity market portfolio and compare it to the dependence obtained with gold and other precious metals. Results from fitting a bivariate copula show that the average left tail dependence reaches its minimum when diamonds are used. We also show that using shares of diamond-mining companies does not provide the same benefits.     

Investigating the dynamic relationship between cryptocurrencies and conventional assets: Implications for financial investors

Cryptocurrencies are gradually establishing themselves as a new class of assets with unique features, although there remains skepticism and a lack of understanding of their nature. In this study, we compare the financial properties of these new digital assets and investigate their dynamic relationship with major financial securities and commodities. Furthermore, we evaluate the economic and financial potential benefits of cryptocurrencies for financial investors. Using different time-varying copula approaches and bivariate dynamic conditional correlation GARCH models, we find that the cross-correlation with conventional assets is changing over time but weak, supporting the idea that these cryptocurrencies can be suitable for financial diversification. However, our analysis of portfolios shows that cryptocurrencies are poor hedging instruments in most of the considered cases. Moreover, we find that the relationship between cryptocurrencies and conventional assets is sensitive to external economic and financial shocks.     

Tail dependence and diversification benefits in emerging market stocks: an extreme value theory approach

This article examines tail dependence, the benefits of diversification and the relation between the two for emerging stock markets. We find most emerging equity markets are independent in limiting joint extremes. However, the dependence in finite levels of extremes is still much stronger than the dependence implied by multivariate normality. Therefore, simple correlation analysis can lead to gross underestimation of the chances of joint crashes in multiple markets. Assuming risk-averse investors guarding against extreme losses, diversification benefits are measured for each two-country optimal portfolio by the reduction in quantile risk measures such as value-at-risk and expected shortfall relative to an undiversified portfolio. It is shown that tail dependence measures developed from multivariate extreme value theory are negatively related to diversification benefits and more importantly can explain diversification benefits better than the correlation coefficient at the most extreme quantiles.     

How are gold returns related to stock or bond returns in the U.S. market? Evidence from the past 10-year gold market

Although the gold market over the past decade has been soaring relative to its prior history, there have been few studies on the relationship between the gold market and other major financial markets based on the past decade of data. To re-investigate how the gold market interacts with the stock market and the bond market, we re-visit economic and financial characteristics of gold using the past 10-year data in terms of co-integration, causality, predictive power, and extreme returns. We find that while gold returns are not co-integrated with stock returns and bond returns, gold returns have a unidirectional causality with both of them. Also, we discover that gold returns have some predictive power on subsequent short-term stock returns. Under extreme market scenarios, it turns out that gold returns tend to deteriorate more simultaneously with bond returns than stock returns. This means that gold can better serve as a safe haven for stock in a relative sense during temporary market downturns.     

Financialization of agricultural commodities: Evidence from China

Speculation in the commodity futures market distorts commodity prices, driving them away from rational levels. This phenomenon, which is known as the financialization of commodities, has raised significant concerns in recent years. Particularly, in the agricultural market, ‘financialized’ commodities have been blamed for high world food prices. In this paper, we examine the financialization of agricultural commodities in China. To do so, a time-varying copula is employed to investigate the dependence structure between commodities and stock markets. Four insightful results are obtained. First, positive correlations between agricultural commodities and stock markets demonstrate the financialization of agricultural commodities. Second, the identified correlations are time-varying and idiosyncratic with respect to products. Third, the agricultural commodity market is more closely correlated with the domestic stock market than with the overseas market. Fourth, a growing dependence between commodities and the stock markets is detected and the co-movement became stronger after the global financial crisis.     

Stock market comovements in Central Europe: Evidence from the asymmetric DCC model

We examine time-varying stock market comovements in Central Europe employing the asymmetric dynamic conditional correlation multivariate GARCH model. Using daily data from 2001 to 2011, we find that the correlations among stock markets in Central Europe and between Central Europe vis-à-vis the euro area are strong. The correlations increased over time, particularly after their EU entry and largely remained at these levels during the financial crisis. The stock markets exhibit asymmetry in the conditional variances and to a certain extent in the conditional correlations as well, pointing to the importance of applying a sufficiently flexible econometric framework. The conditional variances and correlations are positively related, suggesting that the diversification benefits decrease disproportionally during volatile periods.     

Dynamic correlation and equicorrelation analysis of global financial turmoil: evidence from emerging East Asian stock markets

This study investigates the dynamic conditional correlations (DCCs) between eight emerging East Asian stock markets and the US stock market and analyses the dynamic equicorrelation among these nine stock markets. We find a significant increase in the conditional correlations and equicorrelation in the first phase of the global financial crisis. We refer to this finding as contagion from the US stock market to the emerging East Asian markets. We also find an additional significant process of increasing correlations and equicorrelation (herding) in the second phase of the global financial crisis. Further, we employ two new models, namely DCCX-MGARCH (a DCC Multivariate GARCH model with exogenous variables) and DECOX-MGARCH (a dynamic equicorrelation multivariate GARCH model with exogenous variables), to identify the channels of contagion. We find that an increase in the VIX Index increases the conditional correlations and equicorrelation, while increases in TED spreads decrease the conditional correlations of six emerging East Asian countries with the USA. We compare the accuracy of the conditional correlation estimates of the DCC and DCCX models (or DECO and DECOX models) by constructing a loss function. We find that the DCCX (DECOX) model provides more accurate conditional correlation estimates than the DCC (DECO) model by extracting additional information from exogenous variables.     

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.     

Dynamic linkages between stock markets: the effects of crises and globalization

This paper investigates changes in the dynamics of linkages between selected national stock markets during the period 1995–2009. The analysis focuses on the possible effects of globalization and differences between crisis and non-crisis periods. We model the dynamics of dependencies between the series of daily returns on selected stock indices over different time periods, and compare strength of the linkages. Our tools are dynamic copula models and a formal sequential testing procedure based on the model confidence set methodology. We consider two types of dependencies: regular dependence measured by means of the conditional Spearman’s rho, and dependencies in extremes quantified by the conditional tail dependence coefficients. The main result consists of a collection of rankings created for the considered subperiods, which show how the mean level of strength of the dependencies have been changing in time. The rankings obtained for Spearman’s rho and tail dependencies differ, which allows us to distinguish between the results of crises and the effect of globalization.     

Stock price synchronicity to oil shocks across quantiles: Evidence from Chinese oil firms

This paper investigates behaviour of stock price synchronicity to oil shocks across quantiles for Chinese oil firms. The spillover effects of the oil market on a firm are segregated into firm-specific and market-wide information. First, our results report a higher level of synchronicity by dynamic conditional correlations than by R-square since the former better captures dynamic linear dependence. Second, we find strong evidence of size effect. In particular, stock price synchronicity is generally higher in large-cap firms than in small-cap ones. Oil shocks affect synchronicity in the upper quantiles differently based on firm size. Third, we also find that synchronicity responds to oil shocks significantly in extreme low quantiles, implying that shocks in the oil market are transmitted to Chinese oil firms via firm-specific information. Finally, we determine that oil shocks have little or no immediate impact on stock price synchronicity; instead, cumulative lagged effect is evident. This evidence highlights the lagging effect of spillover of oil shocks on Chinese oil firms.     

Determinants of stock market comovements among US and emerging economies during the US financial crisis

By analyzing the dynamic conditional correlations (DCC) of the daily stock returns of 10 emerging economies in comparison with those of the US for the period of 2006–2010, we find different patterns of crisis spillover among 10 emerging economies. While a group of countries has three distinctive phases of crisis spillover (contagion, herding, and post-crisis adjustment), other groups show different phases of crisis spillover. It is also shown that increases in CDS spread and TED spread decrease conditional correlations while increases in foreign institutional investment, exchange market volatility, and the VIX index of the S&P 500 increase conditional correlations.     

Safe haven,hedge and diversification for G7 stock markets: Gold versus bitcoin

We compare gold and Bitcoin for the G7 stock markets, finding that gold and Bitcoin have distinct safe haven and hedging characteristics. Gold is an undisputable safe haven and hedge for several G7 stock indices, whereas Bitcoin takes these two functions in Canada. The out-of-sample hedging effectiveness of gold is much superior to that of Bitcoin. Furthermore, we find that the conditional diversification benefits offered by gold to equity investments in the G7 markets are comparatively much higher and more stable than those of Bitcoin, especially in the lower return quantiles, i.e., when both the stock and gold markets are in a bearish state. Implications are further discussed.     

Correlations and volatility spillovers across commodity and stock markets: Linking energies,food, and gold

This paper employs a VAR-GARCH model to investigate the return links and volatility transmission between the S&P 500 and commodity price indices for energy, food, gold and beverages over the turbulent period from 2000 to 2011. Understanding the price behavior of commodity prices and the volatility transmission mechanism between these markets and the stock exchanges are crucial for each participant, including governments, traders, portfolio managers, consumers, and producers. For return and volatility spillover, the results show significant transmission among the S&P 500 and commodity markets. The past shocks and volatility of the S&P 500 strongly influenced the oil and gold markets. This study finds that the highest conditional correlations are between the S&P 500 and gold index and the S&P 500 and WTI index. We also analyze the optimal weights and hedge ratios for commodities/S&P 500 portfolio holdings using the estimates for each index. Overall, our findings illustrate several important implications for portfolio hedgers for making optimal portfolio allocations, engaging in risk management and forecasting future volatility in equity and commodity markets.     

Firm Market Performance and Volatility in a National Real Estate Sector

We present empirical evidence using daily data for stock prices for 17 real estate companies traded in the Sao Paulo, Brazil stock exchange, from August 26, 2006 to March 31, 2010. We use the U.S. house price bubble, financial crisis and risk measures to instrument for momentums and reversals in the domestic real estate sector. We find evidence of conditional premium persistence and conditional volatility persistence in the market. We find that the conditional risk-return relationship in the sector is consistent with the prospect theory of risk attitudes in this period. Certain companies seem to be operating on a perceived potential industry return above the target, while most others are below the target, and the whole sector is below target on average.     

股票转让方式与极端收益风险——兼论新三板市场引入做市转让制度的经济后果

在极端收益风险形成机理的现有研究中,交易环节是其逻辑链条中缺失的一环;对于做市转让制度的实施效果,现有实证研究也普遍忽视了其对极端收益风险的影响.文章从交易环节入手,提出了一个解释极端收益风险形成机理的新假说,并以新三板市场引入做市转让制度为契机,实证考察了股票转让方式和极端收益风险之间的关系.研究发现:(1)与实施协议转让的股票相比,实施做市转让的股票极端收益风险显著较低,但更多的做市商并未带来显著更低的极端收益风险;(2)做市转让方式对股价暴涨风险的抑制作用在熊市中较强,对股价暴跌风险的抑制作用则在牛市中较强;(3)股票转让方式对极端收益风险的影响主要通过股票流动性路径起作用,而信息有效性路径会起作用主要是因为信息有效性和股票流动性之间的高相关性.使用处理效应模型来控制自选择偏差的影响,使用不同的极端收益风险度量指标,延长极端收益风险的计算窗口,均不改变上述实证结果.这表明,交易环节是影响极端收益风险的重要因素,做市转让方式的引入有助于降低新三板挂牌公司的极端收益风险.文章对于深入理解极端收益风险形成机理、改善新三板市场交易机制具有重要的意义.     

Where does the risk lie? Systemic risk and tail risk networks in the Chinese financial market

This paper studies tail risk connectedness and systemic risk in the Chinese financial market in the post-crisis period of 2009–2017. We adopt the conditional value at risk (CoVaR) and complex theory to construct the tail risk connectedness network and identify the systemically important financial institutions during the Chinese financial turbulence. We precisely characterize the dynamic evolution of the tail risk connectedness at the institutional, sector and market levels. We find that, during normal times, the banking sector contributes the most tail risk to the market and that the real estate sector contributes the least. However, during the crisis period, the real estate sector played its role and became the most significant tail risk emitter. In addition, we identify the significant important financial institutions in the Chinese financial market, highlighting the fact that the four state-owned commercial banks and two largest insurance companies dominate. Our results are helpful to both regulators for developing macroprudential supervision policies and investors interested in the Chinese financial market for making risk management strategies.     

Is gold a hedge and safe haven for stock market?

The paper aims to examine the hedge and safe haven properties of gold relative to Dow Jones stock industry indices using quantile-GARCH approach. Splitting the sample period into two sub-periods, our results show that the hedge and safe haven properties of gold have a changing nature. In a whole period (1980–2017), gold is not a hedge for Oil&Gas, Basic materials and Utilities; gold is a safe haven for almost all sectors except Technology. While in sub-period I (1980–1995) gold is not a hedge for Oil&Gas but a strong safe haven for all sectors. In sub-period II (1996–2017) gold is not a hedge for Oil&Gas, Basic materials and Utilities, also not a safe haven for Oil&Gas, Basic materials, Utilities, Telecom and Technology.