中国创业板市场与中小板市场间的波动溢出效应研究——基于方法比较视角

基于创业板市场与中小板市场的特殊关系,本文分别运用单变量条件异方差模型和多元条件异方差模型考察二者之间的信息传导和波动溢出效应,研究结果表明:(1)创业板市场对中小板市场存在波动的集聚性和持久性溢出效应,中小板市场对创业板市场不存在波动的集聚性溢出效应,但存在波动的持久性溢出效应;(2)创业板市场与中小板市场间均值溢出效应不显著,二者互不构成对方的定价中心;(3)单变量GARCH模型下,创业板市场对中小板市场存在单向的波动溢出效应,而多元GARCH模型下,创业板市场与中小板市场间存在双向波动溢出效应,表明多元GARCH模型效果优于单变量GARCH模型;(4)创业板市场与中小板市场间的波动溢出效应程度均不大,但中小板市场对创业板市场的波动溢出效应程度要大于创业板市场对中小板市场的波动溢出效应程度,表明老市场向新兴市场的信息流动量较大.     

沪港通背景下行业间波动溢出效应及形成机理

研究目标：研究资本市场开放是否强化跨境资本市场间的联系及如何促进波动溢出和风险传染等问题。研究方法：运用广义溢出指数法对比分析沪港通开通前后中国内地与中国香港股市行业间波动溢出效应的变化及其形成机理。[HTH]研究发现：沪港通开通前,信息、电信等第三产业的信息溢出水平较高,但沪港通开通后,材料、工业等第二产业的信息溢出能力显著增强;沪港通的实施提高了两市行业间的双向波动溢出程度,且主要增强了上证各行业对恒生行业的波动溢出强度;市盈率效应、规模效应和投资者情绪变化等内地市场的非理性特征也会影响中国内地与中国香港股市间的波动溢出。研究创新：在沪港通政策背景下,从行业层面考察两地股市间的波动溢出效应及形成机理,将风格投资和投资者情绪等非理性行为因素纳入两地资本市场波动溢出的解释框架。研究价值：为两地资本市场的风险传染机制提供更为系统的视角,为检验内地资本市场开放政策提供更为全面的评估,为推行“深港通”等制度提供借鉴。     

国际能源市场与股票市场的波动溢出效应及驱动因素研究——基于TVP-VAR-DY溢出指数分解的实证研究

随着能源金融化程度不断加深,国际能源市场和股票市场之间的联系日益密切。采用TVP-VAR-DY溢出指数分解方法探究国际能源市场和股票市场之间的时变溢出关系,在此基础上进一步探究跨市场溢出效应的主要驱动因素。研究结果表明：国际能源市场与股票市场既存在显著的市场内部溢出效应,也存在显著的跨市场溢出效应,且系统总体溢出水平的动态变化主要由后者驱动;国际能源市场对股票市场的溢出效应弱于股票市场对能源市场的溢出,即国际能源市场为溢出净接收者。国际金融危机、COVID-19等极端风险事件发生时,跨市场波动溢出效应显著增强;地缘政治风险和全球经济政策不确定性是导致跨市场波动溢出的重要因素,且分别在金融市场动荡时期、全球流动性收紧时期表现得更加明显。鉴于此,投资者应高度重视两个市场之间的波动溢出风险,当极端经济事件发生时,监管部门应采取必要的非常规政策措施,减轻溢出效应的不利影响,防范化解系统性金融风险。     

权证市场和基础市场关系研究——基于二元GARCH模型的实证分析

本文首先通过建立ARIMA(p,0,q)模型将交易量变动率分成预期的和非预期的两个变量,然后列入到二元GARCH(1,1)模型的条件均值方程中,来研究股票市场和权证市场之间的信息不对称关系。同时通过使用BEEK模型的设定形式作为GARCH模型的条件方差方程,来研究股票市场和权证市场之间的交易量波动溢出关系。通过实证研究,结果表明我国的股票市场和权证市场之间确实存在显著的信息不对称效应和双向的交易量波动溢出效应,且这种波动溢出现象也具有一定的"不对称性"。     

中国股市与汇市波动溢出效应研究

以上证综合指数和人民币兑美元名义汇率为指标,运用多元GARCH模型对中国股票市场和外汇市场之间的波动溢出效应进行实证研究。结果表明：汇率制度改革后,我国股市与汇市存在显著的双向波动溢出效应;汇市对股市表现出较强的波动传导,而股市对汇市的波动传递则相对较弱,存在着波动传导的非对称性。     

金融市场协同波动溢出分析及实证研究

对于动态投资组合与风险管理来说，测定金融市场之间的波动溢出是非常重要的。在已有的文献中往往是研究两个金融市场之间是否存在波动溢出，多个金融市场对一个金融市场的协同波动溢出则未提及。本文使用独立成分分析（ICA）来消除多个金融市场波动之间的相关性，使用GARCH模型研究多个金融市场对一个金融市场的协同波动溢出，并进行了实证分析。     

沪深两市股票市场的Garch类模型分析

本文采用EGARCH(1,1)模型和Granger因果检验分别对我国沪、深两个股票交易市场2001年2月到2006年的3月期间的股票价格指数的日度数据进行了分析。EGARCH(1,1)模型表明这两个市场股指收益率存在条件异方差、持久的波动聚类现象和杠杆效应。Granger因果检验则说明两市场波动之间则存在双向的Granger因果关系,即两个市场之间表现出对称的波动溢出效应。     

中国金融市场间极端风险溢出的监测预警研究——基于MVMQ-CAViaR方法的实现

为有效监测与预警中国金融市场间极端风险溢出的方向与程度，本文基于MVMQ-CAViaR方法，结合中国2013—2017年银行间市场、债券市场与股票市场相关数据，分析各金融市场间的极端风险传递过程。实证结果显示，股票市场与债券市场对银行间市场产生显著的单向极端风险溢出效应，而银行间市场对另外两个市场无极端风险传递效果，这表明股票市场与债券市场的极端风险向银行间市场的传递过程具有不可逆性。从风险传递的强度来看，债券市场对股票市场和银行间市场的极端风险溢出效应更加显著。因此，决策部门应重点关注债券市场的极端风险水平变化，缓释债券市场与股票市场对银行间市场的极端风险冲击，以有效防范和化解不同金融市场间极端风险的传染与暴露。     

基于二元GARCH方法对我国国债市场的分割性检验

我国的国债市场目前尚处于分割状态,本文从市场之间信息流动的角度出发,构建二元GARCH模型对我国两个国债交易市场之间的波动溢出效应进行研究,发现银行间市场与交易所市场存在稳定的一阶矩长期关系及二阶矩的双向信息流动;并构造时变的条件相关系数对市场一体化程度进行分析,发现总体上两市场一体化程度较差,在检验期末的时段,相关系数开始呈现上升趋势。这一结果更多地归因于两市场跨市交易品种较少、投资者结构的差异以及现行的转托管制度。     

美国量化宽松与常规货币政策对中国实体经济溢出效应的实证检验

本文通过构建基于美国联邦基金利率、中国实际GDP同比增速、中国通货膨胀率的三元非线性平滑迁移自回归模型,对美国常规货币政策时期和量化宽松时期货币政策对中国实体经济的溢出效应进行了检验。结果发现,美国货币政策对中国宏观经济具有显著的溢出效应,并且在常规货币政策和量化宽松货币政策时期,美国货币政策对中国实体经济的影响存在显著的非对称效应,常规货币政策对中国实体经济的影响高于量化宽松货币政策。     

Spillovers between sovereign CDS and exchange rate markets: The role of market fear

As important variables in financial market, sovereign credit default swaps (CDS) and exchange rate have correlations and spillovers. And the volatility spillovers between the two markets become further complicated with the effect of market fear caused by extreme events such as global pandemic. This paper attempts to explore the complex interactions within the “sovereign CDS-exchange rate” system by adopting the forecast error variance decomposition method. The results show that there is a relatively close linkage between the two markets and the total spillover index of the system is dynamic. For most of the past, the exchange rate has a higher spillover effect on the sovereign CDS than vice versa. Moreover, after the market fear variables are introduced, the “sovereign CDS-exchange rate” system and market fear variables present bidirectional spillovers. The results of the study have particular significance for maintaining the financial stability and preventing risk contagion between markets.     

国际金融市场波动溢出效应与动态相关性

在DCC GARCH、DCC EGARCH、DCC TGARCH方法下,采用中、美、日、德、英等国家1993年1月至2013年12月的金融数据,实证得出如下结论：样本国市场利率和股指波动率呈现尖峰、肥尾、有偏的特征,更为符合t分布。样本国市场利率波动表现出显著的溢出效应、杠杆效应和联动效应。样本国股指波动率对中国股指波动率的溢出效应趋于增强,特别在美国金融危机后。样本国利率波动对中国股指波动率具有一定的溢出效应和杠杆效应,但影响程度非常低。治理世界性金融风险,各国当局应加强政策协调性,合理进行风险分担。     

Dynamic volatility connectedness between industrial metal markets

Combined with the spillover framework of Diebold and Yilmaz (2009, 2012, 2014) and the TVP-VAR-SV model of Primiceri (2005), this paper studies the dynamic volatility connectedness between six major industrial metal (i.e., aluminum, copper, lead, nickel, tin and zinc) spot and futures markets. The results show that: (1) The total volatility connectedness between industrial metal spot or futures markets has three obvious cyclical change periods with a higher connectedness level; (2) The net connectedness of zinc and copper with other metals has been at a high positive level for a long time, which indicates the two metal markets dominate the industrial metal market; (3) Zinc exhibits the strongest volatility spillovers, while tin exhibits the weakest volatility spillovers, no matter in spot markets or futures markets; (4) The connectedness of realized skewness and kurtosis have similarity with volatility connectedness but the spillover effects of skewness and kurtosis are not as obvious as the volatility spillover effects.     

Is bitcoin a safe haven or a hedging asset? Evidence from China

Based on daily data about Bitcoin and six other major financial assets (stocks, commodity futures (commodities), gold, foreign exchange (FX), monetary assets, and bonds) in China from 2013 to 2017, we use a VAR-GARCH-BEKK model to investigate mean and volatility spillover effects between Bitcoin and other major assets and explore whether Bitcoin can be used either as a hedging asset or a safe haven. Our empirical results show that (i) only the monetary market, i.e., the Shanghai Interbank Offered Rate (SHIIBOR) has a mean spillover effect on Bitcoin and (ii) gold, monetary, and bond markets have volatility spillover effects on Bitcoin, while Bitcoin has a volatility spillover effect only on the gold market. We further find that Bitcoin can be hedged against stocks, bonds and SHIBOR and is a safe haven when extreme price changes occur in the monetary market. Our findings provide useful information for investors and portfolio risk managers who have invested or hedged with Bitcoin.     

What drives dynamic connectedness of the U.S equity sectors during different business cycles?

The study investigates (i) the time-varying and directional connectedness of nine equity sectors through intra- and inter-sector volatility spillover periods and (ii) assesses the impact of state variables on aggregate volatility spillovers. The study finds about 76% of volatility linkage is associated with cross-sector volatility transmissions. Aggressive sectors, which are sensitive to macroeconomic risk, play the net volatility transmission role. Defensive sectors that are largely immune to macroeconomic risk play the net volatility receiving role. The intensity and direction of volatility transmissions among the sectors vary with economic expansion and recession periods. Over time, some sectors switching from net transmitting to net receiving role and vice versa. Macro and financial market uncertainty variables significantly impact volatility spillover at lower volatility spillover (economic expansion period) and higher volatility (economic recession periods) volatility spillover quantiles. Political signals are seemingly more imprecise and uninformative during economic expansion or low quantiles, intensifying volatility spillover. Overall, the causal effects of macro, financial, and policy uncertainty variables on aggregate volatility spillover are asymmetric, nonlinear, and time-varying. The study's result supports the cross-hedging and financial contagion views of volatility transmission across nine US equity sectors.     

交易量适合作为股价波动信息的代理变量吗?——来自中国沪深股市的证据

本文利用中国沪深股市日交易数据,采用多元GARCH模型从信息传递的角度进行实证研究,结果表明:股价对交易量具有显著的波动溢出效应,但交易量对股价的波动溢出效应不明显。这种波动的单向溢出说明在应对信息的冲击上股价比交易量能更快地做出反应,其后才通过波动溢出在交易量上得到反映,股价波动对成交量波动具有先导作用。因此,从波动冲击传导和信息传递的角度看,单纯地将交易量视为股价变动信息的代理变量还缺乏稳健的统计证据。     

Spatial spillover effects and risk contagion around G20 stock markets based on volatility network

Employing the spatial econometric model as well as the complex network theory, this study investigates the spatial spillovers of volatility among G20 stock markets and explores the influential factors of financial risk. To achieve this objective, we use GARCH-BEKK model to construct the volatility network of G20 stock markets, and calculate the Bonacich centrality to capture the most active and influential nodes. Finally, we innovatively use the volatility network matrix as spatial weight matrix and establish spatial Durbin model to measure the direct and spatial spillover effects. We highlight several key observations: there are significant spatial spillover effects in global stock markets; volatility spillover network exists aggregation effects, hierarchical structure and dynamic evolution features; the risk contagion capability of traditional financial power countries falls, while that of “financial small countries” rises; stock market volatility, government debt and inflation are positively correlated with systemic risk, while current account and macroeconomic performance are negatively correlated; the indirect spillover effects of all explanatory variables on systemic risk are greater than the direct spillover effects.     

Evidence of information transmission across currency futures markets using frequency domain tests

In this article, I examine the returns and volatility spillovers in the currency futures market incorporating the recently developed frequency domain tests. Such analysis allows differentiating between permanent (long-run) and transitory (short-run) linkages among the currency futures markets by investigating the causality dynamics at low and high frequencies respectively. I detect significant informational linkages between USD, EUR, GBP and JPY futures contracts in the Indian currency futures market. Evidence of innovations from USD futures market to other markets is the most significant for returns spillover and for volatility spillover, EUR is found to be the most significant compared to other currency futures contracts. The results would have implications for the market participants and policymakers.     

Return and volatility spillovers across the Western and MENA countries

We use weekly data on returns and range-based volatility over 2005–2017 to examine the degree of interconnectedness in financial markets of eleven MENA and four Western economies using the methodology proposed by Diebold and Yilmaz (2009, 2012, 2014). Our findings suggest (a) similar patterns of dynamic spillovers in both returns and in volatility. Both return and volatility spillover indices experienced significant bursts from 2008 to 2011 coinciding with the U.S. financial crisis. (b) Financial markets of Israel, Saudi Arabia and the UAE are more closely integrated with Westerns markets and may serve as primary channels for transmission of Western shocks to the region. Also, shocks to these three markets have noticeable impacts on other MENA markets. (c) Shocks to the U.S. financial markets play a critical role in return and volatility of MENA markets. (d) These findings are robust to alterations in window size and forecast horizon.     

COVID-19 and asymmetric volatility spillovers across global stock markets

In this study, I improve the assessment of asymmetry in volatility spillovers, and define six asymmetric spillover indexes. Employing Diebold-Yilmaz spillover index, network analysis, and my developed asymmetric spillover index, this study investigates the time-varying volatility spillovers and asymmetry in spillovers across stock markets of the U.S., Japan, Germany, the U.K., France, Italy, Canada, China, India, and Brazil based on high-frequency data from June 1, 2009, to August 28, 2020. I find that the global markets are well connected, and volatility spillovers across global stock markets are time-varying, crisis-sensitive, and asymmetric. Developed markets are the main risk transmitters, and emerging markets are the main risk receivers. Downside risk dominates financial contagion effects, and a great deal of downside risk spilled over from stock markets of risk transmitters into the global markets. Moreover, during the coronavirus recession, the total degree of volatility spillover is staying at an extremely high level, and emerging markets are the main risk receivers in the 2020 stock markets crash.