全球股票市场间风险传染的测度、监管及预警

近年来,伴随金融一体化程度的加深,全球各股票市场间风险传染的动态复杂性加剧,其准确测度、高效监管及实时预警已成为优先事项。本研究选取全球21个代表性股票市场作为分析样本,首先基于广义向量自回归模型的滚动估计准确测度其间风险动态传染的高维网络序列,进一步借由矩阵值因子模型来稳健收缩上述序列,以探究其潜在动态核心结构,从而实现高效监管。最后,通过向量自回归模型的预测功能实现对全球股票市场间风险传染的实时预警。研究表明,全球股票市场间风险传染具有时变性,其监管与预警可通过少数与地理区域高度相关的风险区域间的动态传染关系及内部的市场构成来刻画。与此同时,我们发现中国内地等新兴市场的重要地位逐渐凸显。本文研究结论可为有效防范与化解金融风险提供有益参考。     

波动溢出网络视角下全球股市风险传染研究

为刻画全球股票市场风险传染的动态路径特征,从波动溢出网络视角分析全球股票市场的风险传染机制.首先,采用DCC-GARCH动态溢出指数框架来捕捉全球股市波动溢出的动态联动性和风险传染效应;然后,基于方差分解构建信息溢出复杂网络,从网络视角分析全球股票市场的风险传染特征.研究发现,在整个样本期间,全球股票市场高度相互关联,并依赖于极端经济事件;从次贷危机到欧债危机期间全球股市溢出整体呈现减弱态势;近年来国际资本流动、金融开放与国际贸易往来等推动我国股市进程走向新阶段,风险溢出与吸收水平有上升趋势.     

我国金融市场极端风险传染路径研究

在金融市场间联系日益紧密的背景下,金融市场极端风险溢出会影响一国金融稳定,因此需要关注金融市场极端风险传染机制.本文构建了MVMQ-CAViaR模型用以分析我国五个主要金融市场间极端风险的传染路径,借助Wald统计检验及分位数脉冲响应工具探究各市场间极端风险传染的存在性、方向性和动态影响过程.研究发现,1％VaR能较好地描述我国金融市场极端风险价值动态变化;模型参数和Wald检验结果表明,五个金融市场间存在单向风险传染,传染链条依次为股票市场、货币市场、债券市场、汇率市场及黄金市场,某一金融市场极端风险价值有助于其他金融市场未来极端风险的预测;分位数脉冲响应结果显示,新息冲击对本金融市场影响力度更大、持久性更强,对其他金融市场影响较小、持久性较低,且作用方向不同.综上,监管当局和金融投资者应密切关注金融市场间的极端风险传染,防范交叉风险传染带来系统性风险.     

沪深300股指期货与现货市场间风险传染效应及影响因素

本文选取2005—2019年我国沪深300股指期货和沪深300股票指数日收盘价数据,结合股票推出时间、股价波动性,设置样本组、对照组,运用GARCH模型、DCC-GARCH模型、Granger因果关系检验及多元线性回归模型分析了沪深300股指期货与现货间的风险传染效应及影响因素,并结合研究结论提出对策,以期促进资本市场健康发展。结果表明:沪深300股指期货市场与现货市场间存在双向的风险传染效应,且经DCC-GARCH模型分析表明风险传染效应在动荡期尤为明显;影响这种风险传染效应的因素有很多,主要表现为微观因素中的股票市场流动性和股票市场不确定性与极端事件两个方面。     

中国绿色债券市场与金融市场间的风险溢出效应研究

本文基于向量自回归模型的预测误差方差分解方法,研究中国绿色债券市场与传统固定收益市场、股票市场以及外汇市场等多种类型的金融市场间的风险溢出效应。实证结果表明,绿色债券市场与包括国债、高收益企业债券以及公司债券市场在内的传统固定收益市场的风险溢出效应最为显著,与股市和外汇市场间的风险溢出效应微弱;绿色债券市场的对外溢出效应强于其接收到的来自其他市场的溢出效应,并且绿色债券市场与传统固定收益市场间的风险溢出具有较大的不确定性。     

货币政策对我国股票市场风险水平(CVaR)的影响

研究货币政策调整对股市风险的影响,对我国来说有理论上的必要性。本文在优选ARCH族模型对我国股市进行拟合的基础上,计算我国股票市场的条件风险价值(CVaR),进而以事件分析法探讨货币政策对股票市场条件风险价值的影响,并通过向量自回归模型(VAR)研究二者间长期均衡关系。     

东亚危机中金融传染的研究——基于香港、日本和新加坡股票市场的实证

本文选取香港、日本和新加坡股票市场指数,建立GARCH(1,1)模型刻画其波动性;然后采用相关分析、Granger因果检验和脉冲响应分析,分别对三个市场的收益率序列和波动率序列是否发生传染进行研究。研究结果表明,东亚危机中存在日本和新加坡股票市场之间收益率和波动率的溢出效应,即存在金融传染,传播路径为新加坡到日本;而日本、新加坡与香港市场间不存在传染机制,只存在依存关系。     

我国信贷市场、股票市场与房地产市场间的风险传染研究——基于VAR-GARCH-BEKK模型的实证分析

本文首先对信贷市场、股票市场与房地产市场间风险传染机理进行分析,在此基础上,用VAR-GARCH-BEKK模型对市场间的价格传导、风险积累与风险传染效应进行实证研究,得出三个市场间存在显著的价格传导效应及较大的风险积聚效应等结论,并据此提出完善我国金融市场的相关政策建议。     

公司债市场是新常态下证券市场的风险信号标吗？——基于公司债与股票市场间风险溢出的研究

以发行债券的上市公司为样本,分别编制公司债指数与股票指数,据此运用Copula-CoVaR模型测度公司债与股票市场间风险溢出的方向与强度。结果发现：股票市场的风险大于公司债市场;公司债与股票市场间存在双向不对称的正向风险溢出,公司债市场对股票市场的风险溢出强度显著强于股票市场对公司债市场的风险溢出强度。经济新常态下,公司债市场成为证券市场的风险指示标,具有较强的风险信号作用。     

波动溢出网络视角的金融风险传染研究

当前各类经济风险交叉关联,金融系统的风险溢出效应备受关注,为刻画我国金融系统性风险传染的路径特征,本文从波动溢出网络的视角分析金融系统内部的风险传染机制。首先使用广义动态因子模型对收益波动的共同波动率成分和特质性波动率成分进行区分。然后,根据货币市场、资本市场、大宗商品交易市场、外汇市场、房地产市场和黄金市场之间的特质性波动溢出效应,利用基于TVP-VAR模型的方差分解溢出指数分析金融系统波动溢出的动态联动性和风险传递机制。在分析方向性波动溢出效应的基础上,采用方差分解网络方法构建起信息溢出复杂网络,从网络视角分析金融系统内部的风险传染特征。实证研究发现,房地产市场和外汇市场的净溢出效应绝对值相较于其他市场更大,其受其他市场风险冲击的影响强于对外风险溢出效应,而股票市场的单向对外风险溢出效应强度最大。在波动溢出的基础上,进一步考虑股市波动率指数与其他市场波动率指数进行投资组合的资产配置权重,计算了波动率指数投资组合的最优组合权重和对冲策略。研究结论有助于更好地理解我国金融系统的风险传染机制,对监管机构加强宏观审慎监管、投资者规避投资风险具有重要意义。     

Financial contagion effects of major crises in African stock markets

This study examines financial contagion effects in African stock markets during major crises over the period 2005 to 2020. We investigate contagion effects in individual stock markets and from a regional perspective using dynamic conditional correlations during the global financial crisis, European debt crisis, Brexit, and COVID-19. The empirical evidence confirms contagion effects in some individual markets. However, significant evidence of contagion is found only during the global financial crisis from the regional perspective. Our findings suggest that the regional impacts of crises differ due to the nature of those crises. We also find financial contagion increases in the country-level risk, market capitalization and export to GDP and decreases in corruption.     

Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach

Measuring the systemic risk contribution (SRC) of country-level stock markets helps understand the rise of extreme risks in the worldwide stock system to prevent potential financial crises. This paper proposes a novel SRC measurement based on quantifying tail risk propagation's domino effect using ΔCoVaR and the cascading failure network model. While ΔCoVaR captures the tail dependency structure among stock markets, the cascading failure network model captures the nonlinear dynamic characteristics of tail risk contagion to mimic tail risk propagation. As an illustration, we analyze 73 markets' SRCs using a daily closing price dataset from 1990.12.19 to 2020.9.8. The validity test demonstrates that our method outperforms seven classic methods as it helps early warning global financial crises and correlates to many systemic risk determinants, e.g., the market liquidity, leverage, inflation, and fluctuation. The empirical results identify that Southeast European markets have higher SRCs with time-varying and momentum features corresponding to significant financial crisis events. Besides, it needs attention that South American and African markets have displayed increasing risk contributions since 2018. Overall, our results highlight that considering tail risk contagion's dynamic characteristics helps avoid underestimating SRC and supplement a “too cascading impactive to fail” perspective to improve financial crisis prevention.     

Global financial crisis and emerging stock market contagion: A volatility impulse response function approach

By employing the volatility impulse response (VIRF) approach, this paper presents a general framework for addressing the extent of contagion effects between the BRICSs’ and U.S. stock markets and how the BRICSs’ stock markets have been influenced in the context of the 2007–2009 global financial crisis. Our empirical results show during the period of 2007–2009 global financial crisis, there are significant contagion effects from the U.S. to the BRICSs’ stock markets. Yet, the degree of stock market reactions to such shocks differs from one market to another, depending on the level of integration with the international economy. Besides, the strengthened degree of stock market integration among the U.S. and BRICS has adverse effect such that if the 2007–2009 global financial crisis occurs today it may result in heavier impact on stock market volatility nowadays compared to the crisis-era.     

Interconnected multilayer networks: Quantifying connectedness among global stock and foreign exchange markets

This paper proposes a novel interconnected multilayer network framework based on variance decomposition and block aggregation technique, which can be further served as a tool of linking and measuring cross-market and within-market contagion. We apply it to quantifying connectedness among global stock and foreign exchange (forex) markets, and demonstrate that measuring volatility spillovers of both stock and forex markets simultaneously could support a more comprehensive view for financial risk contagion. We find that (i) stock markets transmit the larger spillovers to forex markets, (ii) the French stock market is the largest risk transmitter in multilayer networks, while some Asian stock markets and most forex markets are net risk receivers, and (iii) interconnected multilayer networks could signal the financial instability during the global financial crisis and the COVID-19 crisis. Our work provides a new perspective and method for studying the cross-market risk contagion.     

Tail risk contagion between international financial markets during COVID-19 pandemic

In this paper, we combine the time-varying financial network model and FARM-selection approach to analyze the tail risk contagion between international financial market during the COVID-19 epidemic. Since the tail risk acts as a global transmission channel, we use the sample of 19 international financial markets to explore the contagion of tail risk during the epidemic. We find that the COVID-19 epidemic increases the number of contagion channels in the international financial system. The clustering level of the financial system has a significant growth during the COVID-19 pandemic, and the number of risk drivers is also larger than risk takers. The key financial market of each international financial network is related to the epidemic country. We also consider the tail risk contagion in local financial markets and find that the COVID-19 pandemic has an important influence on the tail risk contagions in local network systems     

Contagion in financial markets after September 11: myth or reality?

Major global events can lead to a change in the cross‐country correlation of assets. Using stock prices from 25 economies, we test whether the terrorist attack in the United States on September 11, 2001, resulted in a contagion—an increase in correlation across global financial markets. Unlike prior works on contagion, we model the intrinsic heteroskedasticity. Our results indicate that international stock markets, particularly in Europe, responded more closely to U.S. stock market shocks in the three to six months after the crisis than before. Our evidence suggests that the benefits of international diversification in times of crisis are substantially diminished.     

中国股市羊群效应的区制转移时变性研究

传统研究采用静态CCK模型检验股票市场的羊群效应,但无法描述羊群行为的动态变化以及市场可能受到的外部影响。本文基于中国股市日频交易数据,在静态CCK模型中引入参数的区制转移性质识别股市在不同状态间的转换,并分析中国股市羊群效应和交叉羊群效应的时变特征。研究表明,中国股市运行周期可被划分为两个区制,分别呈现低波动和高波动的行情特征;羊群效应的程度随区制转移而变化,具有区制依存性。其中,沪深股市在高(低)波动区制中,羊群效应更强(弱),相应区制持续时间较短(长);中国台湾股市仅在高波动区制中出现羊群效应,相应区制持续时间较短;中国香港股市无论在低波动区制或是高波动区制中,均不存在羊群效应。此外,沪深A股在低波动区制中对美国股市和中国香港股市存在交叉羊群效应。     

Contagion effect in financial markets after the South-East Asia Tsunami

Powerful earthquakes may cause heavy damage to the financial markets of individual countries (regions), and may even spillover to other countries (regions). Using 26 international stock indexes and exchange rates, this study examines whether any contagion effect occurred across financial markets after the strong earthquake in South-East Asia on December 26, 2004. Using heteroscedasticity biases based on correlation coefficients to examine the existence of the contagion effect, this study shows that no individual country stock market suffered from the contagion effect, but that the foreign exchange markets of some countries (namely India, Philippines and Hong Kong) did suffer from the contagion effect.