我国证券投资基金、股票市场和债券市场的溢出风险测度——来自上海证券市场的证据

本文基于VAR-DCC-MGARCH模型分析了沪市基金指数与股票指数和国债指数的波动相关性和溢出效应,估计了三个市场的VaR,并通过失败检验法进行了验证,研究发现:基金市场与股票市场的条件相关系数一直呈现正向相关关系;股票市场与国债市场以及基金市场与国债市场的动态条件相关系数具有很强的时变特征,而且走势呈现相似性,但是统计检验显示基金市场与国债市场的相关性不明显。基金市场对自身和股票市场存在显著波动溢出效应,股票市场对国债市场和基金市场存在一定显著的波动溢出效应。在给定期望损失概率下,发现基金指数收益率的VaR波动最为剧烈;股票指数收益率的VaR变动风险与均值的比值是最高的;结合剔除其他市场波动影响的VaR发现,三个市场的风险承受度更高,可以接受更大的损失收益率。     

美债牛市接近尾声

美国国债一直被认为是与美元等量齐观的全球流通性最好的金融资产,且基本无违约风险,是各国政府和投资者的优选投资品。2011年下半年以来,随着欧债危机愈演愈烈,美债上演了一轮“超级行情”。然而近期,欧债危机进入中场休息,美国国债收益率却出现罕见的火幅飙升,这是否意味着美田困债市场牛市接近尾声？     

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.     

对近期我国能否发生债务危机的定量分析

为实施积极财政政策而迅速膨胀的国债规模，引发了社会各界对财政风险和债务危机的广泛关注。根据国内外的理论与实践，定量分析我国财政的举措能力和应债主体的承受能力，我国到2010年以前不会发生债务危机。     

欧元区债市曲折前进

今年以来,欧元区的债券市场走势趋稳。首先,欧元区的整体风险和危机国家的国别风险明显降低,加之逐步见底反弹的宏观经济,以及持续宽松的货币政策,危机国家的国债收益率继续整体下降。意大利和西班牙等危机国家的国债收益率已经降至接近危机之前的水平,不过进入2013年后降幅明显趋缓。其次,随着欧元区渐渐走出欧债危机的泥潭,核心国家德国作为避险天堂的作用逐步减弱,投资德国国债的资金开始流出,德国的国债收益率稳中有升。     

关于黄金、国债、金融债的安全资产属性研究——基于资产避险功能和对冲功能的实证研究

本文在梳理安全资产相关定义的基础上，运用GARCH类模型分析中国金融市场中黄金、国债、金融债三类资产的安全资产属性。安全资产属性分析包括：第一，通过分析经济危机时期资产回报率与股票资产回报率是否存在负相关性来考量资产的避险功能；第二，通过分析经济平稳时期资产回报率与股票资产回报率是否存在负相关性来考量资产的风险对冲功能。研究结果显示：第一，在2008年全球金融危机期间，国债未能表现出对股票市场的避险功能，而黄金、金融债均表现出对股票市场存在弱避险功能；第二，在2020年初新冠疫情暴发期间，黄金、国债、金融债均表现出对股票市场风险的强避险功能，其中黄金避险功能最为强大；第三，从整体样本区间来看，国债和金融债对股票市场具有较强的风险对冲能力，其中，国债对冲风险的能力强于金融债。因此，结合资产的避险功能和风险对冲功能，本文认为国债、金融债具备一定的安全资产属性，可以作为中国金融市场上的安全资产，而黄金仅为避险资产。     

宏观经济变量对中国国债风险溢价影响的实证研究——基于上海证券交易所的交易数据

本文基于面板数据模型,对各主要宏观经济变量及利率期限结构对国债风险溢价的影响进行了实证研究.研究结果表明:国债利率期限结构曲线越陡峭,国债的风险溢价水平越高;通货膨胀因素对国债风险溢价水平的影响较大;规模以上工业增加值、上证综合指数月度收益率与L 债风险溢价水平存在显著负相关关系;广义货币供应量与国债风险溢价水平存在显著正相关关系;官方利率与国债风险溢价水平的关系较弱.     

中国股债市场长期动态相关性的影响因素研究——基于宏观不确定性和协动性视角

本文借鉴现代宏观经济学中的无套利仿射模型,基于"定价核"的定价方式,将股票市场和债券市场收益率之间的相关系数分解为其主要驱动因素--通货膨胀、真实利率和股息率的不确定性,以及三者之间的协方差。在实证部分,采用DCC-MGARCH模型计算股票市场和债券市场收益率的动态相关系数,验证中国股债相关性的时变规则;进而通过回归分析探究所选取的解释变量对中国股债相关性的贡献。结果表明,通货膨胀和股息率的不确定性以及真实利率与通货膨胀和股息率各自之间的协动性是影响这种相关性的主要因素;通胀冲击、真实利率和股息率可以解释这种相关性与长期动态的暂时背离。其中,通货膨胀和股息率的不确定性对股债相关性的影响与其他欧美主要经济体有着不同的表现,反映了中国市场的特殊性;此外,相较于中国经济市场的平稳时期,股市动荡期间各经济因素的影响会发生改变,且模型解释力会降低。     

新一轮欧债危机的演进与应对

本轮危机的特点是,欧债危机与美债危机同时爆发,两种危机的叠加将给全球金融市场与实体经济造成相当剧烈的冲击尽管进入7月底8月初以来,关于美国国债上限的争论以及美国国债信用等级被调降的冲击吸引了国际金融市场的注意力,然而与美债危机相比,最近卷土重来的欧债危机同样凶险,后者在短期内对国际金融市场的冲击可能更为显著。演进历程     

基于Fuzzy-AHP方法的我国国债风险预警指标分析

为了准确判断国债风险的存在,并有效地对国债风险加以控制,本文首先根据已有文献建立了国债风险预警指标体系,构建了基于三角模糊数的AHP评价方法,对国债风险预警指标体系中指标的重要性进行排序,以便在时间和资源有限的情况下优先对重要的指标进行预警,同时加以控制以避免国债风险。根据专家提供的指标对比矩阵,通过算法处理得到国债风险预测体系中指标的重要性排序为:国债负担率、国债偿债率、国债依存度、赤字率、国民应债率、国债借债率、居民应债率。     

Volatility transmission between stock and bond markets

A two-factor no-arbitrage model is used to provide a theoretical link between stock and bond market volatility. While this model suggests that short-term interest rate volatility may, at least in part, drive both stock and bond market volatility, the empirical evidence suggests that past bond market volatility affects both markets and feeds back into short-term yield volatility. The empirical modelling goes on to examine the (time-varying) correlation structure between volatility in the stock and bond markets and finds that the sign of this correlation has reversed over the last 20 years. This has important implications far portfolio selection in financial markets.     

Multiscale stock-bond correlation: Implications for risk management

This paper examines the multiscale return correlation between the stocks and government bonds of different maturities returns in 25 countries. The analysis reveals that developed markets correlations are generally negative at the first time-scale and move in a positive direction at higher scales. This contrasts with emerging markets, where the correlation tends to be positive throughout. Thus, the results support a greater flight-to-safety effect in developed markets. Further evidence highlights the ability of the correlation to produce portfolios with a lower VaR. Results support this at longer time-scales and for both developed and emerging markets. The results here demonstrate the importance of accounting for time-scales in modelling the stock-bond correlation and in constructing portfolios.     

Impact of financial market uncertainty and macroeconomic factors on stock–bond correlation in emerging markets

This paper examines the impact of global financial market uncertainty and domestic macroeconomic factors on stock–bond correlation in emerging markets. In particular, by applying the wavelet analysis approach, we are able to examine stock–bond correlations over different time horizons in ten emerging markets. We find that stock–bond correlation patterns vary significantly between the time horizons. In particular, the correlation in short horizon changes the sign rapidly showing sustainable negative episodes while the correlation in long horizon stays positive most of the time. The most important factor influencing stock–bond correlation in short horizon is the monetary policy stance, while the factors with the greatest long-term impact are inflation and stock market uncertainty. Finally, global stock market uncertainty plays a more significant role than global bond market uncertainty in explaining stock–bond correlations in emerging markets.     

极端风险事件下股票市场与公司债券市场的尾部风险溢出研究——基于MVMQ-CAViaR模型

构建MVMQ-CAViaR模型,结合金融市场内部极端风险事件和外部极端风险事件,考量股票市场与公司债券市场的尾部风险溢出问题。结果表明,在金融市场内部极端风险事件下,股灾期间仅存在股票市场对公司债券市场单向的尾部风险溢出。公司债券违约潮期间,股票市场与公司债券市场之间存在双向不对称的尾部风险溢出,且公司债券市场对股票市...     

Analysis of risk correlations among stock markets during the COVID-19 pandemic

The outbreak of the COVID-19 pandemic significantly negatively impacted the global economy and stock markets. This paper investigates the stock-market tail risks caused by the COVID-19 pandemic and how the pandemic affects the risk correlations among the stock markets worldwide. The conditional autoregressive value at risk (CAViaR) model is used to measure the tail risks of 28 selected stock markets. Furthermore, risk correlation networks are constructed to describe the risk correlations among stock markets during different periods. Through dynamic analysis of the risk correlations, the influence of the COVID-19 pandemic on stock markets worldwide is examined quantitatively. The results show the following: (i) The COVID-19 pandemic has caused significant tail risks in stock markets in most countries, while the stock markets of a few countries have been unaffected by the pandemic. (ii) The topology of risk correlation networks has become denser during the COVID-19 pandemic. The impact of the COVID-19 pandemic makes it easier for risk to transfer among stock markets. (iii) The increase in the closeness of the risk relationship between countries with lower economic correlation has become much higher than that between counties with higher economic correlation during the COVID-19 pandemic. For researchers and policy-makers, these findings reveal practical implications of the risk correlations among stock markets.     

Equilibrium moment restrictions on asset returns: normal and crisis periods

Empirically, the covariance between stock returns varies with their volatility. We seek a robust theoretical explanation of this. With minimal assumptions, we model stochastic properties of equilibrium returns which result from the interaction between inter-temporal traders and noisy, price-sensitive short-term traders. The inter-temporal traders can have arbitrary investment rules, preferences and information. In all cases we find a set of restrictions between second moments of equilibrium returns. With two assets there is also a bound on the correlation between asset returns. Estimation with second moments of global stock returns supports our theoretical framework. Higher volatility in at least one market can increase comovement among markets. With globalization, covariances between two stock markets can also affect covariances between two other stock markets. We also find that the changes in trader behavior between normal and crisis periods lead to changes in the moment restrictions between asset returns.     

Return–volume nexus in financial markets: A survey of research

This paper provides a systematic review of the return–volume literature, broadly defined to include theoretical and empirical research relating to the intramarket and cross-market interlinkages between security return and trading volume characteristics in four financial markets, namely, the stock, bond, foreign exchange, and futures markets. Viewed through this lens, this paper attempts to review previous empirical research within a unified theoretical framework that relates the interlinkages between return and volume characteristics in various financial markets. Overall, this paper marks several interesting areas of debate and controversy based on several controversial theories and empirical findings in the literature, suggesting directions for future research.     

Extreme Correlation of Stock and Bond Futures Markets: International Evidence

This study explores time‐varying extreme correlation of stock–bond futures markets in three major developed countries. In the United States and the United Kingdom, there is evidence of positive extreme stock–bond correlation when both futures markets are extremely bullish or bearish. In Germany, stock–bond futures extreme correlation is negative, suggesting the most diversification potentials of bond futures when German stock index futures market plunges. Macroeconomic news, the business cycle, and the stock market uncertainty all significantly affect the median stock–bond futures correlation. However, only the stock market uncertainty still significantly affects the extreme stock–bond futures correlation when the stock market is extremely bearish.     

Stock–bond dependence and flight to/from quality

This paper investigates the stock–bond dependence structure using a dependence-switching copula model. The model allows stock–bond dependence to switch between positive dependence regimes (contagions or crashes of the two markets during downturns or booms in both markets during upturns) and negative dependence regimes (flight-to-quality from stock markets to bond markets or flight-from-quality from bond markets to stock markets). Using data from four developed markets including the US, Canada, Germany, and France for the period between January 1985 and August 2022, we find that the within-country stock–bond (extreme) dependence could be both positive and negative. In the positive dependence regimes, the stock–bond dependence is asymmetric with stronger left tail dependence than the right tail dependence, giving evidence of a higher likelihood of joint stock–bond market crashes or contagions during market downturns than the collective stock–bond market booms. Under the negative dependence regimes, we find both flight-from-quality and flight-to-quality, with flight-to-quality being more dominant in the North American markets while flight-from-quality is more prominent in the European markets. Further, the dependence switches between positive and negative regimes over time. Moreover, the dependence is mainly in the positive regimes before 2000 while mostly in the negative regimes after that, indicating contagions mostly before 2000 and flights afterwards. Further, the dependence switches between positive and negative regimes around financial crises and the COVID-19 pandemic. These results greatly enrich the findings in the existing literature on the co-movements of stock–bond markets and are important for risk management and asset pricing.     

中外股票市场收益率相关性分析及其影响路径分解

本文通过计算相关系数,研究了过去15年中国股票市场与国际股票市场收益率的相关性,发现在金融危机爆发的年份里,中外股票市场的收益率存在负相关关系。本文在此基础上利用面板数据回归模型,研究了影响中外股票市场收益率相关性的主要因素,发现出口路径会显著增强收益率的正相关性,对经济危机起到传导作用;外商直接投资路径会显著增强收益率的负相关性,对经济危机起到缓冲作用。建议政府在制定应对金融危机的政策时,积极利用外商直接投资的缓冲作用,同时不断引导出口企业增强国际竞争力,努力扩大内需,减少经出口路径传导至我国的外部冲击。