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1.
杨翱 《海南金融》2014,(4):20-25
本文选取最具代表性的欧盟碳排放权交易体系为研究对象,选用2008年3月3日至2012年12月31日洲际交易所官方网站公布的每日欧盟碳减排配额(EUA)期货市场价格作为分析对象,用 GARCH 模型估计厚尾分布下的EUA日收益率的波动性,并运用极值理论对收益率的尾部进行建模,得到在不同置信水平下有效而准确的VaR估计和ES估计,利用阈值法建立厚尾分布(GED 分布)下GARCH-EVT-VaR动态模型,并对该模型进行返回检验,进一步验证了该模型的准确性。结果表明基于极值理论的GARCH-EVT-VaR模型比传统模型更适合度量厚尾分布下的金融时间序列,是刻画碳市场尾部风险的有效工具。  相似文献   

2.
股价指数的收益率序列具有时变波动性、厚尾特征、波动性群集等特点,传统的计量分析无法刻画这些特点。文章利用ARCH族模型,选取2003年1月20日~2013年12月12日上证指数每日收益率共2621个数据对其波动进行定量与定性的分析,结果显示,上证指数日收益率存在高阶的ARCH效应,杠杆效应,波动集聚性特征,条件方差对日收益率有很强的影响,其中EGARCH模型在反映股市波动性方面优于其他模型。  相似文献   

3.
通过因子分析从诸宏观经济变量中提取了金融政策因子和宏观经济状态因子,建立了基于VAR的股价波动、金融政策和宏观经济三变量回归模型。研究表明:金融政策影响股价的表现,而宏观经济状态对股价、股价对金融政策和宏观经济状态的影响均不显著;基于标准差的VAR(5)模型相对于基于收益率的VAR(3)模型能更好地刻画股市波动与金融政策、宏观经济三者之间的关系。  相似文献   

4.
基于马尔科夫区制转移模型,在刻画全球金融周期特征的基础上,构建包含调节效应的面板模型,对货币政策与汇率政策有效协调机制进行实证分析。结果表明:全球金融周期处于高波动率区制,即市场风险厌恶水平较高时,资本流动水平较低,浮动汇率政策能够有效缓解资本流动对货币政策独立性的影响;反之,浮动汇率政策调节效果减弱。因此在推进金融开放与人民币汇率市场化改革的进程中,要充分关注全球金融周期波动状况。  相似文献   

5.
本文以2010年6月21日~2019年4月30日期间的上证综合指数、上证国债指数以及人民币兑美元汇率的收益率为样本,基于ARFIMA-HYGARCH模型分别对我国股债汇风险点的长记忆特征进行刻画,并在此基础上构建三元VFIAR-DCC-HYGARCH模型,旨在探究各自间的关联性问题。结论如下:股市收益的长记忆性不显著,而波动存在显著的长记忆特征;债市和汇市的收益与波动存在显著的双长记忆特征;三大风险点间的关联程度均较低,但具有很强的波动时变性,其中股市与债市、债市与汇市表现为正相关关系,股市与汇市表现为负相关关系。基于以上结论,本文为如何有效防范金融风险提出了相应的建议。  相似文献   

6.
基于SVI函数、平远期插值和Dupire公式,提出NALVS局部波动率建模算法,成功解决了中国期权市场上"有套利"和"少数据"两大难题,构建得到上证50ETF期权无套利局部波动率曲面.研究发现:(1)无套利局部波动率曲面可灵活刻画波动率偏态和期限结构,充分挖掘市场信息;(2)不同时期,上证50ETF期权波动率曲面性态不尽相同,具体表现为NALVS算法下波动率参数的时变性;(3)NALVS算法比BS模型和GARCH模型在场外期权复制对冲上能够得到更小的对冲误差,表明该算法更有利于金融机构对场外期权进行复制和静态对冲.  相似文献   

7.
基于动态随机一般均衡框架构建模型,采用校准和贝叶斯技术对模型参数进行估计,并通过对比实际经济与模拟经济评价模型。通过引入货币政策、房地产偏好、供给和通胀四种冲击,对比有无抵押品的模型以观察房地产抵押品渠道视角的金融加速机制是否存在。研究发现,抵押品效应是金融加速机制存在的重要原因。表现一是抵押品效应存在时,各冲击下的主要经济变量的波动更显著,二是房地产作为重要资产,在抵押品效应存在时房地产的财富效应更明显。  相似文献   

8.
宫晓莉  熊熊 《金融研究》2020,479(5):39-58
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。  相似文献   

9.
为了考察人民币汇率高阶矩风险的动态特征,本文首先采用拉格朗日乘子检验对人民币/美元名义汇率收益率序列是否存在异方差、异偏度和异峰度效应进行判断,然后运用自回归条件方差偏度峰度模型对汇率波动的高阶矩风险进行测量.研究表明,人民币汇率波动的方差风险和偏度风险具有时变特征,而峰度风险不具有时变性,鉴于人民币汇率风险的时变性,应该从动态角度进行汇率风险的防范与规避.  相似文献   

10.
GARCH族模型是金融计量学中用来描述或预测金融资产收益率波动的模型,通过对金融资产收益率波动的建模,可以得出未来金融资产收益率的条件分布。Copula函数可以用来描述多个随机变量间的相依结构,进而得出他们的联合分布。Copula自被引入金融产品分析以来,以取得了很多成果也被广泛使用。运用GARCH族模型进行资产组合中边缘分布的建模,继而使用Copula得到组合资产联合分布的方法来计算资产组合VaR值最早被吴振翔(2006)系统性地提出,但其中有许多问题仍需要完善。本文将继续这个思路,通过EGARCH模型更好地描述资产收益率的杠杆效应,以及考虑Copula函数中参数的时变性,来完善这一方法。  相似文献   

11.
This paper presents a Markov chain Monte Carlo (MCMC) algorithm to estimate parameters and latent stochastic processes in the asymmetric stochastic volatility (SV) model, in which the Box-Cox transformation of the squared volatility follows an autoregressive Gaussian distribution and the marginal density of asset returns has heavy-tails. We employed the Bayes factor and the Bayesian information criterion (BIC) to examine whether the Box-Cox transformation of squared volatility is favored against the log-transformation. When applying the heavy-tailed asymmetric Box-Cox transformed SV model, three competing SV models and the t-GARCH(1,1) model to continuously compounded daily returns of the Australian stock index, we find that the Box-Cox transformation of squared volatility is strongly favored by Bayes factors and BIC against the log-transformation. While both criteria strongly favor the t-GARCH(1,1) model against the heavy-tailed asymmetric Box-Cox transformed SV model and the other three competing SV models, we find that SV models fit the data better than the t-GARCH(1,1) model based on a measure of closeness between the distribution of the fitted residuals and the distribution of the model disturbance. When our model and its competing models are applied to daily returns of another five stock indices, we find that in terms of SV models, the Box-Cox transformation of squared volatility is strongly favored against the log-transformation for the five data sets.  相似文献   

12.
Abstract:  We propose generalised stochastic volatility models with Markov regime changing state equations (SVMRS) to investigate the important properties of volatility in stock returns, specifically high persistence and smoothness. The model suggests that volatility is far less persistent and smooth than the conventional GARCH or stochastic volatility. Persistent short regimes are more likely to occur when volatility is low, while far less persistence is likely to be observed in high volatility regimes. Comparison with different classes of volatility supports the SVMRS as an appropriate proxy volatility measure. Our results indicate that volatility could be far more difficult to estimate and forecast than is generally believed.  相似文献   

13.
In this paper, we investigate the volatility in stock markets for the new European Union (EU) member states of the Czech Republic, Hungary, Poland, Slovenia and Slovakia by utilising the Markov regime switching model. The model detects that there are two or three volatility states for the emerging stock markets. The result reveals that there is a tendency that the emerging stock markets move from the high volatility regime in the earlier period of transition into the low volatility regime as they move into the EU. Entry to the EU appears to be associated with a reduction of volatility in unstable emerging markets.  相似文献   

14.
Despite its obvious importance, little empirical research has examined the impact of political risk on stock market volatility. This paper uses data on the Hong Kong stock market over a long sample period to investigate whether political risk has induced regime shifts in stock market volatility. Regime shifts are modelled via a Markov switching EGARCH model that allows for regime-dependent volatility asymmetry. We find strong evidence of regime shifts in conditional volatility as well as significant volatility asymmetry in high volatility periods. Major political uncertainties were reflected in a switch to the high-volatility regime. However, contrary to popular perceptions, we find no evidence that the Hong Kong stock market has become persistently more volatile since the start of Sino-British political negotiations in 1982.  相似文献   

15.
We develop a Vector Heterogeneous Autoregression model with Continuous Volatility and Jumps (VHARCJ) where residuals follow a flexible dynamic heterogeneous covariance structure. We employ the Bayesian data augmentation approach to match the realised volatility series based on high-frequency data from six stock markets. The structural breaks in the covariance are captured by an exogenous stochastic component that follows a three-state Markov regime-switching process. We find that the stock markets have higher volatility dependence during turmoil periods and that breakdowns in volatility dependence can be attributed to the increase in market volatilities. We also find positive correlations between the Asian stock markets, the European stock market, and the UK stock market. The US stock market has positive correlations with all other markets for most of the sample periods, indicating the leading position of US stock market in the global stock markets. In addition, the proposed three-state VHARCJ model with Dynamic Conditional Correlation (DCC) and break structure under student-t distribution has a superior density forecast performance as compared to the competing models. The forecast models with structural breaks outperform those without structural breaks based on the log predicted likelihood, the log Bayesian factor, and the root mean square loss function.  相似文献   

16.
隋建利  刘碧莹 《金融研究》2020,485(11):1-20
随着人民币国际化进程的逐步推进,SDR货币篮子中人民币的国际化定位引人瞩目。本文基于非线性MSBIARCH模型,实时甄别人民币市场与美元市场、英镑市场、日元市场、欧元市场之间的波动传染关系,以及波动传染作用下汇率市场的波动聚类态势,进而识别SDR货币篮子中人民币的国际化定位,旨在为及时防范并规避人民币市场的波动风险提供参考。研究发现,汇率市场经由“经济基本面”“市场情绪”以及“市场预期”对外发挥波动传染作用,人民币市场与美元市场之间存在双向波动传染关系,与英镑市场、欧元市场以及日元市场之间存在单向波动传染关系。不同汇率市场之间的波动传染关系表现出时间区制转移特征,汇率市场的波动聚类态势也呈现时变特征。汇率市场发挥波动传染作用的时间与汇率市场呈现波动聚类态势的时间相匹配,均集中在极端经济事件期、不规则事件期以及政策颁布事件期。国际汇率市场的波动传染作用导致了人民币市场的波动聚类态势,而人民币市场的波动传染作用仅强化了国际汇率市场的波动聚类态势,SDR货币篮子中人民币的国际化程度有待进一步提高。  相似文献   

17.
The mechanism of risk responses to market shocks is considered as stagnant in recent financial literature, whether during normal or stress periods. Since the returns are heteroskedastic, a little consideration was given to volatility structural breaks and diverse states. In this study, we conduct extensive simulations to prove that the switching regime GARCH model, under the highly flexible skewed generalized t (SGT) distribution, is remarkably efficient in detecting different volatility states. Next, we examine the switching regime in the S&P 500 volatility for weekly, daily, 10-minute and 1-minute returns. Results show that the volatility switches regimes frequently, and differences between the distributions of the high and low volatility states become more accentuated as the frequency increases. Moreover, the SGT is highly preferable to the usually employed skewed t distribution.  相似文献   

18.
Traditional quantitative credit risk models assume that changes in credit spreads are normally distributed but empirical evidence shows that they are likely to be skewed, fat-tailed, and change behaviour over time. Not taking into account such characteristics can compromise calculation of loss probabilities, pricing of credit derivatives, and profitability of trading strategies. Therefore, the aim of this study is to investigate the dynamics of higher moments of changes in credit spreads of European corporate bond indexes using extensions of GARCH type models that allow for time-varying volatility, skewness and kurtosis of changes in credit spreads as well as a regime-switching GARCH model which allows for regime shifts in the volatility of changes in credit spreads. Performance evaluation methods are used to assess which model captures the dynamics of observed distribution of the changes in credit spreads, produces superior volatility forecasts and Value-at-Risk estimates, and yields profitable trading strategies. The results presented can have significant implications for risk management, trading activities, and pricing of credit derivatives.  相似文献   

19.
This paper investigates the presence of the leverage effect in commodities, in comparison with financial markets. The EGARCH model with a Mixture of Normals distribution (EGARCH-MN) is used to capture (i) heavy tails and skewness in the conditional returns, and (ii) leverage effects and time-varying long-term component in the volatility specification. Besides, the estimation strategy relies on an innovative recursive (REC) method, which allows disentangling the leverage effect from the unconditional skewness as an empirical result. When applied to a broadly diversified dataset of assets during 1995–2012, the EGARCH-MN models offers state-of-the-art specifications with leverage and fat-tailed skewed densities, that allow to contrast the specific characteristics of commodities with traditional assets (equities, bonds, FX).  相似文献   

20.
While the time-varying volatility of financial returns has been extensively modelled, most existing stochastic volatility models either assume a constant degree of return shock asymmetry or impose symmetric model innovations. However, accounting for time-varying asymmetry as a measure of crash risk is important for both investors and policy makers. This paper extends a standard stochastic volatility model to allow for time-varying skewness of the return innovations. We estimate the model by extensions of traditional Markov Chain Monte Carlo (MCMC) methods for stochastic volatility models. When applying this model to the returns of four major exchange rates, skewness is found to vary substantially over time. In addition, stochastic skewness can help to improve forecasts of risk measures. Finally, the results support a potential link between carry trading and crash risk.  相似文献   

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