中国经济波动特征的研究——基于ARCH类模型

一个国家经济的波动对经济的发展有很大的影响。本文引入ARCH类模型,在简要介绍模型的基础上,基于中国1953~2012年实际GDP增长率的数据进行实证分析,探究我国经济增长的波动特征。结果表明:GARCH(1,1)模型较好地表示了我国经济的波动,该波动具有很强的波动聚集性和波动持续性;我国经济的波动不存在不对称性;经济增长的波动性增加将导致增长率绝对水平的提高,但是该影响效果并不明显。     

中国实际GDP波动率的实证研究

本文对中国实际国内生产总值增长率的波动率进行了一种实证分析．利用最大似然方法估计了三种GARCH类模型(GARCH、T-GARCH和E-GARCH)、实证研究表明．GARCH模型提供了最好的统计拟合，它表明波动率是变化的．对GDP实际增长率是对称的。     

基于ARCH类模型的VaR方法在外汇风险计量中的应用

本文将残差项服从t分布的ARCH类模型应用于我国外汇风险的计量。通过美元/人民币汇率日波动率VaR值的实证分析发现:(1)ARCH类模型预测得到的VaR值都能很好地拟合美元/人民币汇率日波动率的实际情况,美元/人民币汇率存在明显的ARCH效应;(2)基于ARCH类模型预测的VaR值其计算精度基本上都超过了J.P.Morgan公司RiskMetrics所采用的EWMA模型,这验证了本文选取ARCH类模型以及考虑残差项服从t分布的合理性;(3)ARCH类模型中以TARCH-M(1,1)模型计算结果最为理想。本研究可为金融机构、监管部门以及外汇投资者规避外汇风险提供决策依据和理论参考。     

我国汇市与股市之间的价格和波动溢出效应实证研究

为了考察我国汇市与股市之间的价格和波动溢出效应,本文利用"汇改后"人民币对美元的汇率与上证综指的日数据建立了多元向量自回归模型GARCH模型.研究发现,我国汇市与股市之间的价格溢出效应不明显,汇率波动率的ARCH效应不对股票市场产生显著的冲击,外汇市场波动的持久性会对股票市场产生显著的影响;股票收益率的ARCH效应不会对外汇市场产生明显的冲击,但股票收益率波动的持久性会显著影响汇率的变化率.     

基于ARCH族模型的白银市场与黄金市场收益率波动性研究

本文选取上海黄金交易所2006年10月至2015年12月的白银与黄金合约产品的日交易数据,通过运用ARCH族模型,分析白银市场与黄金市场的ARCH效应、杠杆效应与波动溢出效应。结果发现白银与黄金日收益率序列具有明显的ARCH效应,利好消息比利空消息在白银市场上能产生更大的影响,而利空消息在黄金市场会产生更大的市场波动。白银市场与黄金市场存在双向影响,但黄金市场对白银市场的影响更加明显。     

我国房地产指数收益率的波动性研究

自回归条件异方差(ARCH)模型是最简单的条件异方差模型,ARcH类模型在金融时序数据的波动性中具有很好的效果。文章利用ARcH类模型对我国房地产指数增长率的波动性进行了实证研究。结果表明房地产指数存在着明显的ARcH效应;GARCH模型更能准确地描述房地产指数的波动特征,且其波动性是对称、持续性的,房地产指数不存在明显的杠杆效应。     

经济时间序列波动率的度量与ARCH

尽管金融经济学家很早就知道经济时间序列的波动率有簇聚效应，并且边际分布具有尖峰形态，但却一直没有建立能够反映这种特点的时间序列模型。恩格尔在20世纪80年代早期开始了波动率模型的研究，成功地突破了传统的时间序列统计分析方法，开创性地建立了随时间变化的波动率模型一自相关条件异方差(ARCH)模型，从而有力地推动了金融经济学的发展。本文介绍了ARCH模型的产生背景、模型结构及其对金融经济学的学术价值。     

沪深300指数收益率波动性分析——基于GARCH模型

波动率的研究是资产定价方面的一个重要的研究方向,其中波动率估计准确与否直接关系到模型运用是否得当,投资的策略是否成立。沪深300指数是时衡量中国资本市场波动的一个重要标志。本文以2005年至2015年2455天样本数据为研究对象,运用ARCH和GARCH模型,研究发现沪深300指数日收益率波动呈现出明显的可变性和波动集簇性,序列分布呈现尖峰厚尾等特点,并且存在明显的GARCH效应,而且,过去的波动对未来的影响逐渐衰减。     

我国深沪股票市场波动的对比分析

金融市场的波动是现代金融学研究的核心问题．而ARCH类模型已经成为国际上最常用的研究金融资产波动的模型。它的一个最大特点就是突破了传统方法中收益与风险线性关系的假定．反应了方差的时变特点。随着ARCH类模型的不断应用，它本身的形式也不断得以发展。出现了非对称的ARCH模型和成分ARCH模型。我国学者近年来也利用ARCH类模型做了许多的研究。陈泽中等（2000）使用GARCH模型指出了我国深市比沪市波动剧烈。王玉荣（2002）使用了ARCH类模型模拟了我国股市收益率波动状况．指出了中国股市波动存在聚类性和非对称性。陈浪南等（2002）也对我国股票市场波动的非对称性做了研究。李丽莎（2004）使用了三种ARCH模型再次描述了我国股票市场收益率波动状况。朱孔来（2005）运用TARCH模型进一步分析了日收益率波动的条件异方差性和非对称性。在上述的研究中．部分文献所采用的时问段过短．这对于最终结论是有一定的影响的．尤其是对于EGARCH模型的使用影响很大。同时部分文献所采用的数据没有经过平稳性的检验．因为早期的中国股市达不到弱式有效。价格指数通不过平稳性的检验。本文使用2000年深沪市的价格指数日收盘序列，都可以通过平稳性的检验．同时，本文还检验了常用的几类ARCH模型．得出了EGARCH可以较好的模拟我国股市波动状况的结论。     

石油市场与黄金市场收益率波动溢出效应研究

在总结国内外相关研究的基础上,基于2002年12月2日到2010年9月30日的日数据,建立相应的ARCH族模型,并进行Granger因果关系检验,本文对石油市场和黄金市场收益的波动性、波动的非对称性及其波动溢出效应进行实证分析。结果表明:两市均具有显著的方差时变性及新信息对波动冲击的持续性;GARCH(1,1)模型能够很好地消除其ARCH效应;两市均存在明显的非对称性,即石油市场中利空消息引起的波动比同等利好消息引起的波动要大,而黄金市场相反;两市只存在从石油市场到黄金市场的单向波动溢出效应。研究结果对该领域投资者的相关投资及决策人的决策制定具有重要的参考价值。     

Volatility forecasts and at-the-money implied volatility: a multi-component ARCH approach and its relation to market models

This article explores the relationships between several forecasts for the volatility built from multi-scale linear ARCH processes, and linear market models for the forward variance. This shows that the structures of the forecast equations are identical, but with different dependencies on the forecast horizon. The process equations for the forward variance are induced by the process equations for an ARCH model, but postulated in a market model. In the ARCH case, they are different from the usual diffusive type. The conceptual differences between both approaches and their implication for volatility forecasts are analysed. The volatility forecast is compared with the realized volatility (the volatility that will occur between date t and t + ΔT), and the implied volatility (corresponding to an at-the-money option with expiry at t + ΔT). For the ARCH forecasts, the parameters are set a priori. An empirical analysis across multiple time horizons ΔT shows that a forecast provided by an I-GARCH(1) process (one time scale) does not capture correctly the dynamics of the realized volatility. An I-GARCH(2) process (two time scales, similar to GARCH(1,1)) is better, while a long-memory LM-ARCH process (multiple time scales) replicates correctly the dynamics of the implied and realized volatilities and delivers consistently good forecasts for the realized volatility.     

The intertemporal volatility structure of Euro CD rates

In this paper we examine the intertemporal volatility structure of Eurocurrency rates of five different maturities ranging from seven days to twelve months for six Euro CD currency denominations spanning the 1986–1992 period. the analysis used the common ARCH-feature testing methodology recently developed by Engle and Kozicki (1993). First, the results indicate presence of ARCH effects in the Eurocurrency rate series. This result suggests that modelling of Eurocurrency rates requires the inclusion of time-varying risk premia. Second, our evidence reveals that short- and long-term Eurocurrency rate series have the same volatility process. the results point out that a common time-varying volatility process characterises most Eurocurrency rate series across maturities and currency denominations. Hence, the common ARCH results imply that a common time-varying variance model would be the appropriate specification of the conditional heterscedasticity for most Eurocurrency rates.     

中国股市开、收盘波动性的比较研究

利用EGARCH模型,对2000年1月至2007年4月间沪深两市具有代表性的股票及指数的开收盘收益率的波动性进行实证分析,结果表明收益率序列有明显的ARCH效应,其波动性具有显著的非对称性的冲击的持续性;在样本期内,上交所的个股和指数未能观察到开盘波动性高于收盘波动性的现象,而深交所个股在2006年7月实施收盘集合竞价机制之后比较明显地观察到开盘波动性高于收盘波动性的现象。     

The Dynamics of Discrete Bid and Ask Quotes

This paper presents an empirical microstructure model of bid and ask quotes that features discreteness, random costs of market making, and ARCH volatility effects. Applied to intraday quotes at 15-minute intervals for Alcoa (a randomly chosen Dow stock), the results show that quote exposure costs contain stochastic components that are persistent and large relative to the deterministic intraday "U" components. Analysis of the filtered estimates of the system suggest that bid and ask costs contain common components, and that these costs reflect risk as proxied by ARCH variance forecasts.     

Exchange rate volatility and productivity growth: The role of financial development

The vast empirical exchange rate literature finds the effect of exchange rate volatility on real activity to be small or insignificant. In contrast, this paper offers empirical evidence that real exchange rate volatility can have a significant impact on productivity growth. However, the effect depends critically on a country's level of financial development. The results appear robust to time window, alternative measures of financial development and exchange rate volatility, and outliers. We also offer a simple monetary growth model in which real exchange rate uncertainty exacerbates the negative investment effects of domestic credit market constraints.     

Volume and Volatility: News or Noise?

This paper presents a market microstructure model that is consistent with several empirical regularities. The model embeds separate latent ARCH‐like volatility processes: one representing movements in the underlying fundamental and one representing noise caused by the trading process. This structure allows the regularities to depend either on news or noise. The heteroskedasticity and persistence in the data are due to both ARCH‐like processes. The model has difficulty in simultaneously capturing the size and persistence of trading volume. Several extensions of the basic model, particularly including a constant level of non‐informational trading, improve the model's ability to capture the relevant characteristics of the data.     

Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility

The paper develops an empirical return volatility-trading volume model from a microstructure framework in which informational asymmetries and liquidity needs motivate trade in response to information arrivals. The resulting system modifies the so-called “Mixture of Distribution Hypothesis” (MDH). The dynamic features are governed by the information flow, modeled as a stochastic volatility process, and generalize standard ARCH specifications. Specification tests support the modified MDH representation and show that it vastly outperforms the standard MDH. The findings suggest that the model may be useful for analysis of the economic factors behind the observed volatility clustering in returns.