股市杠杆效应与溢出效应实证分析-GARCH模型之应用

通过使用广义自回归备件异方差GARCH模型对我国股市收益波动性的非对称性及波动性之间的互动性进行分析发现;在我国股票市场上，两效应在扩充样本区间内与国内文献构成一定的差异，与国外文献趋近一致。从此意义上说，我国股市正逐渐趋于理性，走向成熟。     

基于GARCH模型的认购权证与认沽权证波动率比较研究

波动性是经济和金融研究的热点问题。本文分别采用无条件波动度量方法和条件波动模型对我国权证市场上具有代表性的六支权证的波动性进行估计,得出以下几个结果:1、六支权证基本上都存在不同程度的波动聚类现象。2、认沽权证的市场有效性弱于认购权证。3、认购权证的波动持续性大于认沽权证,说明认沽权证投机性更强,风险更大。4、认购权证的风险收益补偿大概是认沽权证的6倍。最后,结合本文研究,将给广大投资者一些投资建议。     

On the asymmetric impact of macro–variables on volatility

We extend the GARCH–MIDAS model to take into account possible different impacts from positive and negative macroeconomic variations on financial market volatility: a Monte Carlo simulation which shows good properties of the estimator with realistic sample sizes. The empirical application is performed on the daily S&P500 volatility dynamics with the U.S. monthly industrial production and national activity index as additional (signed) determinants. We estimate the Relative Marginal Effect of macro variable movements on volatility at different lags. In the out-of-sample analysis, our proposed GARCH–MIDAS model not only statistically outperforms the competing specifications (GARCH, GJR-GARCH and GARCH–MIDAS models), but shows significant utility gains for a mean-variance investor under different risk aversion parameters. Attention to robustness is given by choosing different samples and estimating the model in an international context (six different stock markets).     

Exchange rate volatility and United Kingdom trade: evidence from Canada,Japan and New Zealand

This paper investigates the influence of exchange rate volatility on the real imports of the United Kingdom from Canada, Japan and New Zealand during the period 1980–2003. The Johansen multivariate cointegration method and the constrained error correction (general-to-specific) method are applied to study the relationship between real imports and its determinants (including exchange rate volatility). Conditional variance from the GARCH(1,1) model is applied as exchange rate volatility. Both nominal and real exchange rates are employed in the empirical study. Results indicate a significant effect of the exchange rate volatility on real imports. These exchange rate volatility effects are mostly positive. The author thanks an anonymous referee, the editor and Myles Wallace for several useful comments and suggestions. Any remaining errors and omissions are the author’s responsibility alone.     

期货价格收益率与波动性的实证研究——以中国上海与英国伦敦为例

采用协整模型、Granger因果关系检验、ECM模型及几种GARCH模型对中国上海与英国伦敦金属期货价格收益率和波动性做了研究.发现两市期货价格之间存在Granger因果关系、协整关系、同向变动关系和长期的共同趋势.采用ECM模型研究了两市的短期波动差异.GARCH类模型研究发现,两市波动性存在非对称性、溢出效应、杠杆效应.上海对伦敦市场的单向溢出效应显著存在.两市存在的利空消息均大于利多消息的作用,伦敦期货市场风险大于上海期货市场风险.     

M1 demand and volatility

The reasons for the instability within the M1 market during the 1970s and 1980s have been attributed to an actual breakdown in the M1 market, multicollinearity, or an inappropriate specification. The present paper offers a more general reason: increased volatility within the money demand determinants produced an econometric environment which made estimation of the relationship problematic. In order to investigate this possibility, the traditional demand vector is re-estimated with additional generalized autoregressive conditional heteroskedasticity representation for income, inflation, and interest rate volatility as conditioning variables. The rolling regression results highlight a significant stability within the M1 demand vector and its long- and short-run parameters. I wish to thank, without implicating, two anonymous referees for helpful comments and suggestions     

Linear and non-linear transmission of equity return volatility: evidence from the US, Japan and Australia

This paper models the transmission of shocks between the US, Japanese and Australian equity markets. Tests for the existence of linear and non-linear transmission of volatility across the markets are performed using parametric and non-parametric techniques. In particular the size and sign of return innovations are important factors in determining the degree of spillovers in volatility. It is found that a multivariate asymmetric GARCH formulation can explain almost all of the non-linear causality between markets. These results have important implications for the construction of models and forecasts of international equity returns.     

A conditional autoregressive range model with gamma distribution for financial volatility modelling

The commonly used conditional autoregressive range model with Weibull distribution (henceforth WCARR) suffers from serious inlier problem. We conjecture that this problem is due to a misspecified distribution to the disturbance, and propose a conditional autoregressive range model with gamma distribution (henceforth GCARR) to model the volatility of financial assets. In this paper, we first discuss the theoretical properties of the GCARR model and then compare its empirical performance with the WCARR. Empirical studies are performed on a broad set of stock indices in different countries over different time horizons. Consistent with the conjecture, we find that the GCARR model can reduce not only the inlier problem but also the outlier problem of the WCARR model. The results indicate that our GCARR model describes the dynamics of the range-based volatility better than the WCARR model and thus serves as a better benchmark.     

The impact of institutional volatility on financial volatility in transition economies

What have been the determinants of financial volatility in the transition countries of Central and Eastern Europe and the former Soviet Union? This paper posits that institutional changes, and in particular the volatility of crucial institutions such as property rights, have been the major causes of financial volatility in transition. Building a unique monthly database of 20 transition economies from 1991 to 2017, this paper applies the GARCH family of models to examine financial volatility as a function of institutional volatility. The results show that more advanced institutions help to dampen financial sector volatility, while institutional volatility feeds through directly to financial sector volatility in transition. Democratic changes in particular engender much higher levels of volatility, while property rights are sensitive to the metric used for their measurement.     

印花税调整对沪深300指数的影响

沪深300指数作为股指期货交易标的指数的市场认可度是股指期货能否成功的关键因素之一,而中国政府采用印花税的调整方式能够刺激股票市场产生短期效应并且不改变长期的趋势的特点尤其突出,利用GARCH模型分析其对于沪深300指数的影响力度,判断沪深300指数的可靠程度。     

汽车行业股价波动性的实证研究——基于GARCH类模型

近年来,我国汽车产业发展迅猛,汽车股价波动日趋复杂。鉴于GARCH模型能够较好地拟合时间序列的尖峰厚尾特征．本文采集了2008年1月1日至2009年11月30日共计1260个道琼斯第一财经中国600汽车和零件行业领先指数的数据,并将其分为熊市牛市两个阶段．运用GARCH类模型进行实证分析,证实了我国汽车行业股价具有尖峰厚尾、显著异于正态分布的特征,说明了两阶段股市中均存在杠杆效应,同时得出了收益随风险的增加而增加的现象在熊市中更加明显。     

人民币"汇改"、汇率风险与利率关系实证研究

本文以GARCH方法和2002-2009年的数据,对人民币利率与人民币汇率风险、通货膨胀、中美利差的关系进行分析。发现2005年7月汇改之后,人民币汇率风险开始对人民币利率的变化起正向作用,尽管人民币汇率风险对于人民币利率的变化仍不是具有决定性作用的因素。同时发现,无论是在汇改前还是在汇改后,中美利差对于人民币利率的变化都具有显著的影响。     

中国转轨期的成品油定价机制研究——基于目标区理论的一个动态架构

成品油定价走向市场化是个必然的趋势,但向市场化迈进的过程中,权衡市场和稳定是转轨期成品油定价机制改革必须关注的重要原则。本文针对我国目前成品油定价机制的不足,结合我国转轨期成品油定价机制改革需要关注的原则,利用国际上汇率目标区实践的经验,第一次从定量的角度为我国成品油定价设计了一个动态的目标区管理机制。相对现存的定价体制,目标区管理的优势体现在:既能够兼顾市场,又能够保持油价的适度稳定,为将来的完全市场化奠定基础;目标区的设计是根据数据逐月更新,充分的反映了国内外市场需求的变化,而且不会因为参照的油价固定、滞后,留给市场投机的空间;用定量的方法确定目标区的范围,相对来说更科学,也为政府干预市场和引导市场预期提供了一个准确的界限。     

中国能源消费波动的计量分析

利用ARCH类模型对我国能源消费增长率的波动规律进行了实证分析,结果表明：我国能源消费不具备自我稳定机制,其波动性存在非对称现象,正向冲击能够增加能源消费增长率的波动性,而负向冲击则能降低能源消费的波动性,且波动性对增长率存在着显著的正向“溢出效应”。     

汇率波动特征的研究方法综述

汇率的波动可以划分为长期波动,中期波动和短期波动,对于变量波动性的研究,金融计量经济学经典的渡动模型是Engk(1982)建立的自回归条件异方差(ARCH)模型,Bollerslev(1986)将ARCH扩展成GARCH模型,允许将条件异方差转化成一个ARMA模型,成为扩展的自回归条件异方差模型.对于波动特征的揭示都有很好的预测效果.     

不同态势下基于EVA的投资组合分析

使用经济增加值高的组合投资和经济增加值低的组合投资以及上证综指,对2001年6月14日到2007年10月16日共1 531个日数据不同态势下的收益、风险结构进行了分析,结果表明:牛市下应投资于经济增加值低的投资组合,而熊市下应投资于经济增加值高的投资组合。     

波动的杠杆效应与股市周期

对股市波动率的研究是研究股票市场的重要方面,而且在不同的股市周期中股票市场的波动特征也不尽相同。对波动率的研究能够明确股市特征,把握股市动态发展趋势。利用波动特征的经典模型对沪深300指数进行波动率分析,进而探讨好消息和坏消息的波动杠杆效应的差异,并且从多头期和空头期分别进行分析,比较杠杆效应在不同阶段的不同特征。