基于协整的豆类期货统计套利实证研究

文章选取大商所大豆、豆粕和豆油期货主力合约2006~2012年收盘价作为研究对象,对大豆压榨套利模拟实证,基于统计套利研究框架,对价格序列进行协整检验,以此为基础建立误差修正模型(ECM),验证三者价格之间存在长期均衡关系,根据协整系数确定套利交易投资组合,依据价差序列进行套利交易模拟,结果表明,豆类期货统计套利获利能力赢利能力并不明显,交易阈值的确定对于交易成本、交易次数和套利效果具有很强的关联性。     

中国费雪效应的门限协整检验

由于中国费雪效应的研究结果具有很大的不一致性,结合中国1991年1月至2008年12月之间的数据,应用可以刻画变量间非线性均衡关系的门限协整理论检验费雪效应,研究结果显示：第一,中国的名义利率与通货膨胀率均为单位根过程,二者之间不存在线性协整关系,而是存在两个门限值的门限协整关系;第二,当通货膨胀率小于-0．8％时,中国费雪效应不存在,而当通货膨胀率在-0．8％～12．03％2;间时,中国存在值为0．42的部分费雪效应;当通货膨胀率大于12．03％时,中国存在值为0．05的部分费雪效应。     

门限协整的非参数方法

本文首先研究门限协整的非参数检验和估计方法,利用局部多项式估计在边界处的良好性质及本身具有的局部性质给出了门限协整的检验和估计步骤;其次用Monte Carlo模拟方法对门限协整关系进行非参数估计,估计结果与真实的数据生成过程非常接近;最后对我国经济增长和农业发展状况的关系进行门限协整分析,表明它们不具有传统意义下的一般协整关系,但具有门限协整关系。     

基于非线性ECM模型的贝叶斯门限协整研究

 现有门限协整检验方法由于模型似然函数具有多峰、不连续特征,导致冗余参数识别存在困难,最优化计算相对复杂。本文提出基于非线性误差修正模型的贝叶斯门限协整分析,结合参数的后验条件分布设计MCMC抽样方案,进行贝叶斯门限协整检验;并利用Monte Carlo仿真研究了贝叶斯门限协整检验的有限样本性质,发现贝叶斯门限协整检验方法具有良好的有限样本性质。同时,利用不同期限的美国利率序列进行了实证研究,结果发现1个月与3个月利率之间、3个月与6个月利率之间以及3个月与1年利率之间均存在门限协整关系。研究结果表明：贝叶斯门限协整检验方法解决了冗余参数识别的难题,使计算变得相对简单,并提高了估计的精确度和检验的准确性。     

基于产业链产销环节的猪肉价格传导机制研究

文章利用向量误差修正模型,对2008年1月4日至2010年9月3日期间我国猪肉价格传导机制进行了研究。结果表明,生猪出场价与猪肉批发价之间存在长期协整关系,从长期来看两者之间存在正相关关系;我国生猪出场价与猪肉批发价的长期均衡关系制约着短期价格波动,并且这种制约作用能自动减弱价格之间的偏离,促使各种价格走向均衡。     

中国权证与标的证券的价格协整分析

基于研究时间序列的协整理论与ECM模型,对中国权证与其标的证券之间的价格协整关系进行了分析,以探索权证与其标的证券之间的长期均衡关系和对短期失衡的纠正机制.实证研究结果发现,权证价格与标的证券价格都是存在单位根的非平稳序列,都是一阶单整的;不同的认购权证价格与其标的证券价格的均衡关系存在一定的差异;不同的权证价格偏离其长期均衡水平时,其误差修正项将以不同的速率进行调节,使其价格逐渐回归到其长期均衡水平;权证市场和股票市场之间存在信息不对称效应.     

基于EGARCH-M模型的沪深300股指期货跨期套利研究——一种修正的协整关系

现有的基于协整股指期货跨期套利策略主要利用GARCH模型进行建模。该模型忽略了杠杆效应的存在,也未考虑条件方差可能影响协整方程。在引入EGARCH-M模型进行套利研究的基础上,提出一种新的协整关系——修正的协整;利用沪深300股指期货合约的每分钟收盘价进行实证分析,结果表明:正态EGARCH-M模型对数据的拟合效果优于传统的GARCH模型,通过设定合理的交易机制可以获得良好的套利结果;非正态的EGARCH-M模型在拟合效果和捕捉套利机会方面都比正态模型具有更好的表现,且套利效果也有显著提高。     

上海燃料油期货套期保值比率选取的实证研究

通过对上海燃料油期货和现货价格的实证分析,表明期货和现货价格之间存在协整关系,同时价格的波动具有时变性和集聚性特征。考虑这两种特征,建立四个模型计算套期保值比率。结果表明,按照考虑协整关系建立的VECM模型估计的最优套保比率进行套期保值,套期保值效果最好,能使决策者面临的价格风险最小。     

对货币供给量与通货膨胀率关系的再认识

文章针对我国连年货币供给量的快速上涨并没有产生严重的通货膨胀的现象,对1994年第1季度至2011年第1季度的季度数据分别从线性协整模型和门限协整模型的视角对货币供给量增长率和通货膨胀率之间的关系进行考察.经线性协整模型检验的结果表明仅有MO的增长率与通货膨胀率有关;而经门限协整模型的检验结果可知,M0、M1和M2的增长率与通货膨胀率之间均存在门限协整关系.     

股指期货对股票现货市场影响的实证研究

我国于2010年4月16日正式推出了沪深300股指期货合约,这使我国资本市场发生了质的转变.文章借鉴了大量资料和成果,对引入GARCH模型HS300股指期货影响现货市场波动性的程度进行实证分析,将协整检验和Granger因果检验分析的方法加以运用来研究两市场彼此长期均衡的关系,同时应用多种方法(方差分解、脉冲响应分析、向量自回归(VAR)模型、向量误差修正(VEC)模型),进一步对期货与现货间价格发现功能进行了分析.     

Cointegration and Long-Run Asset Allocation

We show that economic restrictions of cointegration between asset cash flows and aggregate consumption have important implications for return dynamics and optimal portfolio rules, particularly at long investment horizons. When cash flows and consumption share a common stochastic trend (i.e., are cointegrated), temporary deviations between their levels forecast long-horizon dividend growth rates and returns, and consequently, alter the term profile of risks and expected returns. We show that the optimal asset allocation based on the error-correction vector autoregression (EC-VAR) specification can be quite different relative to a traditional VAR that ignores the cointegrating relation. Unlike the EC-VAR, the commonly used VAR approach to model expected returns focuses on short-run forecasts and can considerably miss on long-horizon return dynamics, and hence, the optimal portfolio mix in the presence of cointegration. We develop and implement methods to account for parameter uncertainty in the EC-VAR setup and highlight the importance of the error-correction channel for optimal portfolio decisions at various investment horizons.     

SUBSAMPLING THE JOHANSEN TEST WITH STABLE INNOVATIONS

By taking into account the thick-tail property of the errors, cointegration analysis in vector error-correction models with infinite-variance stable errors is a natural generalization of cointegration analysis in error-correction models with normally distributed errors. We study the Johansen test for cointegrated systems under symmetric stable innovations with discrete spectral measures. The results show that the distributions of the Johansen test statistics under these innovations involve nuisance parameters. To overcome the problem of nuisance parameters, we implement a nonparametric subsampling procedure. We document some subsampling simulation results and demonstrate in an empirical example how the test can be used in practice.     

Cointegration in VAR(1) process: Characterization and testing

In this paper we taken a rather different approach to the concept of cointegration (comparated to existing literature) by focusing on the distance norm of an appropriately defined stochastic process (the first differences of one series) and a closed linear subspace defined from the first differences of the other series. The main result contained in Theorem 2 states that, within a VAR(l) framework, two series are cointegrated if and only if this distance is smaller than the standard deviation of the former process. It links cointegration to the evaluation of the distance between two information sets concerning the short-run dynamic paths of the variables. Hence cointegration can be detected by the differenced series. We, also propose a test for cointegration     

Aggregate consumption functions for India: A cointegration analysis under structural changes, 1919-86

This paper extends cointegration methodology to include the effect of possible structural changes on aggregate consumption behaviour in India during 1919-86. The only cointegrated relation is found to be a dynamic linear regression of lag order two, with 1944 as the year in which structural change began. The estimated short-run marginal propensity to consume (MPC) is greater than the long-run MPC. The estimates of the MPC are different from previous estimates for the Indian economy based on conventional econometrics. The initial year of structural change has been selected by extending the method of Perron and that of Zivot and Andrews.     

Unit root econometrics and economic nonlinearities

This paper concentrates on some shortcomings of contemporary unit root econometric methodology (testing for cointegration, common roots and stationarity) where the dynamics of an economy are described by a nonlinear process. It is shown that, in such circumstances, traditionally applied unit root econometrics may not lead to interpretable or statistically significant results. Two cases of such nonlinearities are discussed: (i) a stochastically nonlinear data generating process and (ii) a time-varying parameters cointegrating relation, typical of an economic reform process. It is shown that case (i) consists of a wide family of economic processes and in most such cases the results of standard unit root tests are not directly interpretable. Case (ii) does not result in a (conventionally understood) error-correction representation of a cointegrated process. Some Monte Carlo experiments evaluate the validity of cointegration tests in situations where there is a change in the cointegration parameter and from cointegration regime to noncointegration and vice versa. A simple method of estimation through simulation is proposed and its finite-sample properties examined.     

Interval forecasting in cointegrated systems

In this paper interval forecasting of cointegrated systems is examined. If the estimated coefficients are used to construct the forecasting intervals the error component due to the estimation of the coefficients is omitted in most cases. Analogous to the stationary case of vectorautoregressive models a correction term is derived basing on Johansen’s error correction representation of cointegrated systems. Its usefulness is analysed by means of a Monte Carlo study. The Monte Carlo study firstly demonstrates the difference between the nominal level of the confidence interval of forecasting and the observed level of the interval construction with known coefficients of variance calculation. Secondly, the forecast interval with estimated coefficients is investigated. Thirdly, it is illustrated that the approximation of forecast intervals can be improved by the proposed correction term for a small sample size, if the true cointegration rank is specified.     

On the usability of the fluctuation test statistic to identify multiple cointegration break points

The fluctuation test suggested by Hansen and Johansen [Some tests for parameter constancy in cointegrated VAR models, Econometrics J. 2 (1999), pp. 306–333] intends to distinguish between the presence of zero and one break in cointegration relations. In this article, we provide evidence by Monte Carlo simulations that it also serves as a graphical device to detect even multiple break locations. It suffices to consider a simplified and easy-to-implement version of the original fluctuation test. Its break detection performance depends on the sign of change in cointegration parameters and the break height. The sign issue can be approached successfully by a backward application of the test statistic. If breaks are observable, the break locations are detected at the true location on average. We apply the graphical procedure to assess the cointegration of bond yields of Spain, Italy and Portugal with German yields for the period 1995–2013 which is surprisingly supported by the trace test. However, the recursive cointegration approach shows that a stable relationship with German yields is only present for sub-periods between the introduction of the Euro and the global financial crisis which is in line with expectations. The statistical robustness of these results is supported by a forward and backward application of the cointegration breakdown test by Andrews and Kim [Tests for cointegration breakdown over a short time period, J. Bus. Econom. Stat. 24 (2006), pp. 379–394].