Intraday Serial Correlation,Volatility, and Jump: Evidence from China's Stock Market

In this article, we investigate the relationships among intraday serial correlation, jump-robust volatility, positive and negative jumps based on Shanghai composite index high frequency data. We implement variance ratio test to quantify intraday serial correlation. We also measure the continuous part of realized volatility using jump-robust MedRV estimator and disentangle positive and negative jumps using Realized Downside Risk Measure and Realized Upside Potential Measure proposed by Bi et al., (2013 Bi, T., Zhang, B., Wu, H. (2013). Measuring downside risk using high frequency data–realized downside risk measure. Communications in Statistics–Simulation and Computation 42(4):741–754.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). We find that intraday serial correlation are positively correlated with jump-robust volatility and negatively correlated with negative jumps which confirm the LeBaron effect.     

基于广义误差分布的股票收益率波动特征分析

假设股票收益率序列服从具有厚尾特征的GED分布,利用多种非对称性模型描述和检验了沪市股票日收益率序列的波动性特征,发现股票价格波动具有条件异方差性,并通过对股票市场信息影响曲线的分析,刻画了沪市股票价格波动中的显著非对称性。这说明股市波动对于不同的政策干预和信息冲击具有不同程度的反应,且非对称性的方向与以往结论有所不同,说明我国股市风险变异特征和收益状况在不断的发生变化,＂利好消息＂对股市的刺激作用需要其他市场干预的配合才能发挥出来。     

中国蔬菜价格波动与通货膨胀——基于波动来源的分解

利用Census X12季节调整和H-P滤波法,将蔬菜价格波动来源分解为趋势变动、季节变动、循环变动和不规则变动要素。利用Bootstrap因果检验与VAR模型,考察了蔬菜价格波动来源的分解因素与中国通货膨胀的关联性。结果表明,蔬菜价格波动影响消费者物价指数的主要渠道是通过季节变动和不规则变动要素;季节变动因素对消费者物价指数的影响呈季节周期性;不规则变动对消费者物价指数的冲击在最初时最显著,随后逐渐减弱。政策含义为,降低公众的通胀预期、促进蔬菜跨区域流通、控制蔬菜运输的物流成本、健全政府灾害天气应急响应机制均有利于减缓CPI上涨。     

最低收购价政策对小麦市场价格波动影响的实证分析

为了估计最低收购价政策对小麦市场价格波动的直接影响,利用2009年1月4日至2016年12月30日小麦现货与期货价格日数据,通过将政策作为虚拟变量引入GARCH模型,实证研究政策对平抑小麦期现货价格波动的作用,并从政策执行区和非执行区的视角比较政策在不同地区维护小麦市场价格稳定方面的效果,对模型结果和价格传导路径进行验证和分析。结果表明,政策对小麦期现货价格波动产生了明显的影响,能够显著降低小麦现货市场的波动程度,并通过期现货市场间的联系对期货市场产生影响,但政策对期货价格波动的作用方向则相反;政策在平抑小麦价格波动方面的效果具有空间上的溢出效应,通过区域间的市场联系从执行区传导到非执行区,导致非执行区价格波动程度的下降。     

上市公司信用风险的KMV模型分析

为研究KMV模型在中国上市公司信用风险定价与度量的适用性问题．选取2004年至2007年260家上市公司的财务指标与股票价格所组成的面板数据,对该模型所揭示的负债资产比、资产波动率和信用风险之间存在的两个内联关系进行实证分析,结果表明：负债资产比与信用风险存在正向关系,资产波动率与信用风险也存在正向关系,得出该模型在对中国上市公司的信用风险定价与度量中具有较高的适用性和精确性的结论。     

Role of stylized features in constructing better estimators

This article discusses the role played by stylized features of financial time series in constructing better estimators for the model parameters. We study in detail one such estimator for the transition probabilities of a simple regime switching model. The estimator is based on the squared autocovariances of the time series, which has been discussed in several empirical studies of economic and financial time series. The effectiveness of this estimator in improving the estimation accuracy is investigated, using both finite sample and asymptotic computations. We also report simulation results to confirm our findings and to extend our conclusions over a bigger region of the parameter space.     

Estimation of structural mean breaks for long-memory data sets

In long-memory data sets such as the realized volatilities of financial assets, a sequential test is developed for the detection of structural mean breaks. The long memory, if any, is adjusted by fitting an HAR (heterogeneous autoregressive) model to the data sets and taking the residuals. Our test consists of applying the sequential test of Bai and Perron [Estimating and testing linear models with multiple structural changes. Econometrica. 1998;66:47–78] to the residuals. The large-sample validity of the proposed test is investigated in terms of the consistency of the estimated number of breaks and the asymptotic null distribution of the proposed test. A finite-sample Monte-Carlo experiment reveals that the proposed test tends to produce an unbiased break time estimate, while the usual sequential test of Bai and Perron tends to produce biased break times in the case of long memory. The experiment also reveals that the proposed test has a more stable size than the Bai and Perron test. The proposed test is applied to two realized volatility data sets of the S&P index and the Korea won-US dollar exchange rate for the past 7 years and finds 2 or 3 breaks, while the Bai and Perron test finds 8 or more breaks.     

Bootstrap forecast intervals for asymmetric volatilities via EGARCH model

Bootstrap forecast intervals are developed for volatilities having asymmetric features, which are accounted for by fitting EGARCH models. A Monte-Carlo simulation compares the proposed forecast intervals with those based on GARCH fittings which ignore asymmetry. The comparison reveals substantial advantage of addressing asymmetry through EGARCH fitting over ignoring it as the conventional GARCH forecast. The EGARCH forecast intervals have empirical coverage probabilities closer to the nominal level and/or have shorter average lengths than the GARCH forecast intervals. The finding is also supported by real dataset analysis of Dow–Jones index and financial times stock exchange (FTSE) 100 index.     

国家能力、出口复杂度与经济增长波动 ——来自178个国家面板数据的经验证据

作为生产产品所需要的不可交易的投入品集合,国家能力的增加不但有利于经济产出的增长,而且能够增强经济体系中供给和需求的稳定性,进而有利于降低经济产出的波动性;出口复杂度的高低可以反映一国能力的多少,因而出口复杂度的提高可以降低供给波动、需求波动和产出波动.对1998—2017年178个样本国家的分析发现:出口复杂度的提高...