中国股市收益率与异质波动性关系研究

本文研究了中国股票市场的异质波动性问题。主要从异质波动性的识别与分布,异质波动性与股票收益率之间的关系,以及异质波动性是否被充分定价等三方面进行探讨。研究的目的在于分析股票异质波动性问题在中国股票市场中的特殊地位,这其中也包括异质波动性对股票收益影响问题。结合中国股票市场的数据,采用广义矩估计(GMM)的数量方法,显著地得到了中国股票市场中异质波动性水平,并以此分析了异质波动性与股票收益之间的关系,证明股票异质波动性水平是投资者进行决策时需要考虑的重要因素之一。     

股票回报率与汇率的关系——基于中国的实证

考察了上海股票市场A股的回报率与人民币汇率的关系．首先,经过单位根检验发现：股票回报率与人民币名义汇率是一阶单整。接着,利用Engle—Granger协整检验得到：在5％的显著性水平下,股票回报率与人民汇率没有长期均衡关系,但不能够拒绝短期单方向的Granger因果关系,即人民币名义汇率是股票回报率的Granger原因．     

中国股市大公司股票与小公司股票收益关系的实证研究

对中国股市的大公司股票与小公司股票的价格与收益关系进行了实证研究,结果表明大公司股票与小公司股票的收益无论在牛市阶段还是熊市阶段都存在较高的相关性;熊市阶段大公司股票收益的自相关程度最高,存在一定趋势性.大公司股票与小公司股票的价格序列是单位根的,但不是协整的,二者的收益序列是稳定的,在牛市阶段和熊市阶段大公司股票与小公司股票收益之间存在双向的领先—滞后后关系.     

基于修正的已实现阈值幂变差的股市跳跃波动行为研究

基于非参数统计方法,利用考虑金融资产价格跳跃和杠杆效应的时点波动估计方法修正已实现阈值幂变差,构造甄别跳跃的检验统计量,对金融资产价格中的随机波动、有限活跃跳跃和无限活跃跳跃等问题进行综合研究。为同时吸收波动率的异方差集聚效应和收益率的非对称效应,对原有的已实现波动率异质自回归预测模型进行拓展,将非对称的异质性自回归模型的误差项设定为GARCH模型,以考察跳跃波动序列与连续波动序列之间的复杂关系。利用沪深股指高频数据进行实证研究,包括进行跳跃识别,跳跃活动程度检验和波动率预测效果对比。研究结果表明,沪深股市同时存在布朗运动成分、有限活跃跳跃和无限活跃跳跃成分,其中连续路径方差占主体。同时,收益和波动间的杠杆效应显著,无论短期还是长期,连续波动和跳跃波动对波动率的预测均具有显著影响,同时考虑股价的跳跃、波动和杠杆效应因素有助于更准确地刻画资产价格动态过程。     

投资者情绪和市场利率对证券市场指数收益影响特点的动态刻画

本文基于2006年10月到2015年6月市场层面的投资者情绪和上证综指收益率,刻画了投资者情绪和市场利率对证券市场指数收益率的影响。首先,本文通过误差修正模型研究了短期层面投资者情绪对证券市场收益的影响特点,补充了以往在长期层面和整体收益水平上投资者情绪对市场收益影响的研究。由于市场层面的投资者情绪会受到宏观政策影响,之后本文将市场利率作为政策因素,通过分位数回归分析了不同市场收益水平下,市场利率和剔除了宏观政策因素的投资者情绪对市场收益的影响。研究结果表明:投资者情绪和证券市场收益之间的关系在短期层面上更为显著;当我国的证券市场环境处于“牛市”时,市场利率和投资者情绪均会对证券市场指数收益产生显著的影响,且随着市场收益水平的逐步上升,市场利率的反向作用和投资者情绪的正向作用均会逐渐加强。     

基于正则逆Gamma分布和广义极值分布的VaR计算

股指收益率的分布和风险价值(VaR)的计算是证券市场研究的热点问题.本文对来自上证指数和深证成指日收益率采用正则逆Gamma分布和偏T分布(SST)分别进行拟合,对极值序列(周、月极大值和极小值)建立广义极值分布函数。并由此计算VaR值,度量这几种序列的风险价值.结果表明正则逆Gamma分布能更好地拟合日收益率的分布,以及采用周极值收益率的广义极值分布计算VaR值来估计风险较为合理.     

金融市场波动性的拟合分析

金融市场的波动性是投资者关注的对象之一,也是被研究的热点。本文检验了我国股市的ARCH效应和序列相关性。并且在此基础上,将AR-IGARCH-M模型应用于上海综指和深圳成指,结果表明该模型能有效拟合我国深沪两股市的波动性。最后,针对结果分析了我国的股市行为。     

基于Tsallis理论的中国股市收益分布研究

应用Tsallis提出的非广延统计力学理论以及与之密切相关的非线性Fokker-Planck方程所描述的动力系统,根据我国上证指数和深证指数2004年1月1日～2008年11月13日的高频数据,分析了在三种不同的时间标度下股指收益的概率分布,发现Tsallis分布可以很好地描述两市收益分布的尖峰厚尾有限方差等特征,同时也给出了市场微观动力学层面的解释。揭示出我国上海和深圳股市的价格过程并不符合随机游走,而是反常扩散过程,两市具有十分接近的非线性动力系统特征。所得结论对于研究我国金融市场的资产配置和定价、风险管理和制度建设都具有重要的意义。     

THE EFFECTS OF ITQ IMPLEMENTATION: A DYNAMIC APPROACH

ABSTRACT. This paper investigates the intertemporal effects of introducing Individual Transferable Quota, ITQ, fishery management programs on stock size, fleet size and composition, and returns to quota holders and to vessel operators. Theoretical analysis is conducted using a specific version of a general dynamic model of a regulated fishery. It is demonstrated that the effects will differ depending upon the prevailing regulation program, current stock size, and existing fleet size, composition and mobility and upon how the stock and fleet change over time after the switch to ITQs. The paper expands upon previous works by modeling the dynamics of change in fleet and stock size and by allowing for changes in the TAC as stock size changes, by comparing ITQs to different regulations, and by allowing the status quo before ITQ implementation to be something other than a bioeconomic equilibrium. Specific cases are analyzed using a simulation model. The analysis shows that the annual return per unit harvest to quota owners can increase or decrease over the transition period due to counteracting effects of changes in stock and fleet size. With ITQs denominated as a percentage of the TAC, the current annual value of a quota share depends upon the annual return per unit of harvest and the annual amount of harvest rights. Because the per unit value can increase or decrease over time, it is also possible that the total value can do the same. Distribution effects are also studied and it is shown that while the gains from quota share received are the present value of a potentially infinite stream of returns, potential losses are the present value of a finite stream, the length of which depends upon the remaining life of the vessel and the expected time it will continue to operate.     

Nonparametric long term prediction of stock returns with generated bond yields

Recent empirical approaches in forecasting equity returns or premiums found that dynamic interactions among the stock and bond are relevant for long term pension products. Automatic procedures to upgrade or downgrade risk exposure could potentially improve long term performance for such products. The risk and return of bonds is more easy to predict than the risk and return of stocks. This and the well known stock-bond correlation motivates the inclusion of the current bond yield in a model for the prediction of excess stock returns. Here, we take the actuarial long term view using yearly data, and focus on nonlinear relationships between a set of covariates. We employ fully nonparametric models and apply for estimation a local-linear kernel smoother. Since the current bond yield is not known, it is predicted in a prior step. The structure imposed this way in the final estimation process helps to circumvent the curse of dimensionality and reduces bias in the estimation of excess stock returns. Our validated stock prediction results show that predicted bond returns improve stock prediction significantly.     

我国股市收益的双长记忆性检验——基于VaR估计的ARFIMA-HYGARcH-skt模型

针对股市收益分布的"尖峰肥尾"特征,引入了偏t分布作为新息分布。基于VaR方法,从风险估计的角度,利用ARFIMA(2,d_1,0)-HYGARCH(1,d_2,1)-skt模型对1996年12月17日至2007年7月5日期间的沪深股市收益进行了实证分析.实证结果显示:沪深股市具有显著的双长记忆特征;上海股市的日收益率和波动率的长记忆性均比深圳股市强;ARFIMA(2,d_1,0)- HYGARCH(1,d_2,1)-skt模型对我国股市收益具有较强的风险估计和预测能力。     

Weekday dependence of German stock market returns

The so‐called ‘Monday effect’ has been found for various stock markets of the world. The empirical finding that Monday returns are significantly smaller than returns measured for the remaining days of the week calls the efficiency hypothesis for pricing processes operating on stock markets into question. Investigating an index series measured at the Frankfurt stock exchange the paper compares estimation results of parametric and non‐parametric autoregressive models with respect to possible weekday dependence of return data. Allowing for heteroskedastic error distributions the wild bootstrap is used to infer against time‐varying means and correlation of return data in parametric models and to obtain confidence bands for non‐parametric estimates. It is shown that time dependence is an important feature describing the dynamics of German stock market returns in the period 1960–1979. Within two subsamples obtained from the period 1980–1997 the evidence in favour of such effects is mitigated substantially. Copyright © 2000 John Wiley & Sons, Ltd.     

Binomial option pricing with nonidentically distributed returns and its implications

The argument of Cox, Ross, and Rubinstein for pricing options is generalized in the direction of using nonidentically distributed binomial returns as a model for the stock price process. It is found that the use of nonidentically distributed binomial returns, in the limit exhaust the class of infinitely divisible distributions. The pricing of these models are considered and it is shown that the model is a generalization of the Black-Scholes model. The use, however, of nonidentically distributed returns, it is shown, can lead to contradictions. Hence, it is argued, the models used for stock price behavior requires restrictions.     

证券市场指数的尖峰厚尾特征与风险量估计

在对DOW,Nasdaq,S&P500和FTSE100等四个证券市场指数进行实证分析基础上,展示了证券市场指数的对数收益率具有尖峰厚尾的分布特征,并利用Logistic分布得到了很好的拟合,同时给出了基于Logistic分布的风险量VaR和CVaR的估计公式,以此计算证券市场指数的对数收益率的风险量VaR和CVaR的估计值.     

Dynamic linkages between stock prices,accrual earnings and cash flows: a cointegration analysis

This paper investigates the dynamic linkages between stock market prices, accrual earnings and cash flows using Finnish data. We find that stock returns lead accounting returns rather than vice versa. Thus, the thin Finnish stock market appears to produce important information about the future success of Finnish companies for decision making purposes. In addition, the cointegration analysis performed here indicates that the inclusion of the so-called error correction term based on non-stationary price variables significantly improves the observed association between stock market and accounting variables. Thus, in future research, the long-term adjustment between stock market and accounting variables should be analysed more carefully when investigating the causality between accounting earnings and stock markets.     

考虑投资人过度自信偏好的占线股票投资策略研究

当股票价格及收益的统计信息不足或无法构建精确概率分布时,股票占线投资问题获得广泛关注,即投资人能够运用在线算法和竞争分析设计出更好的占线投资策略以应对股价的不确定性。本文将投资人过度自信偏好这种认知偏差,引入到股票占线投资问题中,构建了离线对手与股票占线投资人的博弈模型,分别给出一般情形和存在动量效应情形下的最优混合策略和混合策略纳什均衡。结果发现,两种情形下的最优混合策略不仅克服了传统股票投资策略对股价或股票收益概率分布假设的过度依赖,并且更好地抽象了股票占线投资人过度自信、追涨杀跌等特征,对现有行为金融与金融占线交易问题的研究提供了有益补充。     

基于MCMC模拟的贝叶斯厚尾金融随机波动模型分析

针对现有金融时间序列模型建模方法难以刻画模型参数的渐变性问题,利用贝叶斯分析方法构建贝叶斯厚尾SV模型。首先对反映波动性特征的厚尾金融随机波动模型(SV-T)进行贝叶斯分析,构造了基于Gibbs抽样的MCMC数值计算过程进行仿真分析,并利用DIC准则对SV-N模型和SV-T模型进行优劣比较。研究结果表明:在模拟我国股市的波动性方面,SV-T模型比SV-N模型更优,更能反应我国股市的尖峰厚尾的特性,并且证明了我国股市具有很强的波动持续性。     

One‐way analysis of variance with long memory errors and its application to stock return data

Recent empirical results indicate that many financial time series, including stock volatilities, often have long‐range dependencies. Comparing volatilities in stock returns is a crucial part of the risk management of stock investing. This paper proposes two test statistics for testing the equality of mean volatilities of stock returns using the analysis of variance (ANOVA) model with long memory errors. They are modified versions of the ordinary F statistic used in the ANOVA models with independently and identically distributed errors. One has a form of the ordinary F statistic multiplied by a correction factor, which reflects slowly decaying autocorrelations, that is, long‐range dependence. The other is a test statistic such that the degrees of freedom of the denominator in the ordinary F test statistic is calibrated by the so‐called effective sample size. Empirical sizes and powers of the proposed test statistics are examined via Monte Carlo simulation. An application to German stock returns is presented. Copyright © 2007 John Wiley & Sons, Ltd.     

媒体信息量异常或有害股票收益

本文借助一个独特的数据样本,运用媒体对股票的剩余关注度模型,实证研究异常媒体信息量与股票收益之间的关系,以期为投资者进行投资决策提供一定的参考和指导。研究发现:异常媒体信息量越大,该股票在下一个月的平均收益率越低,存在媒体效应;由此所构造的零投资组合经CAPM模型、FF三因素模型和Car-hart四因素模型调整后,均能获取显著的超额收益,结果具有稳健性。此外,实证结果还表明媒体效应所带来的超额收益源于媒体信息量异常大的股票组合的显著低收益,本文认为,这种不对称现象产生的原因可能更多的是由投资者情绪导致的股票价格对媒体报道的过度反应,并进而导致较低的期望收益。     

动态非短视资产负债管理

用均值-回复过程刻画股票价格变化,本文研究了股票收益可预测金融市场中的连续时间资产负债管理问题。运用动态规划方法,求得了最优资产负债管理策略的闭合解。结果表明,最优策略是风险溢价的线性函数,随着投资期限的缩短,股票上的投资金额不断降低。数值分析表明,投资期限、股票风险溢价和债务对于最优资产配置策略和股票风险溢价不确定性跨期对冲需求都存在显著影响。