The Structural Break in the Equity Premium

This article uses Bayesian marginal likelihood analysis to compare univariate models of the stock return behavior and test for structural breaks in the equity premium. The analysis favors a model that relates the equity premium to Markov-switching changes in the level of market volatility and accommodates volatility feedback. For this model, there is evidence of a one-time structural break in the equity premium in the 1940s, with no evidence of additional breaks in the postwar period. The break in the 1940s corresponds to a permanent reduction in the general level of stock market volatility. Meanwhile, there appears to be no change in the underlying risk preferences relating the equity premium to market volatility. The estimated unconditional equity premium drops from an annualized 12% before to the break to 9% after the break.     

A Multivariate Threshold Varying Conditional Correlations Model

In this article, a multivariate threshold varying conditional correlation (TVCC) model is proposed. The model extends the idea of Engle (2002 Engle , R. F. ( 2002 ). Dynamic conditional correlation: a simple class of multivariate generalized autoregressive conditional heteroskedasticity models . Journal of Business and Economic Statistics 20 ( 3 ): 339 – 350 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) and Tse and Tsui (2002 Tse , Y. K. , Tsui , A. K. C. ( 2002 ). A multivariate GARCH model with time-varying correlations . Journal of Business and Economic Statistics , July 2002 , 20 ( 3 ): 351 – 362 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]) to a threshold framework. This model retains the interpretation of the univariate threshold GARCH model and allows for dynamic conditional correlations. Techniques of model identification, estimation, and model checking are developed. Some simulation results are reported on the finite sample distribution of the maximum likelihood estimate of the TVCC model. Real examples demonstrate the asymmetric behavior of the mean and the variance in financial time series and the ability of the TVCC model to capture these phenomena.     

Industry Implications of Value Creation and Appropriation Investment Decisions*

Managers face a critical task in making firm investment decisions that are targeted toward creating and appropriating value. As managers weigh their resource investment decisions, we argue that these investments have a direct impact on the growth and volatility of the firm's industry. With data covering 377 industries across 16 years, we investigate relationships for aggregate firm investments on the growth and volatility of industry profit and sales. Results reveal important, complex relationships between investment in value creation and appropriation and different elements of the industry environment. Implications for management theory and practice are discussed.     

基于函数型自适应聚类的股票收益波动模式比较

股票收益波动具有典型的连续函数特征,将其纳入连续动态函数范畴分析,能够挖掘现有离散分析方法不能揭示的深层次信息。本文基于连续动态函数视角研究上证50指数样本股票收益波动的类别模式和时段特征。首先由实际离散观测数据信息自行驱动,重构隐含在其中的本征收益波动函数。进一步,利用函数型主成分正交分解收益函数波动的主趋势,在无核心信息损失的主成分降维基础上,引入自适应权重聚类分析客观划分股票收益函数波动的模式类别。最后,利用函数型方差分析检验不同类别收益函数之间波动差异的显著性和稳健性,并基于波动函数周期性时段划分,图形展示和可视化剖析每一类别收益函数在不同时段波动的势能转化规律。研究发现：上证综指股票收益波动的主导趋势可以分解为四个子模式,50只股票存在五类显著的波动模式类别,并且5类波动模式的特征差异主要体现在本次研究区间的初始阶段。本文拓展了股票收益波动模式分类和差异因素分析的研究视角,能够为金融监管部门的管理策略制定和证券市场的投资组合配置提供实证支持。     

Self-weighted recursive estimation of GARCH models

The generalized autoregressive conditional heteroscedasticity (GARCH) processes are frequently used to investigate and model financial returns. They are routinely estimated by computationally complex off-line estimation methods, for example, by the conditional maximum likelihood procedure. However, in many empirical applications (especially in the context of high-frequency financial data), it seems necessary to apply numerically more effective techniques to calibrate and monitor such models. The aims of this contribution are: (i) to review the previously introduced recursive estimation algorithms and to derive self-weighted alternatives applying general recursive identification instruments, and (ii) to examine these methods by means of simulations and an empirical application.     

VIX指数对股票市场间联动性影响的实证研究

近期金融危机频繁发生,国际金融市场之间的动态联动性成为一个重要的研究课题。以往学者大都直接研究金融市场间的相关性,而忽略了外生金融变量对金融市场间相关性的影响。本文将对上述问题进行研究,借鉴Silvennoinen和Terasvirta(2015) STCC模型的思想,假定Copula参数受外生变量的影响,建立时变动态Copula模型——ST-VCopula模型,并基于该模型探究市场波动率（VIX指数）对股票市场之间相关性的影响,进而对几个国家的股票指数数据进行了实证分析。实证结果表明VIX指数对股票市场间联动性产生了显著的影响。VIX指数的获取简单便捷且更为直观,为市场间动态联动性的研究提供了另一种途径,可以为投资者在进行分散投资等金融活动时提供一定的指导和建议。     

基于混频已实现GARCH模型的波动预测与VaR度量

本文将Hansen等（2012）的Realized GARCH模型扩展为包含日内收益率、日收益率以及已实现波动率的混频已实现GARCH模型（M-Realized GARCH模型）。该模型将日内交易分为前后两段,引入了混频均值方程,并对混频均值方程的残差分别建立条件波动率方程和已实现日波动率方程。本文采用2013-2016年沪深300指数混频数据,分别在扰动项服从正态分布、t分布和广义误差分布的假设下,采用损失函数、SPA检验、kupiec检验和动态分位数检验法,对GARCH、Realized GARCH和M-Realized GARCH模型的波动率预测和VaR度量效果对比研究,得出M-Realized GARCH模型能提高预测精度,且VaR实际失败率与理论失败率一致,失败发生之间不相关。最后,本文利用Block bootstrap方法抽样得到混频数据,模拟证明了M-Realized GARCH模型比Realized GARCH模型具有更高的预测精度。     

Inflation in Transition Economies: An Empirical Analysis

The present research works with yearly data on backward looking measures of inflation i.e. GDP deflator series for Bulgaria, Czech Republic, Estonia, Hungary, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, and Slovakia. Because of the data limitations in the transition economies annual series are converted to smooth quarterly series before they are employed for inflation prognosis using state space models. The results show statistically significant evidence of time-varying volatility in Bulgaria, Czech Republic, Estonia, Hungary, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, and Slovakia using critical values obtained from χ₃² distributions. The results also show that the non-normality hypothesis cannot be rejected in all the series using critical values due McCulloch (J Bus Econ Stat 15:74–81, 1997). The efficiently estimated inflation forecast range between 0.925 for Bulgaria to 99.106 for Latvia. The estimated value of the characteristic exponent α of 2.000 for Hungary, and for the other countries having α equal to 1.999 shows tendency toward normal behavior in exception of Bulgaria, where α equals 1.861.      

持续期间、交易量、波动率与知情交易

内容提要：Admati和Pfleiderer [1]认为交易强度的增加,可能来自于知情交易也可能来自于流动性交易。本文通过分析中国股票市场上持续期间、交易量和波动率之间的关系,提供了识别知情交易和流动性交易的证据。与国外相关研究结论均不同的是,本文的实证结果认为：波动率与持续期间之间存在非线性关系,交易量较小时,交易强度的增加主要来自于流动性交易;而交易量较大时,交易强度的增加主要来自于知情交易。最后,本文对以上实证结果进行了稳健性检验,通过分析波动率日内特征对实证结果的影响,本文还发现,中国股票市场的知情交易通常发生在刚开盘的阶段。     

基于ARCH—M模型上证基金指数收益性与波动性的实证分析

以日收盘价指数的对数收益率为基础,采用ARCH—M类模型（GARCH—M,TGARCH—M和EGARCH—M）对上证基金指数的波动性与收益性进行了实证研究。结果表明基金波动性存在集聚性、波动率与收益率正相关．利空与利好消息对基金波动冲击存在不显著的杠杆效应。