SV—N与SV—M模型测量股市波动性的应用

与传统的GARCH类模型一样,SV模犁(随机波动模型)是用来捕捉股市波动特征的一个较好的模型,该模型在国外得到广泛的应用.实证研究表明:利用SV模型的两个子类,即基于正态分布下的SV模型(SV-N)和均值SV模型(SV-M)来测量我国沪深股市波动性明显优于GARCH类模型,能够更好地描述其统计特征.     

开放式基金给基金业带来的机遇与挑战

一、我国基金业目前存在的问题 一、基金没有发挥稳定市场的作用。一般来说，成熟证券市场上股票的波动率在20％左右，而据我们的测算，2000年上半年，我国证券市场大盘的波动率为42．72％，国债的波动率为1．93％，A股的波动率为74．67％，B股的波动率为74．33％，而且基金重仓持有的风华高科、     

Shibor利率跳跃扩散模型的参数估计与蒙特卡罗模拟检验

Shibor是央行培养的中国货币市场基准利率体系,能够准确的模拟基准利率Shibor的动态变化特征,对利率衍生品定价与利率风险管理都具有重要意义。我们对CKLS模型、CKLS-Jump跳跃扩散模型、带随机波动率的CKLS-Jump-SV模型和带跳跃随机波动率的CKLS-SV-Jump模型进行自适应MCMC参数估计,结果表明CKLS-SV-Jump模型能够最有效的刻画出Shibor的利率动态变化特征;我们对北京银行7天Shibor挂钩债券进行蒙特卡罗数值计算,研究表明CKLS-Jump-SV模型能够很好的提供利率衍生品定价的利率路径模拟。     

基于MCMC模型的国内外黄金价差波动性分析

对于我国黄金市场价格的研究方法多种多样,本文运用马尔科夫链蒙特卡罗方法(MCMC)、Gibbs抽样算法、标准随机波动模型(SV-N)对国内外黄金价差进行研究。通过对历史数据进行计算,本文得出结论,我国黄金与国际黄金价格的价差有进一步扩大趋势,且波动幅度也将相应增大,我国有必要采取措施减小国内外黄金价差及其波动幅度。     

中国证券市场社保基金的行为和监管——基于行为金融学的视角

本文基于行为金融学的视角,结合投资者的行为特征、行为金融决策理论基础以及行为模型等,通过分析机构投资者之一社保基金的投资行为特征、规模和影响,提出了完善相关法律法规建设、加强社保基金监管、建立完善的基金市场机制等一系列建议措施。     

中国证券市场社保基金的行为和监管——基于行为金融学的视角

本文基于行为金融学的视角,结合投资者的行为特征、行为金融决策理论基础以及行为模型等,通过分析机构投资者之一社保基金的投资行为特征、规模和影响,提出了完善相关法律法规建设、加强社保基金监管、建立完善的基金市场机制等一系列建议措施。     

社保基金持股与企业盈余质量:A股上市公司的证据

本文利用中国A股上市公司2006-2015年的数据,研究社保基金持股对上市公司盈余质量的影响。我们用上市公司财务重述作为测度盈余质量的指标,发现社保基金持股能够显著降低企业发布财务重述的概率,这表明社保基金对上市公司盈余质量的提高具有促进作用。并且,社保基金的这一治理作用在国有企业、内部治理水平较差以及市场化程度较低地区的上市公司中更加显著。通过双重差分模型和安慰剂检验等方法弱化了内生性问题之后,以上结论依然成立,说明社保基金持股和盈余质量提升之间存在因果关系,我们称之为社保基金的公司治理作用。进一步研究发现,社保基金可以通过抑制控股股东资金占用、增加机构调研次数等途径提升被持股公司的盈余质量。本文有助于认识和评估社保基金持股对于上市公司的监督与治理作用。     

价格跳跃对我国股指期货市场的影响研究

流动性、波动率及交易活跃度是金融市场微观结构研究中的三个热点问题,在实际的金融市场上也得到了极大关注。利用沪深300股指期货的高频数据,检测出股指期货价格发生跳跃的交易日,并运用Granger因果检验方法研究了跳跃发生日和无跳跃发生日中,市场流动性、波动率及交易活跃度这三个指标之间的相互因果关系。实证结果表明,无论价格是否发生跳跃,我国股指期货市场上的流动性与波动率及流动性与成交量指标之间均存在双向的Granger因果关系。而衡量期货市场交易活跃度的另一重要指标——持仓量,在无跳跃发生时可引导流动性和波动率指标,但在有跳跃发生时这些因果关系消失。     

我国证券投资基金与股市和债市的波动相关性——基于BEKK模型和失败检验法的研究

本文基于多元GARCH模型中的三元对角BEKK模型,分析了我国沪深两市基金与股票、国债市场的波动相关性,并通过失败检验法得出波动相关的具体数值.研究结果表明:沪深两市基金市场与股票市场和国债市场都具有显著的时变方差特征和波动持久性;沪市基金市场与股票市场存在30％左右的正向波动相关度,而深市基金市场与股票市场的正向波动相关性很小;两市基金市场都与国债市场有较大的负向波动相关性,表现出对波动明显的非对称效应.     

"国有股划拨社保基金"及"社保基金海外投资"政策的经济效应——基于文字表述的一般均衡模型分析

“国有控股上市公司划拨部分国有股充实全国社保基金”和“全国社保基金海外投资”引人瞩目,全国社保基金运营(包括筹集、保值增值)的经济效应(经济增长效应和再分配效应)研究愈显重要。本文运用文字表述的一般均衡模型分析说明:全国社保基金长期持有部分国有股、社保基金海外投资分别通过“降低代际企业所有权的转移成本”和“资本市场专门人才培育、社保基金保值增值”两条传导途径促进经济均衡增长(增长效应),增加劳动者和退休人的福利(再分配效应)。建议加快“划拨国有股充实社保”步伐,减少全国社保基金国内投资、加大海外投资比重,加强对海外投资的有效监管。     

中国社会保障战略储备基金管理中存在的问题及对策分析

全国社会保障基金是中国社会保障战略储备基金,其安全性以及保值增值状况对中国社会保障的发展具有重要战略意义。我国社保基金不断发展壮大,同时,实行直接投资和间接投资相结合的管理模式,保证了较好的安全性和较高的收益率。但是,仍然存在着资金来源不稳定、保值增值能力不足以及信息披露机制不完善等问题,因此,应完善基金来源规划、壮大基金规模,增强基金保值增值、抗风险能力,并完善信息披露机制。     

Gradient-based simulated maximum likelihood estimation for stochastic volatility models using characteristic functions

Parameter estimation and statistical inference are challenging problems for stochastic volatility (SV) models, especially those driven by pure jump Lévy processes. Maximum likelihood estimation (MLE) is usually preferred when a parametric statistical model is correctly specified, but traditional MLE implementation for SV models is computationally infeasible due to high dimensionality of the integral involved. To overcome this difficulty, we propose a gradient-based simulated MLE method under the hidden Markov structure for SV models, which covers those driven by pure jump Lévy processes. Gradient estimation using characteristic functions and sequential Monte Carlo in the simulation of the hidden states are implemented. Numerical experiments illustrate the efficiency of the proposed method.     

The impact of the Social Security Fund on auditor litigation risk

In this study, we examine the effect of the Social Security Fund on auditor litigation risk. Using audit fees as a proxy for auditor perceptions of litigation risk, we find that the Social Security Fund significantly reduces auditor litigation risk. Furthermore, we show that the Social Security Fund influences auditor litigation risk through reducing both the audit risk and the business risk of public companies. In addition, the impact of the Social Security Fund for reducing auditor litigation risk is more obvious in the group of firms with low levels of internal governance, which indicates that the Social Security Fund plays an important governance role as a high-quality institutional investor. In summary, we verify that the Social Security Fund, when acting as an institutional investor, plays an important role in corporate governance, and that it helps to reduce auditor litigation risk. Our results provide empirical support for expanding the governance role of the Social Security Fund as an institutional investor in China’s A-share market.     

Implications of Social Security Reform on Interest Rates: Theory and Evidence

This article investigates the potential effect that Social Security reform may have on bond and equity returns. We specifically focus on the effect of proposals to shift a portion of the investment of the U.S. Social Security Trust Fund to the equities market. Models are developed to demonstrate the relationship between returns and both the relative size of the Social Security Trust Fund and the portfolio allocation of the Trust Fund. Using these two models, we then show that interest rates will increase from either a decrease in the size of the Social Security Trust Fund or a shifting in the investment mix from bonds to equities. We derive an adjustment factor that relates the magnitude of change in interest rates from either source and use this adjustment factor in conjunction with estimates of the relationship between government debt and interest rates to forecast the potential effect on interest rates from shifting part of the Trust Fund to the equity market. The estimates herein suggest that investing some of the Social Security funds in equities is not a painless cure‐all for the Social Security system and may even have some adverse effects in terms of income transfers from American taxpayers to foreign bondholders.     

The affine styled-facts price dynamics for the natural gas: evidence from daily returns and option prices

This study analyzes affine styled-facts price dynamics of Henry Hub natural gas price by incorporating the price features of jump risk, and seasonality within stochastic volatility framework. Affine styled-facts dynamics has the advantage of being able to incorporate mean reversion (MR), stochastic volatility (SV), seasonality trends (S), and jump diffusion (J) in a standardized inclusive framework. Our main finding is that models that incorporate jumps significantly improve overall out-of-sample option pricing performance. The combined MRSVJS model provides the best fit of both daily gas price returns and the related cross section of option prices. Incorporating seasonal effects tend to provide more stable pricing ability, especially for the long-term option contracts.     

货币政策对中国股市连续性波动和跳跃性波动的影响研究

股票价格包括连续和跳跃两个部分,本文基于股市高频数据将中国股市的已实现波动分解为连续性波动和跳跃性波动,通过建立多元线性回归模型和Tobit模型,研究了存款准备金政策和利率政策对不同类型股市波动的影响。研究表明,存款准备金率调整的信息发布对连续性波动没有显著影响,但对跳跃性波动存在显著的影响;存款准备金率的实际调整对连续性波动、跳跃性波动均存在显著影响,但跳跃性波动更多地受到了信息发布时的影响;利率政策的调整对连续性波动和跳跃性波动存在显著影响,中国股市对利率政策变化提前作出反应。     

Index Option Pricing Models with Stochastic Volatility and Stochastic Interest Rates

This paper specifies a multivariate stochasticvolatility (SV) model for the S & P500 index and spot interest rateprocesses. We first estimate the multivariate SV model via theefficient method of moments (EMM) technique based on observations ofunderlying state variables, and then investigate the respective effects of stochastic interest rates, stochastic volatility, and asymmetric S & P500 index returns on option prices. We compute option prices using both reprojected underlying historical volatilities and the implied risk premiumof stochastic volatility to gauge each model's performance through direct comparison with observed market option prices on the index. Our major empirical findings are summarized as follows. First, while allowing for stochastic volatility can reduce the pricing errors and allowing for asymmetric volatility or leverage effect does help to explain the skewness of the volatility smile, allowing for stochastic interest rates has minimal impact on option prices in our case. Second, similar to Melino and Turnbull (1990), our empirical findings strongly suggest the existence of a non-zero risk premium for stochastic volatility of asset returns. Based on the implied volatility risk premium, the SV models can largely reduce the option pricing errors, suggesting the importance of incorporating the information from the options market in pricing options. Finally, both the model diagnostics and option pricing errors in our study suggest that the Gaussian SV model is not sufficientin modeling short-term kurtosis of asset returns, an SV model withfatter-tailed noise or jump component may have better explanatory power.     

Box-Cox stochastic volatility models with heavy-tails and correlated errors

This paper presents a Markov chain Monte Carlo (MCMC) algorithm to estimate parameters and latent stochastic processes in the asymmetric stochastic volatility (SV) model, in which the Box-Cox transformation of the squared volatility follows an autoregressive Gaussian distribution and the marginal density of asset returns has heavy-tails. We employed the Bayes factor and the Bayesian information criterion (BIC) to examine whether the Box-Cox transformation of squared volatility is favored against the log-transformation. When applying the heavy-tailed asymmetric Box-Cox transformed SV model, three competing SV models and the t-GARCH(1,1) model to continuously compounded daily returns of the Australian stock index, we find that the Box-Cox transformation of squared volatility is strongly favored by Bayes factors and BIC against the log-transformation. While both criteria strongly favor the t-GARCH(1,1) model against the heavy-tailed asymmetric Box-Cox transformed SV model and the other three competing SV models, we find that SV models fit the data better than the t-GARCH(1,1) model based on a measure of closeness between the distribution of the fitted residuals and the distribution of the model disturbance. When our model and its competing models are applied to daily returns of another five stock indices, we find that in terms of SV models, the Box-Cox transformation of squared volatility is strongly favored against the log-transformation for the five data sets.     

A smooth non-parametric estimation framework for safety-first portfolio optimization

In this paper, we adopt a smooth non-parametric estimation to explore the safety-first portfolio optimization problem. We obtain a non-parametric estimation calculation formula for loss (truncated) probability using the kernel estimator of the portfolio returns’ cumulative distribution function, and embed it into two types of safety-first portfolio selection models. We numerically and empirically test our non-parametric method to demonstrate its accuracy and efficiency. Cross-validation results show that our non-parametric kernel estimation method outperforms the empirical distribution method. As an empirical application, we simulate optimal portfolios and display return-risk characteristics using China National Social Security Fund strategic stocks and Shanghai Stock Exchange 50 Index components.     

Pricing and static hedging of European-style double barrier options under the jump to default extended CEV model

This paper develops two novel methodologies for pricing and hedging European-style barrier option contracts under the jump to default extended constant elasticity of variance (JDCEV) model, namely: a stopping time approach based on the first passage time densities of the underlying asset price process through the barrier levels; and a static hedging portfolio approach in which the barrier option is replicated by a portfolio of plain-vanilla and binary options. In doing so, both valuation methodologies are extended to a more general set-up accommodating endogenous bankruptcy, time-dependent barriers and the commonly observed stylized facts of a positive link between default and equity volatility and of a negative link between volatility and stock price. The two proposed numerical methods are shown to be accurate, easy to implement and efficient under both the JDCEV model and the nested constant elasticity of variance model.