中国股票市场的收益-风险关系和惯性分析

本文采用非对称 EGARCH-M模型刻画了中国股票市场的个股风险 ,并对全市场的收益 -风险特征进行了横向分析 ,结果表明 ,从长期的角度来讲 ,在正常的市场条件下 ,中国股票市场存在着一定的高风险 -高收益、低风险 -低收益的关系 ,但从短期来看 ,由于不确定性因素较多 ,这种风险收益关系并不显著 .其次 ,本文分别采用每只股票历史 3个月的累积收益率、6个月的累积收益率以及 1 2个月的累积收益率分析了中国股票市场的惯性 ,我们发现 ,无论是从短期还是从比较长的时间来看 ,中国股票市场都不存在市场惯性 ,而表现出一定的反转现象 ,但反转现象会随着时间的推移逐渐减弱     

Nonparametric prediction of stock returns based on yearly data: The long-term view

One of the most studied questions in economics and finance is whether empirical models can be used to predict equity returns or premiums. In this paper, we take the actuarial long-term view and base our prediction on yearly data from 1872 through 2014. While many authors favor the historical mean or other parametric methods, this article focuses on nonlinear relationships between a set of covariates. A bootstrap test on the true functional form of the conditional expected returns confirms that yearly returns on the S&P500 are predictable. The inclusion of prior knowledge in our nonlinear model shows notable improvement in the prediction of excess stock returns compared to a fully nonparametric model. Statistically, a bias and dimension reduction method is proposed to import more structure in the estimation process as an adequate way to circumvent the curse of dimensionality.     

投资者注意的风险补偿对股市回报的预测

利用历史累积交易金额数据,本文构造了中国股票市场增量注意风险补偿和存量注意风险补偿,并检验其对中国股票市场收益率的预测能力。样本外检验结果显示,以上两种注意风险补偿均能显著预测下个月中国股市的超额收益率,其R²分别达到了2.68%和2.50%;与中国股票市场中其他预测变量相对比,增量注意和存量注意风险补偿表现出更强的预测能力。此外,基于不同的样本外检验期、不同的风险厌恶参数以及五种不同的变量构造方式,投资者注意风险补偿均产生显著的预测能力。围绕着经济周期波动,本文对注意风险补偿的预测能力进行了解释,同时还发现,相较于经济衰退期间,经济繁荣期间的投资者注意风险补偿样本外预测能力更强。     

The participation puzzle with reference-dependent expected utility preferences

Expected utility theory with a smooth utility function predicts that, when allocating wealth between a risky and a riskless asset, investors allocate a positive amount to the risky asset whenever its expected return exceeds the riskless rate of return. A large number of people invest none of their wealth in risky assets, though, leading to the ”participation puzzle.” This paper explores whether the participation puzzle can be addressed when the utility function has a kink at the reference wealth level. It shows that when the reference wealth level is initial wealth increased by the riskless rate of return, there exists a range of expected excess returns for the risky asset for which the investor takes no position. Moreover, this range of expected excess returns is described by comparing a common performance measure of stock returns, the Omega Function, to a function of preference parameters. However, if the reference wealth level is any other constant, the usual expected utility prediction holds and investors allocate at least some of their wealth to the risky asset whenever it has a positive expected excess return.     

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.     

上海股市收益率序列簇生特征局部线性平滑分析

本文从分析上海股票市场收益率序列的基本特征入手,重点利用非参数方法分析收益率序列波动性的簇生特征.首先通过一系列描述指标说明股市收益率序列具有的基本特点,利用非参数方法估计收益率序列的密度函数.进一步利用非参数回归分析的方法,分析股票市场的波动性,说明股市收益率序列的簇生特征是一个一般规律,在防范股市风险的时候应该注意到这一特点.     

基于ARMA-GARCH-SN模型的沪深300股指期货日内波动率研究与预测

运用五个交易日的股指期货高频数据(每秒两笔),本文主要研究了沪深300股指期货日内波动率特征并对日内波动率预测。研究发现高频股指期货日内收益率有明显的波动率聚集和条件异方差现象,但无尖峰厚尾现象,收益率序列分布符合有偏正态分布。因此,我们对时间序列建立了最优的ARMA-GARCH-SN模型,并对模型拟合充分性做了验证,拟合结果发现ARMA(1,2)-GARCH(1,1)-SN模型基本能够刻画股指期货高频日内波动特征,条件方差所受的冲击具有很强的持续性、日内波动也具有长记忆性,最后我们还利用自助法对高频股指期货日内波动率两步预测、利用滚动回归预测方法对样本做了样本内预测。预测结果表明,波动率预测结果能够较好地反映股指期货日内波动特征。     

Multiple Priors and Asset Pricing

The asset pricing implications of a statistical model consistent with multiple priors, or beliefs about return distributions, are developed. It is shown that quite generally equilibrium differences in mean returns across priors are to be explained in terms of perceived risk differences between these priors. Advances in filtering theory are employed on time series data to filter all the multiple state conditional components of risks and rewards. It is then observed that excess return differentials across priors are broadly consistent with required risk compensations under these priors, though the sharp hypothesis of zero intercept and unit slope is rejected. The filtered results also deliver numerous other interesting statistics. Here we focus on the construction of long horizon return distributions from data on daily returns using a Markov chain approach to incorporate stochasticity in elementary risk characterizations like volatility, skewness and kurtosis.      

关于长期债券是长期投者无风险资产的研究

假设短期利率服从C IR模型,通过研究投资者如何选择长期债券和短期债券进行资产配置,发现保守的长期投资者在长期债券上投资的比例更大;投资者的投资期限越长,投资的长期债券越多;在进行债券投资时不存在市场时机的选择。对于长期投资者而言,可以为其提供长期稳定收益率的长期债券才是无风险的。     

Pricing stock and bond derivatives with a multi-factor Gaussian model

The martingale approach to pricing contingent claims can be applied in a multiple state variable model. The idea is used to derive the prices of derivative securities (futures on stock and bond futures, options on stocks, bonds and futures) given a continuous time Gaussian multi-factor model of the returns of stocks and bonds. The bond market is similar to Langetieg's multi-factor model, which has closed-form solutions. This model is a generalization of Vasicek's model, where the term structure depends on state variables following correlated mean reverting processes. The stock market is affected by systematic and unsystematic risk.     

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。     

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.     

Variance vs downside risk: Is there really that much difference?

The popularity of downside risk among investors is growing and mean return–downside risk portfolio selection models seem to oppress the familiar mean–variance approach. The reason for the success of the former models is that they separate return fluctuations into downside risk and upside potential. This is especially relevant for asymmetrical return distributions, for which mean–variance models punish the upside potential in the same fashion as the downside risk.The paper focuses on the differences and similarities between using variance or a downside risk measure, both from a theoretical and an empirical point of view. We first discuss the theoretical properties of different downside risk measures and the corresponding mean–downside risk models. Against common beliefs, we show that from the large family of downside risk measures, only a few possess better theoretical properties within a return–risk framework than the variance. On the empirical side, we analyze the differences between some US asset allocation portfolios based on variances and downside risk measures. Among other things, we find that the downside risk approach tends to produce – on average – slightly higher bond allocations than the mean–variance approach. Furthermore, we take a closer look at estimation risk, viz. the effect of sampling error in expected returns and risk measures on portfolio composition. On the basis of simulation analyses, we find that there are marked differences in the degree of estimation accuracy, which calls for further research.     

Portfolio optimization in a regime-switching market with derivatives

We consider the optimal asset allocation problem in a continuous-time regime-switching market. The problem is to maximize the expected utility of the terminal wealth of a portfolio that contains an option, an underlying stock and a risk-free bond. The difficulty that arises in our setting is finding a way to represent the return of the option by the returns of the stock and the risk-free bond in an incomplete regime-switching market. To overcome this difficulty, we introduce a functional operator to generate a sequence of value functions, and then show that the optimal value function is the limit of this sequence. The explicit form of each function in the sequence can be obtained by solving an auxiliary portfolio optimization problem in a single-regime market. And then the original optimal value function can be approximated by taking the limit. Additionally, we can also show that the optimal value function is a solution to a dynamic programming equation, which leads to the explicit forms for the optimal value function and the optimal portfolio process. Furthermore, we demonstrate that, as long as the current state of the Markov chain is given, it is still optimal for an investor in a multiple-regime market to simply allocate his/her wealth in the same way as in a single-regime market.     

债券投资组合业绩归因的多期实证研究

目前国内对投资组合的业绩归因研究主要从管理者层面着手,将超额收益的来源归结为择时能力和选股能力,但这并不适用于债券投资。本文基于Campisi模型,对债券定价公式进行分解,从债券自身的特性来研究组合的超额收益来源,并结合GRAP跨期处理方法,形成多期业绩归因模型,对长期债券投资组合进行归因分析。相对于单期的归因模型,多期归因模型可以对任意一段时间内投资组合的超额收益进行归因,而不是单期归因项的简单加总。本文以中证全债指数为基准组合,对32只债券构成的投资组合进行实证研究,结果表明模型符合市场情况和实际操作情况。因此本文提出的多期业绩归因研究具有实用性。     

我国创业板企业内部人交易择时行为研究

利用深圳证券交易所2012年1月1日至2013年12月31日期间的创业板企业内部人的交易数据,从间接与直接两个角度考虑创业板企业的内部人交易与信息优势利用的关系.从间接角度来看,创业板企业的内部人卖出能够有效预测未来股票走势,来获取超额收益;而买入则不具有显著的择时能力,不能获取正的超额收益,这与主板企业具有相同特点;但其中创业板小额买入可取得长期收益,这与主板企业有所不同.从直接角度来看,创业板企业内部人在卖出中充分利用了估值判断优势,抓住高估值偏差的市场机会套现,这与主板企业的特点相同;而创业板企业的内部人买入交易决策与估值判断、业绩预测这两种信息优势利用的关系都不密切,这与主板企业的特点有所不同.     

基于股市高频数据的半参数估计方法

针对非参数方法研究国内股市长记忆性时结论参差不齐的现状,本文研究了更为稳健的半参数估计方法,即局部W h ittle(LW)估计和对数周期图(LP)回归。通过对不同频率高频数据的分析,证实了LW估计方法尽管需要数值最优化,但仍然要优于LP回归。进而将LW估计首次应用于中国股市,结果表明不同频率绝对收益序列的长记忆强度基本一致;同时发现,重大突发事件发生时的长记忆性表现得最为强烈,且事件后比事件前表现的要强烈,这说明股票市场的溢出效应在事件后增强,此项结论对我国证券市场有一定的借鉴意义。     

Estimating Value-at-Risk and Expected Shortfall using the intraday low and range data

Value-at-Risk (VaR) is a popular measure of market risk. To convey information regarding potential exceedances beyond the VaR, Expected Shortfall (ES) has become the risk measure for trading book bank regulation. However, the estimation of VaR and ES is challenging, as it requires the estimation of the tail behaviour of daily returns. In this paper, we take advantage of recent research that develops joint scoring functions for VaR and ES. Using these functions, we present a novel approach to estimating the two risk measures based on intraday data. We focus on the intraday range, which is the difference between the highest and lowest intraday log prices. In contrast to intraday observations, the intraday low and high are widely available for many financial assets. To alleviate the challenge of modelling extreme risk measures, we propose the use of the intraday low series. We draw on a theoretical result for Brownian motion to show that a quantile of the daily returns can be estimated as the product of a constant term and a less extreme quantile of the intraday low returns, which we define as the difference between the lowest log price of the day and the log closing price of the previous day. In view of this, we use estimates of the VaR and ES of the intraday low returns to estimate the VaR and ES of the daily returns. We provide empirical support for the new proposals using data for five stock indices and five individual stocks.     

我国股票市场的中长期回报率的过度反应

过度反应是证券市场异象之一。对沪市1993-2001年的股市交易数据,我们分为形成期1年和2年两种情况,分别检验出显著的过度反应,而且数据结果和图表显示形成期越长,随后的反转越明显,"输家组合"的平均超常收益率越高于"赢家组合"。对套利组合的风险因子回归分析仍然支持过度反应的存在。我们认为,我国证券市场还不完善的交易制度,加剧了投资者固有的认知偏差,从而导致价格超涨超跌的过度反应现象。     

基于Black-Litterman框架的资产配置策略研究

本文基于Black-Litterman框架提出了中国股票市场投资中行业间资产配置的策略。因为宏观经济指标对于股票收益率有一定的解释能力,本文通过宏观经济变量对收益率序列建模并且用GJR-GARCH模型捕捉资产收益率变化的特征,得出的预测资产收益率及其方差作为Black-Litterman框架下的输入。最后通过实证结果表明,基于这种策略构建的投资组合收益率在一定条件下会优于基于市场均衡权重或者传统Markowitz框架下的投资策略。