新股流动性风险及其与IPO抑价的关系

本文利用上交所新股交易高频数据从四个不同维度实证分析了自动撮合市场中IPO股票后市流动性风险的变动特征,发现IPO投资者面临的流动性风险高于后市投资者.将流动性资产定价理论应用于IPO抑价研究,研究结果表明后市流动性风险与IPO抑价显著正相关,流动性越差,抑价越高.     

我国股市β系数的多尺度特性分析

自William Sharp(1964)提出著名的资本资产定价模型以来,β系数作为该模型最重要的参数之一,被公认为是衡量证券投资组合系统风险的主要指标.通过对β系数的估计,投资者可以预测证券未来的市场风险.     

基于FARM的我国股市流动性溢价的实证研究

流动性风险和流动性溢价是影响资产价格的重要因素。基于自由流通量调整的收益模型假设系统流动性风险为资产价格的风险因子,资产的流动性价差与其自由流通额的倒数成比例。中国股票市场全流通条件下的股本结构为利用FARM模型研究流动性风险与流动性溢价提供了十分有利的条件。文章通过选取2006年7月至2010年6月深圳股票市场与上海股票市场共1168只样本股进行实证分析。     

中国股票市场股权溢价的时变性研究

文章使用GARCH、EGARCH和跨期资本资产定价模型(ICAPM)来对1991年1月-2008年6月期间我国股票市场股权溢价的时变性问题进行研究.结果表明,我国股票市场的股权溢价具有明显的随着时间变化的特征,ARCH效应和杠杠效应显著. 模型和模型估计结果表明,我国股票市场的股权溢价并不具有明显的时变性,条件标准差比条件方差的拟合效果要更好一些.     

基于过度自信的资产均衡价格分析

文章构建了在过度自信投资者接受关于资产收益的私人信号后,与理性投资者交易单个风险资产时的资产均衡定价模型。以此模型为基础,在存在短期出售最大数量约束条件下,还分析了过度自信对股票均衡价格的影响,从而解释了过度自信导致的对理性均衡价格偏离的数量,以为股票市场投资提供理论指导。     

下方资本资产定价模型及其实证分析

近30多年来,CAPM在广泛应用的同时也备受学者和实践者的争议,主要是方差作为计量风险的指标越来越受到质疑。文章以半方差作为计量风险的指标,得到建立在均值—半方差理论上的一个均衡定价模型———下方资本资产定价模型(D-CAPM),并以上海股票市场为例实证研究D-CAPM的优越性。     

时变资本资产定价状态空间模型的构建及实证

为提高CAPM模型定价效率,文章在资产定价模型中引入投资者情绪影响因子,并利用状态空间模型建立了动态的基于投资者情绪的资本资产定价模型.实证分析表明投资者非理性情绪是证券定价的一个系统性因子,并且风险溢价因子及投资者非理性情绪因子具有显著的时变特征.     

资本资产定价模型（CAPM）对上海股市的实证研究

本文采用实证分析方法和经验验证手段,结合中国证券市场实践,对资本资产定价模型(CAPM)进行了有效性检验。我们采用回归分析方法,计算出了100支样本股的β系数,进而拟合出了上海股票市场的证券市场线(SML)。实证分析表明:上海股票市场中股票的β值对收益有一定的解释力,但对市场风险的度量缺乏显著性作用。方差分析结果表明:CAPM一定程度上可衡量上海股票市场风险与收益之间的关系,但有效性不强,非系统性风险对股票收益具有重大影响。     

资本资产定价模型在保险中的应用

资本资产定价模型(CAPM)先后由Sharpe,Litner和Mossin分别独立提出,Kahane,Hill,Cummins通过CAPM能够估计出承保的β系数,并进一步得出保险公司的公平收益率,从这个模型得到的收益率是指一定意义上的竞争收益率,即在保险公司面临的所有系统风险完全能够得到补偿时的收益率,由承保收益率和损失率之间的关系决定了保险人的预期损失也能够得到补偿.然而,通过CAPM导出的收益率和保费都是被高估的,因为该模型没有考虑保险公司的破产风险.用这个高估的收益率来监管保险业将会鼓励投资者增加对保险业的投资,从而导致保险业的供过于求,致使保险业效率低下.     

基于风险偏好系数的半方差房地产投资组合模型

文章基于半方差度量投资风险和投资者的风险偏好行为可变,构建了带有风险偏好系数的丰方差房地产投资组合模型.经实例验证,得出结论:该模型能求出更优的投资组合;投资决策取决于风险和收益之间的对比,即单位风险的回报才是资产选择的决定因素.     

The Distribution of Stock Returns When the Market Is Up

Abstract

For some investments, the relation between stock returns and the market proxy is conventionally described by a linear regression model with the normality assumption. This paper derives the distribution of stock returns for a security in an upgrade (or downgrade) market with the assumption that the log stock returns of the market proxy follow a mixture of normal distributions. We discuss MLE and the method of moment estimation for parameters involved in the model. An analysis of stock data in Johannesburg Stock Exchange is included to illustrate the model. This note explains the phenomenon in financial analysis regarding the shape of the distribution of long-run stock returns limited on an upgrade or downgrade market index.     

Testing Alphas in Conditional Time-Varying Factor Models With High-Dimensional Assets

ABSTRACT

For conditional time-varying factor models with high-dimensional assets, this article proposes a high-dimensional alpha (HDA) test to assess whether there exist abnormal returns on securities (or portfolios) over the theoretical expected returns. To employ this test effectively, a constant coefficient test is also introduced. It examines the validity of constant alphas and factor loadings. Simulation studies and an empirical example are presented to illustrate the finite sample performance and the usefulness of the proposed tests. Using the HDA test, the empirical example demonstrates that the FF three-factor model is better than CAPM in explaining the mean-variance efficiency of both the Chinese and U.S. stock markets. Furthermore, our results suggest that the U.S. stock market is more efficient in terms of mean-variance efficiency than the Chinese stock market. Supplementary materials for this article are available online.     

沪深A、B股市场信息传递路径实证分析

运用计量经济学中的ARCH-LM检验、GARCH模型、Granger引导关系检验等分析方法，实证分析了B股市场对境内投资者开放前后沪深两市A指收益率序列与B指收益率序列和非预期收益率序列的Granger引导关系，给出沪深A、B股市场信息传递路径，并且指出从信息流动角度来说，A、B股市场整合的方式是从A股市场向B股市场的内幕消息的传递和从B股市场向A股市场的投资理念的趋同。     

A dynamic analysis of stock markets using a hidden Markov model

This paper proposes a framework to detect financial crises, pinpoint the end of a crisis in stock markets and support investment decision-making processes. This proposal is based on a hidden Markov model (HMM) and allows for a specific focus on conditional mean returns. By analysing weekly changes in the US stock market indexes over a period of 20 years, this study obtains an accurate detection of stable and turmoil periods and a probabilistic measure of switching between different stock market conditions. The results contribute to the discussion of the capabilities of Markov-switching models of analysing stock market behaviour. In particular, we find evidence that HMM outperforms threshold GARCH model with Student-t innovations both in-sample and out-of-sample, giving financial operators some appealing investment strategies.     

金融市场收益率方向预测模型研究———基于文本大数据方法

金融市场的发展关系着一国的经济命脉,而股票市场作为金融市场的重要组成部分,对其收益率的研究也一直都是学术界的热点。财经新闻常被认为蕴含着丰富的信息,其中所包含的情感信息作为影响投资者投资决策的重要因素之一,对股票收益率也具有一定的影响。故本文构建了适用于金融投资领域的财经新闻情感词典来对财经新闻进行文本分析,同时构造了新的预测模型:将财经新闻文本中所含的情感量化为情绪指数并与时变密度函数相结合,得到时变加权密度模型。并在此基础上以模型评分为权重组合多个预测模型构建出评分加权模型用于股票收益率预测。结果显示,加入情绪指数能有效提高模型预测能力,而评分加权模型的预测能力则在此基础上更进一步,在准确率以及评分规则上基本达到双重最优。     

FIGARCH模型对股市收益长记忆性的实证分析

一、问题的提出长记忆性是指过去的冲击持续到将来,对预期的将来具有很大的影响。在大多数情况下,自相关函数的曲线图用来描述时间序列的长记忆特征。因此长记忆性可以定义如下：假设Ｙｔ是一个离散的时间序列,ｊ阶滞后的自相关函数为ρｊ,如果有ｌｉｍｎ→∞Σｎｊ＝...     

A semi-parametric method for estimating the beta coefficients of the hidden two-sided asset return jumps

ABSTRACT

We introduce a new methodology for estimating the parameters of a two-sided jump model, which aims at decomposing the daily stock return evolution into (unobservable) positive and negative jumps as well as Brownian noise. The parameters of interest are the jump beta coefficients which measure the influence of the market jumps on the stock returns, and are latent components. For this purpose, at first we use the Variance Gamma (VG) distribution which is frequently used in modeling financial time series and leads to the revelation of the hidden market jumps' distributions. Then, our method is based on the central moments of the stock returns for estimating the parameters of the model. It is proved that the proposed method provides always a solution in terms of the jump beta coefficients. We thus achieve a semi-parametric fit to the empirical data. The methodology itself serves as a criterion to test the fit of any sets of parameters to the empirical returns. The analysis is applied to NASDAQ and Google returns during the 2006–2008 period.     

跨期风险—收益权衡关系研究——来源于沪港通的新证据

风险—收益权衡关系是金融经济学重要内容之一。应用扩展的EGARCH-M模型考察了上海股票市场组合跨期风险收益权衡关系以及沪港通对这种关系的影响。研究发现,上海股票市场组合的跨期风险收益权衡关系显著为正,沪港通的开通正向加强了这种关系,提高了投资者的风险溢价需求。通过不同样本的对比和不同条件分布的假定证实了结果的稳健性。此外,还识别出了SGED分布可能更适合用于描述上海股票市场组合收益率的条件概率分布。     

基于风险预期的深市收益率预报研究

在预报股市收益率时考虑到股市风险波动及其结构性变化对股民心理预期的影响,采用状态空间理论将静态风险溢价GARCH-M模型改进为动态风险溢价模型。以中国深圳股市作为算例,研究了2006年1月至2008年8月深市风险的波动及股民风险预期的变化,并据此模拟了深市2008年8月的收益率,结果表明改进模型解释力更强,拟合精度更高,比一般的GARCH-M预报结果更准确。     

Variance (Non) Causality in Multivariate GARCH

This paper extends the current literature on the variance-causality topic providing the coefficient restrictions ensuring variance noncausality within multivariate GARCH models with in-mean effects. Furthermore, this paper presents a new multivariate model, the exponential causality GARCH. By the introduction of a multiplicative causality impact function, the variance causality effects becomes directly interpretable and can therefore be used to detect both the existence of causality and its direction; notably, the proposed model allows for increasing and decreasing variance effects. An empirical application evidences negative causality effects between returns and volume of an Italian stock market index future contract.