有效市场投资组合的识别与确定

Sharp、Lintner和Mossin发现的资本资产定价模型(CAPM)是一个一般均衡模型,不仅使人们提高了对市场行为的了解,而且还提供了实践上的便利,同时也为评估风险调整中的业绩提供了一种实用的方法。因此CAPM为投资组合分析的多方面的应用提供了一种原始的基础。然而,在1977年RichardRoll对CAPM的检验提出了尖锐的批评,批评的关键之一就是有效市场投资组合是否能得到识别。本文运用自己独创的一种几何方法解决了这个长达二十余年的国际性难题。本文首先把Markowitz模型的有效前沿用投资组合的权重向量表示出来,然后将资本市场线(CML)也用投资组合的权重向量表示出来,再由CML的定义就求出这个有效市场投资组合了。     

考虑消费与投资者情绪的股票市场资产定价

首先基于现有相关研究成果从理论上建立了考虑消费与投资者情绪的资产定价模型,然后选取2005年5月~2018年4月期间的中国A股上市公司数据以及消费和投资者情绪数据,分别对构建的考虑消费与投资者情绪的模型以及CAPM、Fama-French三因子和五因子模型进行实证检验和比较分析.研究结果表明:1)在资产定价模型中引入消费和投资者情绪因子能够在理论上对CAPM、Fama-French三因子和五因子模型进行合理拓展和修正.2)从总体定价效率看,用消费和投资者情绪因子分别替代Fama-French三因子模型中的规模和账面市值比因子、Fama-French五因子模型中的盈利和投资因子,都能够提高资产定价效率;在考虑消费和投资者情绪因子后,Fama-French五因子模型中的盈利和投资因子不再能提高资产定价效率.本文研究结果基于消费和投资者情绪改善了Fama-French模型定价效率,在一定程度上丰富和完善了资产定价理论.     

一种新的金融动态横截面估计方法——基于中国股票市场条件定价模型评估的应用与扩展

大多数资产定价模型常常用静态横截面回归(the static cross-sectional regression)进行定价表现评估,从而投资组合回报率的时间变化性并不能被时变的风险承载或者(和)时变的风险溢价所解释.本文从经济学的角度,运用一种新的金融动态横截面回归(the dynamic cross-sectional regression),首次考察了基于中国股票市场和美国股票市场的条件资产定价模型的定价表现:股票市场投资组合回报率的时变性是否能被时变的风险溢价所解释.本文发现,短期收益反转和流通市值加权市场换手率为条件变量的条件资本资产定价模型和基于消费的条件资本资产定价模型,能更好的解释中国股票投资组合的回报时变性,其时变性主要来自于时变的风险溢价.另外,本文发现一些拥有持续(persistence)和缓慢变化(slow-moving)特性的条件变量更能够解释横截面投资组合的时变回报.     

股票定价模式及股价分解测度方法研究——基于输入输出转换及相对比较的视角

通过超额收益统计检验研究市场有效性和利用均值-方差投资组合理论间接研究金融资产定价的经典方法与范式正面临尖锐的质疑和挑战.本文从输入输出转换和相对比较的视角对股票定价机制进行了分析,提出了一个涵盖四类定价因素,综合反映股票内在价值和相对价值的定价模式,给出了各组成部分的测度模型.最后,利用9家多重上市公司股票论证了本文提出方法的有效性.     

A Rational Theory of Mutual Funds' Attention Allocation

The question of whether and how mutual fund managers provide valuable services for their clients motivates one of the largest literatures in finance. One candidate explanation is that funds process information about future asset values and use that information to invest in high‐valued assets. But formal theories are scarce because information choice models with many assets are difficult to solve as well as difficult to test. This paper tackles both problems by developing a new attention allocation model that uses the state of the business cycle to predict information choices, which in turn, predict observable patterns of portfolio investments and returns. The predictions about fund portfolios' covariance with payoff shocks, cross‐fund portfolio and return dispersion, and their excess returns are all supported by the data. These findings offer new evidence that some investment managers have skill and that attention is allocated rationally.     

Analysing the information embedded in the optimal mean–variance weights: CAPM versus Bamberg and Dorfleitner model

This paper is centred on the analysis of the information embedded in the optimal weights of the assets in the CAPM and the Bamberg–Dorfleitner model. On this basis, first we find a functional relationship between the optimal weights of both models. Next, we find a set of performance indicators that express the contribution of each asset to the reward/volatility ratio measured as the Sharpe ratio or through a utility function. For the Bamberg–Dorfleitner model these indicators also lead to identify the contribution of each independent variable to the reward/volatility ratio. Technically, these connections are obtained through the covariance-normalized portfolio that consists of a transformation of the inverted covariance matrix. The additive property of covariances is transmitted to the indicators. These results enable investors and portfolio managers to obtain a precise knowledge of the causes of the value of the reward/volatility ratio. From the corporate point of view, this approach contributes to a better identification of the features of the different types of investors to whom to focus the corporate financial policy.     

基于资产链的异质投资者资本资产定价模型

本文基于资产链理论给出投资者的异质预期假设,通过对资产链各节点系统风险的分解,将传统的资本市场线转变为资本市场超平面,建立基于资产链的资本资产定价模型。本文使用小波滤波分解资产收益,对模型在上海A股市场的适用性进行检验,结果表明模型能够区分各类系统风险对资产收益的影响,对资产的平均收益具有显著的解释能力。     

金融网络风险下多因子矩阵回归的资产组合与定价

本文从企业的股权、债权关系出发,基于违约距离构建无向图网络,分析了不确定性风险以网络形式进行传染、溢出和蔓延等现象,通过最小生成树的稀疏网络优化方法最大限度降低资产组合的非线性风险影响。站在资源配置的角度,利用稀疏聚类算法深入挖掘资产特征和捕捉其间的相依关系,采用多目标、多指数的稳健矩阵回归策略动态跟踪市场趋势,并通过自适应权重学习策略对网络风险叠加影响下的资产组合进行选择和配置,最终获得最小生成树风险下投资组合的稀疏聚类优化策略,进一步扩充了资产定价多因子模型。研究发现多目标矩阵回归的稀疏聚类投资组合,不仅对组合内投资标的进行了选择性舍弃,使资金能够集中配置于优质资产,更有助于通过最小生成树减缓甚至切断风险在网络中的传播,有效降低了资产之间风险的传染性。基于金融网络的风险分析方法不仅有效地刻画了风险以网络方式互相传染、互相影响、互相强化的非线性叠加效应,而且通过资产之间配置系数的压缩变换和最小生成树的优化方式,最小化最坏情形下风险传染的影响,对复杂网络环境下的资产配置和全面风险管理进行了有益补充,为长期投资基金获得风险和收益更为均衡的资产配置,提供了合意的投资策略和决策依据。     

不完备金融资产市场中的资本资产定价原理

本文中,我们在不完备金融资产市场的框架下研究了资本资产的定价问题,得到了著名的资本资产定价模型(CAPM)的一个重要推广形式,建立了相应的混合投资基金定理,这些结果对于金融资产市场的理论研究具有重要的意义。     

模型不确定性条件下的Robust投资组合有效前沿与CAPM

本文提出了Robust投资组合有效前沿的概念,并研究了模型不确定性条件下的资本资产定价模型(CAPM)。研究发现,当市场上不存在无风险资产时,模型不确定性对风险资产投资比例的影响是非平等的,因此会导致投资组合的非分散化;而且此时的两基金分离定理以及零-βCAPM也不成立。但是当市场上存在无风险资产时,模型不确定性对风险资产投资比例的影响则是平等的,并且两基金分离定理仍然成立,因为任何Robust有效前沿组合都可以表示为市场组合与无风险资产的线性组合。而此时的CPAM仍然能够成立,只是在表达形式上增添了一个因子--不确定性因子;并且所有资产或资产组合的超额收益都可以分解为风险溢价与不确定性溢价两部分。     

Transform Analysis and Asset Pricing for Affine Jump‐diffusions

In the setting of ‘affine’ jump‐diffusion state processes, this paper provides an analytical treatment of a class of transforms, including various Laplace and Fourier transforms as special cases, that allow an analytical treatment of a range of valuation and econometric problems. Example applications include fixed‐income pricing models, with a role for intensity‐based models of default, as well as a wide range of option‐pricing applications. An illustrative example examines the implications of stochastic volatility and jumps for option valuation. This example highlights the impact on option ‘smirks’ of the joint distribution of jumps in volatility and jumps in the underlying asset price, through both jump amplitude as well as jump timing.     

金融数学模型

数学模型对于金融市场中的交易者有着非常重要的作用,数学模型应用于金融市场研究的重大突破是证券组合投资模型和金融衍生工具定价模型的出现,资本资产定价模型是由此发展起来的具有重大应用价值的金融数学模型。这些模型的发展和应用仍是当今金融领域的研究热点问题。本文将概括性地介绍一些模型和它们的应用。     

存在方差持续性的资本资产定价模型分析

自回归条件异方差(ARCH) 类模型突破了传统计量经济分析的同方差假定,对现代资本 资产定价理论产生了深远的影响. 随着对时变方差研究的深入,方差持续性也日益受到人们的 重视. 文章首先介绍了条件均值、条件方差以及在自回归条件异方差的基础上介绍了方差持续 性的有关概念和性质,并将之用于资本资产定价模型的研究,讨论了条件方差持续性对资本资 产定价模型的影响,并且进一步讨论了在多资产条件下向量GARCH 模型持续性对组合投资 的影响.     

Time‐Varying Risk Premium in Large Cross‐Sectional Equity Data Sets

We develop an econometric methodology to infer the path of risk premia from a large unbalanced panel of individual stock returns. We estimate the time‐varying risk premia implied by conditional linear asset pricing models where the conditioning includes both instruments common to all assets and asset‐specific instruments. The estimator uses simple weighted two‐pass cross‐sectional regressions, and we show its consistency and asymptotic normality under increasing cross‐sectional and time series dimensions. We address consistent estimation of the asymptotic variance by hard thresholding, and testing for asset pricing restrictions induced by the no‐arbitrage assumption. We derive the restrictions given by a continuum of assets in a multi‐period economy under an approximate factor structure robust to asset repackaging. The empirical analysis on returns for about ten thousand U.S. stocks from July 1964 to December 2009 shows that risk premia are large and volatile in crisis periods. They exhibit large positive and negative strays from time‐invariant estimates, follow the macroeconomic cycles, and do not match risk premia estimates on standard sets of portfolios. The asset pricing restrictions are rejected for a conditional four‐factor model capturing market, size, value, and momentum effects.     

非完全市场条件下的0-水平资产定价法研究

资产的0-水平定价法是指投资者在特定的效用函数和财富水平状况下已取得的最优投资组合,不会因新的资产出现及其相应的定价而调整,即对新资产的定价使追求效用最大化的投资者对新资产的最佳持有量为零。因此对新资产采用0-水平定价不会使市场产生套利机会。本文主要介绍Lenberger等人提出的0-水平定价的概念、方法及性质,并且将这种定价方法与e-套利定价方法进行比较,然后证明了在局部完全市场里,0-水平定价与e-套利定价的一致性。     

THE EFFECTS OF VARIABLE AND FIXED TRANSACTION COSTS ON OPTIMAL INVESTMENT DECISIONS

This paper studies the impact of variable and fixed transaction costs on investment decisions under conditions of risk. The decision model is first formulated as a mixed-integer nonlinear program. The following subjects are then examined: the structure of the investment frontier facing the investor and the effects of transaction costs on this frontier, the impact of transaction costs on the investor's optimal investment strategy, and the conditions for the equilibrium structure of risky asset prices and risk-return relationships. The main finding is that the relaxation of the assumption of the absence of transaction costs eliminates some of the most unattractive implications of the classic capital asset pricing model (CAPM) while preserving the more attractive implications of this model. Also, our model provides explanations for some discrepancies between the theoretical CAPM and empirical findings and, therefore, is a step toward narrowing the gap between theory and practice.     

COUNTRY PORTFOLIOS IN OPEN ECONOMY MACRO‐MODELS

This paper develops a simple approximation method for computing equilibrium portfolios in dynamic general equilibrium open economy macro‐models. The method is widely applicable, simple to implement, and gives analytical solutions for equilibrium portfolio positions in any combination or types of asset. It can be used in models with any number of assets, whether markets are complete or incomplete, and can be applied to stochastic dynamic general equilibrium models of any dimension, so long as the model is amenable to a solution using standard approximation methods. We first illustrate the approach using a simple two‐asset endowment economy model, and then show how the results extend to the case of any number of assets and general economic structure.     

基于流动性风险的资本资产定价模型

在现有的资产定价理论基础上,研究了考虑流动性风险因素的风险资产定价问题。首先在无套利下对流动性风险进行定价,得到流动性风险的市场价格,进而给出了无风险资产和风险资产的有效前沿。再从风险构成的角度给出了流动性风险的测度和市场价格,推导出两种形式的基于流动性风险的资本资产定价模型(以相对量表示风险的LBCAPM和以绝对量表示风险的LBCAPM)并揭示了资产期望回报的形成过程。最后,介绍了定价模型的应用前景。     

Estimation and Confidence Regions for Parameter Sets in Econometric Models1

This paper develops a framework for performing estimation and inference in econometric models with partial identification, focusing particularly on models characterized by moment inequalities and equalities. Applications of this framework include the analysis of game‐theoretic models, revealed preference restrictions, regressions with missing and corrupted data, auction models, structural quantile regressions, and asset pricing models. Specifically, we provide estimators and confidence regions for the set of minimizers Θ_I of an econometric criterion function Q(θ). In applications, the criterion function embodies testable restrictions on economic models. A parameter value θthat describes an economic model satisfies these restrictions if Q(θ) attains its minimum at this value. Interest therefore focuses on the set of minimizers, called the identified set. We use the inversion of the sample analog, Q_n(θ), of the population criterion, Q(θ), to construct estimators and confidence regions for the identified set, and develop consistency, rates of convergence, and inference results for these estimators and regions. To derive these results, we develop methods for analyzing the asymptotic properties of sample criterion functions under set identification.     

ADVERTISING AND VALUE MAXIMIZATION: AN INTEGRATIVE APPROACH *

The model developed in this paper is interdisciplinary in that we incorporate the advertising decision into the capital asset pricing model (CAPM) for valuation of risky income streams. The advertising decision involves the purchase of media services whose effects on sales (profit) are hypothesized to vary with general economic activity. As in any asset expansion, the firm purchases an income distribution with a given expected value and covariance with the economy. By consulting the CAPM, we are able to obtain a value for the income distribution associated with the advertising expenditure. By failing to account for both risk and return, those previous studies which have examined the effect of advertising on profit or valuation are, at best, incomplete. We are able to demonstrate the inappropriateness of ranking alternative advertising strategies solely on the basis of expected income.