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.     

考虑零售商质量控制和风险规避的供应链网络均衡研究

研究零售商质量控制和供应链成员风险规避背景下供应链网络均衡问题。应用条件风险值度量风险规避程度,利用变分不等式理论描绘供应链参与者的最优经济行为,设计供应链网络均衡模型,考虑风险规避和质量控制策略对均衡的影响,证明均衡解存在且唯一,并运用Levenberg-Marquardt算法求解均衡模型。最后对重要参数进行数值分析,揭示质量控制和风险规避对供应链均衡解以及参与者条件风险值的影响。研究表明：供应链参与者越规避风险越有利于产品质量水平的提高,风险规避程度的加深会降低制造商或零售商自身的CVaR,同时增大对方的CVaR,对因产品合格率提高带来的利益而言,制造商所得优于零售商。     

基于非参数与L-Moment估计的股市动态极值ES风险测度研究

通过运用带宽非参数方法、AR-GARCH模型对时间序列的条件均值、条件波动性进行建模估计出标准残差序列,再运用L-Moment与MLE(maximum Likelihood estimation)估计标准残差的尾部的GPD参数,进而运用实验方法测度出风险VaR(value at Risk)及ES(ExpectedShortfall),最后运用Back-Testing方法检验测度准确性。结果表明,基于带宽的非参数估计模型比GARCH簇模型在测度ES上具有更高的可靠性;基于非参数模型与L-Moment的风险测度模型能够有效测度沪深股市的动态VaR与ES。     

Conditional Uncertainty Analysis and Implications for Decision Making: The Case of WIPP

Uncertainty analyses and the reporting of their results can be misinterpreted when these analyses are conditional on a set of assumptions generally intended to bring some conservatism in the decisions. In this paper, two cases of conditional uncertainty analysis are examined. The first case includes studies that result, for instance, in a family of risk curves representing percentiles of the probability distribution of the future frequency of exceeding specified consequence levels conditional on a set of hypotheses. The second case involves analyses that result in an interval of outcomes estimated on the basis of conservative assumptions. Both types of results are difficult to use because they are sometimes misinterpreted as if they represented the output of a full uncertainty analysis. In the first case, the percentiles shown on each risk curve may be taken at face value when in reality (in marginal terms) they are lower if the chosen hypotheses are conservative. In the second case, the fact that some segments of the resulting interval are highly unlikely—or that some more benign segments outside the range of results are quite possible—does not appear. Also, these results are difficult to compare to those of analyses of other risks, possibly competing for the same risk management resources, and the decision criteria have to be adapted to the conservatism of the hypotheses. In this paper, the focus is on the first type (conditional risk curves) more than on the second and the discussion is illustrated by the case of the performance assessment of the Waste Isolation Pilot Plant in New Mexico. For policy-making purposes, however, the problems of interpretation, comparison, and use of the results are similar.     

基于高阶矩波动和Copula函数的相依性模型及其应用

本文提出了基于高阶矩波动的相依结构模型:Copula-NAGARCHSK-M模型。考虑资产的时变条件方差风险、条件偏度风险和条件峰度风险对边缘分布的影响,应用模型研究了上证综指和深证成指对数收益率之间、条件方差之间、条件偏度之间和条件峰度之间的相依结构。发现两股票市场的指数对数收益率之间、条件方差之间和条件峰度之间有相似的相依结构,而条件偏度之间的相依结构则是负方向的相似。     

混合椭球分布下证券组合的尾部条件方差

由于风险价值、条件风险价值等下方风险度量没有考虑尾部数据的变异性,因此在刻画极端金融风险方面存在一定的缺陷。为了更好地控制尾部极端损失的发生概率,我们选择用尾部条件方差来刻画这种极端风险,即超过风险价值的那部分损失的方差。考虑到混合椭球分布在金融数据建模中的重要性,本文在这类分布下研究了证券组合的尾部条件方差,得到了证券组合尾部条件方差风险的精确表达式,为了验证本文的结果,我们也进行了一些数值计算及在最优投资组合方面的应用研究。     

Risk of Extreme Events in Multiobjective Decision Trees Part 2. Rare Events

Earlier work with decision trees identified nonseparability as an obstacle to minimizing the conditional expected value, a measure of the risk of extreme events, by the well-known method of averaging out and folding back. This second of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming that a random variable is observed only in the upper 100 (1 −α) percent of potential outcomes, where α is a cumulative probability preselected by the decision maker. An approach is proposed to overcome the need to evaluate all policies in order to identify the optimal policy. The approach is based in part on approximating the conditional expected value by using statistics of extremes. An existing convenient approximation of the conditional expected value is shown to be separable into two constituent elements of risk and can thus be optimized, along with other objectives including the unconditional expected value of the outcome, in a multiobjective decision tree. An example of sequential decision making for remediation or environmental contamination is provided. The importance of the results for risk analyis beyond the minimization of conditional expected values is pointed out.     

Strategic supply network planning with vendor selection under consideration of risk and demand uncertainty

We present a stochastic version of a three-layer supply network planning problem that includes the selection of vendors that must be equipped with company-specific tools. The configuration of a supply network must be determined by using demand forecasts for a long planning horizon to meet a given service level. The risk induced by the uncertain demand is explicitly considered by incorporating the conditional value at risk. The objective is to maximize the weighted sum of the expected net present value of discounted cash flows and the conditional value at risk. This would lead to a non-linear model formulation that is approximated by a mixed-integer linear model. This approximation is realized by a piecewise linearization of the expected backlogs and physical inventory as non-linear functions of cumulative production quantities. A two-stage stochastic programming approach is proposed. Our numerical analysis of generic test instances indicates that solving the linearized model formulation yields a robust and stable supply network configuration when demand is uncertain.     

Multiobjective Decision-Tree Analysis1

Single-objective-based decision-tree analysis has been extensively and successfully used in numerous decision-making problems since its formal introduction by Howard Raiffa more than two decades ago. This paper extends the traditional methodology to incorporate multiple noncommensurate objective functions and use of the conditional expected value of the risk of extreme and catastrophic events. The proposed methodology considers the cases where (a) a finite number of actions are available at each decision node and (b) discrete or continuous states of nature can be presented at each chance node. The proposed extension of decision-tree analysis is introduced through an example problem that leads the reader step-by-step into the methodological procedure. The example problem builds on flood warning systems. Two noncommensurate objectives—the loss of lives and the loss of property (including monetary costs of the flood warning system)–are incorporated into the decision tree. In addition, two risk measures—the common expected value and the conditional expected value of extreme and catastrophic events—are quantified and are also incorporated into the decision-making process. Theoretical difficulties associated with the stage-wise calculation of conditional expected values are identified and certain simplifying assumptions are made for computational tractibility. In particular, it is revealed that decisions concerning experimentation have a very interesting impact on the noninferior solution set of options—a phenomenon that has no equivalence in the single-objective case.     

Risk and Uncertainty Analysis in Government Safety Decisions

Probabilistic risk analysis (PRA) can be an effective tool to assess risks and uncertainties and to set priorities among safety policy options. Based on systems analysis and Bayesian probability, PRA has been applied to a wide range of cases, three of which are briefly presented here: the maintenance of the tiles of the space shuttle, the management of patient risk in anesthesia, and the choice of seismic provisions of building codes for the San Francisco Bay Area. In the quantification of a risk, a number of problems arise in the public sector where multiple stakeholders are involved. In this article, I describe different approaches to the treatments of uncertainties in risk analysis, their implications for risk ranking, and the role of risk analysis results in the context of a safety decision process. I also discuss the implications of adopting conservative hypotheses before proceeding to what is, in essence, a conditional uncertainty analysis, and I explore some implications of different levels of "conservatism" for the ranking of risk mitigation measures.     

非对称结构下金融市场动态风险测度研究

针对金融市场呈现出的非对称结构,以新兴市场的中国大陆沪市上证综指(SSEC)和成熟市场的标准普尔指数(S&P500)作为代表性的研究对象,运用有偏学生分布(SKST)来刻画金融收益的有偏非对称分布形态;运用APARCH等模型来刻画金融收益条件波动率的非对称波动性,并以此来开展风险测度研究;最后运用返回测试中LRT和DQR来检验风险测度的准确性。实证结果表明:没有哪种金融收益的条件非对称波动模型具有绝对优越的风险测度能力;在标准收益服从的分布上,新兴市场SSEC与成熟市场S&P500市场却又表现出明显的不同,Normal分布并不适合SSEC,但能适合S&P500;ST能够适应SSEC,却不能适应S&P500,而SKST能够适应两种市场;对于S&P500,在99%这样高的置信水平下是Normal优越,而在95%的置信水平下却是SKST优秀,对于SSEC,SKST分布的准确性在两个水平下都是最高。     

基于EVT-POT-SV-MT模型的极值风险度量

针对金融资产收益的异常变化,采用SV-MT模型对风险资产的预期收益做风险补偿并捕捉收益序列的厚尾性、波动的异方差性等特征,将收益序列转化为标准残差序列,通过SV-MT模型与极值理论相结合拟合标准残差的尾部分布,建立了一种新的金融风险度量模型——基于EVT-POT-SV-MT的动态VaR模型.通过该模型对上证综指做实证分析,结果表明该模型能够合理有效地度量上证综指收益的风险.     

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.     

基于Skew-t-FIAPARCH的金融市场动态风险VaR测度研究

本文引入FIAPARCH模型刻画金融价格条件波动率特征,引入有偏学生t分布捕获收益率有偏特征,并以此来测度金融市场动态风险VaR;进而运用返回测试和动态分位数回归方法对风险测度模型准确性进行实证检验.结果表明,RiskMetrics和GARCH-N测度金融市场的风险的可靠性差;有偏学生t分布比正态分布、学生t分布更能准确反应金融收益分布实际特征,具有更高的风险测度能力;FIAPARCH-SKST展示出比其它模型具有绝对优越的风险测度效果.     

多银行贷款池的组合违约风险研究

资产组合的违约风险是决定其定价的重要因素.根据多银行贷款池这样一类特殊的资产组合的契约特征,可将其组合违约风险的影响因素分解为:1)宏观的系统风险因素;2)各贷款银行的风险因素;3)各债项的异质风险因素.在此基础上,构建了反映这类贷款池的违约风险和相关性结构的多因素模型,并在条件独立性假设和多元正态分布假设下,得到了该贷款池的违约行为随机特征.数值分析表明,多元正态分布的因素模型能够比较清楚地刻画所研究的多银行贷款池的组合违约风险.     

A Distributional Approach to Characterizing Low-Dose Cancer Risk

Since cancer risk at very low doses cannot be directly measured in humans or animals, mathematical extrapolation models and scientific judgment are required. This article demonstrates a probabilistic approach to carcinogen risk assessment that employs probability trees, subjective probabilities, and standard bootstrapping procedures. The probabilistic approach is applied to the carcinogenic risk of formaldehyde in environmental and occupational settings. Sensitivity analyses illustrate conditional estimates of risk for each path in the probability tree. Fundamental mechanistic uncertainties are characterized. A strength of the analysis is the explicit treatment of alternative beliefs about pharmacokinetics and pharmacodynamics. The resulting probability distributions on cancer risk are compared with the point estimates reported by federal agencies. Limitations of the approach are discussed as well as future research directions.     

Adjexpectile风险测度的性质、优化及资产配置的应用

金融风险的度量和识别是风险管理的重要内容,常用的风险度量工具是标准差、VaR、ES,但存在很多缺陷,expectile的提出弥补了这些不足,在理论界得到广泛的讨论和应用。本文扩展了expectile进行资产配置,提出Adjexpectile的概念,并讨论和分析了Adjexpectile的一致性风险度量、随机占优性、凸性,与标准差、VaR、shortfall的关系,风险贡献及风险分解的性质。通过对六个资产指数：上证国债指数、上证企业债指数、上证180指数、深圳100指数、深成长40p指数和黄金现货指数的复合周收益率数据进行组合优化配置,发现Adjexpectile在非对称性收益数据、组合前沿、风险分散方面具有一定的优越性。     

胖尾分布及长记忆下的动态EVT-VaR测度研究

针对金融收益胖尾分布特征及条件波动率长记忆性特征,运用FIGARCH对条件波动率建模、极值理论(extreme value theory,EVT)对标准收益序列的尾部建模,测度出金融市场动态极值风险,进而运用返回测试(back-testing)技术,对模型在样本内的测度准确性与样本外的推广能力进行稳健性检验.实证研究结...     

Risk of Extreme Events in Multiobjective Decision Trees Part 1. Severe Events

Earlier work with decision trees identified nonseparability as an obstacle to minimizing the conditional expected value, a measure of the risk of extreme events, by the well-known method of averaging out and folding back. This first of two companion papers addresses the conditional expected value that is defined as the expected outcome assuming the exceedance of a threshold β, where β is preselected by the decision maker. An approach is proposed to overcome the need to evaluate all policies in order to identify the optimal policy. The approach is based on the insight that the conditional expected value is separable into two constituent elements of risk and can thus be optimized along with other objectives, including the unconditional expected value of the outcome, by using a multiobjective decision tree. An example of sequential decision making for improving highway capacity is given.     

Income Variance Dynamics and Heterogeneity

Recent theoretical work has shown the importance of measuring microeconomic uncertainty for models of both general and partial equilibrium under imperfect insurance. In this paper the assumption of i.i.d. income innovations used in previous empirical studies is removed and the focus of the analysis is placed on models for the conditional variance of income shocks, which is related to the measure of risk emphasized by the theory. We first discriminate amongst various models of earnings determination that separate income shocks into idiosyncratic transitory and permanent components. We allow for education‐ and time‐specific differences in the stochastic process for earnings and for measurement error. The conditional variance of the income shocks is modelled as a parsimonious ARCH process with both observable and unobserved heterogeneity. The empirical analysis is conducted on data drawn from the 1967–1992 Panel Study of Income Dynamics. We find strong evidence of sizeable ARCH effects as well as evidence of unobserved heterogeneity in the variances.