运用生存分析与变点理论对上证指数的研究

本文运用生存分析与变点理论对上证指数进行了研究,发现连涨和连跌的股指服从伽玛分布,表明股市是有记忆的并且不服从随机游动假说。当股市发生变化时,伽玛分布的参数也会发生变化,而且伽玛分布的两个参数很好地反映了牛市、熊市的变化以及股市波动的变化。我们运用变点理论对这一变化进行了实证分析,得出了一些有意义的结论。     

最大化生存概率的投资策略

本文研究最大化生存概率准则下的最优投资问题。假设投资者面临着不可对冲的随机风险,市场是不完备的,任何投资策略都不能完全消除财富总量的下行风险。本文主要结果是:假设无风险资产利率大于零,分别研究了无借贷约束和有借贷约束条件下基于最大化生存概率准则的最优投资问题,运用随机控制理论,通过求解HJB方程,获得了最优投资策略及相应最大生存概率的闭式解,给出了数值算例,通过比较静态分析揭示了生存概率和投资策略与各参数之间的数量关系。结果表明,风险资产最优投资比例随财富总量的增加而减少,企业的生存概率随财富总量的增加而增加,随法定水平的增加而减少。     

基于MARKOV链的军事目标伪装生存概率模拟分析

军事目标的伪装是作战保障的重要内容,也是一种重要的作战行动.本文运用系统论的思想和随机过程理论,设计了军事目标在隐真与示假伪装时的生存概率计算公式,构建了其在受到敌方攻击时,生存概率的MARK-0V链模型,并运用MATLAB语言设计了仿真程序,进行了仿真实验.结果表明,彩综合伪装技术可显著提高军事目标的生存能力.本研究为科学合理地估算军事目标伪装的生存与毁伤概率提供了有效的方法.     

基于转换点生存概率的或有可转债定价研究

首先利用二叉树模型及风险中性定价原理,给出了离散时间下或有可转债(Contingent Convertible Bonds,简称Co Cos)的估值方法;然后通过刻画Co Cos在各转换点的生存概率,扩展构建了一个连续时间下的Co Cos定价模型;最后以瑞信集团发行的或有可转债"BCN"为例,进行定价计算及敏感性分析。结果表明银行资产及资产波动率对Co Cos价值有显著的正向影响。另外,为弥补现有研究不足,本文以权益比率为触发器,避免了银行权益与Co Cos价值间的多重均衡问题,并通过建立权益比率与核心一级资本充足率的线性模型,使定价模型可推广适用于以资本充足率为触发器的债券。     

审计抽样推断的局限性分析

本文通过对审计抽样推断的局限性在当前审计工作中的表现进行阐述,从三方面对其形成原因进行了分析,进而有针对性的对克服审计抽样推断局限性的措施提出自己的看法。     

基于贝叶斯推断的证券投资基金绩效分析

从投资者先验信念的角度,运用贝叶斯推断对我国封闭式基金绩效进行实证研究。通过直观的问题引出投资者对基金管理者技巧的先验信念集合,并与具有4个风险指标的线性模型相结合,有效联系了投资决策过程中的重要因素——个人直观理念与实际市场数据,给出投资者在不同先验信念下的后验绩效。研究表明,随着投资者对管理者先验信念的增加,基金后验绩效增加,投资者更倾向于投资;只有当投资者对管理者有极强的先验信念时,才会投资于表现一般的基金;同理,不投资于绩优基金也需极强的先验信念。同时发现,基金费用对基金后验绩效的影响主要反映在基准线的平移。进一步,通过分时间段的投资组合权重分析,给出投资者在不同市场环境下的最优投资组合策略选择方法。     

基于生存分析模型的中美两国股市比较研究

本文首次运用生存分析方法对道琼斯工业价格指数进行研究,研究发现道琼斯工业指数的连涨连跌收益率服从Gamma分布,并且在牛市和熊市中,Gamma函数的两个参数是不同的。最后对上证指数和道琼斯工业指数的连涨连跌收益率进行对比分析,发现道琼斯工业指数比上证指数运行更加平稳。     

基于样本外分布回测的随机过程统计推断方法

采用不同的随机过程模型描述标的资产的价格动态,会极大的影响衍生品定价和风险管理活动。在文献中,同一资产采用的随机过程往往是不一致甚至是矛盾的。本文以GBM过程与OU过程为例,提出了一种统计推断方法,旨在从多个备选模型中选出能更好的描述标的资产价格动态的随机过程。该方法应用事后检验原理,将数据分成估计窗和检验窗,估计窗用来估计随机过程的参数,然后在模型参数不变的假定下,推导了原假设成立时检验窗各个时点的资产价格的样本外分布,看实际数据落在接受域或拒绝域的频数来判断是否接受原假设。本文以大宗商品、汇率、利率、股票作为标的资产,对随机过程选择进行了实证分析。实证结果表明,一些经常使用的随机过程模型并不一定是最优的模型。     

顾客购买行为影响因素分析及重购概率的预测

顾客购买行为是市场营销研究的重要内容之一。目前已有一些文献通过引入几个属性变量,构建起描述顾客购买行为或预测购买概率的随机模型。本文在前人研究的基础上,首先分析了对顾客购买行为影响较大的顾客购买决策、前后两次购买间隔时间、顾客重购行为和顾客逃逸等因素,而后将这些因素综合考虑,给出预测日用消费品重购概率的一种方法,并用实际数据对预测方法进行检验,预测的结果与实际数据非常接近。本方法的特点一是预测精度较高,二是具有一般性,适用于一般的日用消费品。     

最小化破产概率的最优投资

本文研究基于最小化破产概率准则的最优投资问题.不同于Merton问题中消费是内生决策变量,本文假设投资者单位时间内必须消费不少于一个固定数量的财富,因而投资者有可能最终破产.在三类不同存贷约束条件下,通过求解模型相对应的Hamilton-Jacobi-Bellmen (HJB)方程,都获得了最优投资策略及最优值函数(破...     

时间贝叶斯网络及其概率推理

针对贝叶斯网络应用中出现的循环和动态问题,研究贝叶斯网络的时间扩展.给出了时间贝叶斯网络的定义;探讨了时间贝叶斯网络中环的存在合理性判断问题;给出了时间贝叶斯网络的概率推理算法,应用示例说明了方法的可行性.     

Operational Slack and Venture Survival

Slack can act as a double‐edged sword. While it can buffer against environmental threats to help ensure business continuity, slack can also be costly and reduce profitability. In this study we focus on operational slack, the form related to the firm's production processes. We investigate the role of operational slack on firm survival during its venture stage when its survival is significantly challenged by environmental threats. Specifically, we explore how change in three types of environmental uncertainty, namely dynamism, complexity, and lack of munificence, affect the relationship between operational slack and venture survival. Results suggest that with an increase in environmental uncertainty, operational slack lowers the likelihood of venture failure.     

我国股票市场指数及指数证券投资组合

运用主成分分析法分析我国上海和深圳两个交易所几个市场指数对市场变化的反应情 况, 结果表明两个股票市场的综合指数和A 股指数可以反应市场的变化, 而其他指数不能反 映各自代表的股票市场变化. 由于这4 个指数都不是一个好的投资组合, 要得到与指数一致的 投资收益需要构造指数投资组合. 本文利用多因子定价模型, 结合统计分析和优化方法, 从每 个股票市场上选取20 余支股票, 经过适当的组合就可以得到与指数一致的收益.     

A New Methodology for Before–After Safety Assessment Using Survival Analysis and Longitudinal Data

The widely used empirical Bayes (EB) and full Bayes (FB) methods for before–after safety assessment are sometimes limited because of the extensive data needs from additional reference sites. To address this issue, this study proposes a novel before–after safety evaluation methodology based on survival analysis and longitudinal data as an alternative to the EB/FB method. A Bayesian survival analysis (SARE) model with a random effect term to address the unobserved heterogeneity across sites is developed. The proposed survival analysis method is validated through a simulation study before its application. Subsequently, the SARE model is developed in a case study to evaluate the safety effectiveness of a recent red‐light‐running photo enforcement program in New Jersey. As demonstrated in the simulation and the case study, the survival analysis can provide valid estimates using only data from treated sites, and thus its results will not be affected by the selection of defective or insufficient reference sites. In addition, the proposed approach can take into account the censored data generated due to the transition from the before period to the after period, which has not been previously explored in the literature. Using individual crashes as units of analysis, survival analysis can incorporate longitudinal covariates such as the traffic volume and weather variation, and thus can explicitly account for the potential temporal heterogeneity.     

Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality

We derive the asymptotic sampling distribution of various estimators frequently used to order distributions in terms of poverty, welfare, and inequality. This includes estimators of most of the poverty indices currently in use, as well as estimators of the curves used to infer stochastic dominance of any order. These curves can be used to determine whether poverty, inequality, or social welfare is greater in one distribution than in another for general classes of indices and for ranges of possible poverty lines. We also derive the sampling distribution of the maximal poverty lines up to which we may confidently assert that poverty is greater in one distribution than in another. The sampling distribution of convenient dual estimators for the measurement of poverty is also established. The statistical results are established for deterministic or stochastic poverty lines as well as for paired or independent samples of incomes. Our results are briefly illustrated using data for four countries drawn from the Luxembourg Income Study data bases.     

基于生存分析法的顾客生命周期计量研究——以商业银行信用卡顾客为例

截至目前,国内学者对于顾客生命周期的计量问题,无论是方法研究方面还是实证研究方面都未形成统一的结论。在生物学、医学等领域较为流行的生存分析方法基础上,针对实际的顾客生存资料调研数据,采用威布尔分布法和乘积极限法来估计商业银行信用卡顾客的生命周期,得出信用卡顾客的半数生存期为30个月的结论。这种将参数与非参数相结合的计量方法为国内信用卡顾客的生命周期计量提供了一种思路。     

Production,Process Investment,and the Survival of Debt‐Financed Startup Firms

Whether to invest in process development that can reduce the unit cost and thereby raise future profits or to conserve cash and reduce the likelihood of bankruptcy is a key trade‐off faced by many startup firms that have taken on debt. We explore this trade‐off by examining the production quantity and cost reducing R&D investment decisions in a two period model wherein a startup firm must make a minimum level of profit at the end of the first period to survive and operate in the second period. We specify a probabilistic survival measure as a function of production and investment decisions to track and manage the risk exposure of the startup depending on three key market factors: technology, demand, and competitor's cost. We develop managerial insights by characterizing how to create operational hedges against the bankruptcy risk: if a startup makes a “conservative” investment decision, then it also selects an optimal quantity that is less than the monopoly level and hence sacrifices some of first period expected profits to increase its survival chances. If it decides to invest “aggressively,” then it produces more than the monopoly level to cover the higher bankruptcy risk. We also illustrate that debt constraint shrinks the decision space, wherein such process investments are viable.