用期权定价模型评估企业并购的价值

针对传统企业并购价值评估模型的局限性,本文从期权的角度阐述了企业并购的期权特性,指出企业并购实质上相当于取得了一个看涨期权;并以连续支付红利的美式期权定价理论为基础,建立了企业并购价值评估的期权定价模型。最后,通过实例论述了如何应用该模型来评估企业并购价值,对实践中企业并购价值的合理确定具有重要的指导意义。     

A two-level electricity demand model : Evaluation of the connecticut time-of-day pricing test

A two-stage budgeting model is developed for electricity demand where comsumption in each period is treated as a different commodity. A relative household demand model is first estimated, a consistent price index for electricity is constructed, and then a total electricity consumption model is estimated. Economic procedures are derived which permit application of the model to both time-of-day price situations and also declining vlock price situatiions which result in non-linear budget sets. The model is applied to both types of situations- the data from the Connecticut time-of-day pricing test as well as data from the declining block rate situation of the prevoius year. The model is also tested in a forecasting application to time-of-day customers.     

分位数局部调整模型及应用

本文基于分位数的回归理论与方法,提出了一个新的经济计量模型:分位数局部调整模型,并给出了其数学表示、参数估计与预测方法等一整套建模技术。分位数局部调整模型能够细致地给出响应变量在各个分位点上的条件分位数,便于揭示响应变量位置、散布与形状等动态调整过程的全景信息,从而得到比均值局部调整模型更为深刻的结果。最后,将分位数局部调整模型应用于中国货币需求分析,结果显示,在货币需求的不同阶段,不仅调整速度不同,调整方式也呈现出非对称性;M1存在货币失踪之谜现象,而M2却在条件密度第一个最优区域实现了供求均衡;最优货币需求条件密度曲线较为分散,这为央行制定货币政策预留了足够的空间。     

基于灰色综合评价模型的供应商评估策略研究

针对有分层、具有定性指标、信息不完全且没有符合典型的概率分布的指标，基于层次分析法和灰色关联分析，提出了进行供应商评价的灰色综合模型。最后进行了实证分析，表明该模型是可行的，为解决供应商评价工作提供了一种全新的思路。     

RANDOM COEFFICIENT MODELS: THEORY AND APPLICATIONS

Abstract. This paper provides an overview of the rationale behind, and the implementation, and uses of, the random coefficient approach to econometric modelling. A simple random coefficient model is presented, and methods for estimating, testing, and validating such a model are described. A more general model is then presented. The general model is shown to include several fixed-coefficient models as special cases and can be estimated incorporating a variety of judgements concerning simplification. Finally, the paper reviews recent applications of random coefficient estimation.     

A Linear Programming Model of the Consumer Price Index Food Component

A bstract A linear programming model is used to measure the rate of inflation in the food component of the consumer price index A diet model to minimize the cost of a diet subject to constraints on nutritive requirements, variety, pal-atabihty, and menu-function is constructed and the rates of increase in a strict minimum cost model and an expanded constraint model are measured for the period 1980-87 Consistent with the consumer utility literature, it is found that the current Laspeyres index approach to measuring the cost of living in fact provides an upper limit on true cost of living increases Results also show that the cost of maintaining a minimum level of subsistence increases more rapidly than the cost of a more palatable diet Finally, the results show that in fact there is very little room for substitution among food items within a reasonable diet model     

The multi-state latent factor intensity model for credit rating transitions

A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of the stylized facts of credit rating migrations. Parameter estimation is based on Monte Carlo maximum likelihood methods for which the details are discussed in this paper. A simulation experiment is carried out to show the effectiveness of the estimation procedure. An empirical application is presented for transitions in a 7 grade rating system. The model includes a common dynamic component that can be interpreted as the credit cycle. Asymmetric effects of this cycle across rating grades and additional semi-Markov dynamics are found to be statistically significant. Finally, we investigate whether the common factor model suffices to capture systematic risk in rating transition data by introducing multiple factors in the model.     

基于模糊图论的企业物流绩效评价耗时模型

运用模糊图论的基本理论,建立了企业物流绩效评价评价耗时模型,包括评价过程的多重有向模糊图和广义模糊矩阵。模型首先对企业物流绩效评价评价各环节之间的关系进行了直观的描述,接着对评价各环节耗费的时间进行了定量的描述。通过该模型,可以定量计算评价工作总的耗费时间,为控制评价工作的时间提供了依据。     

基于Usher曲线的深基坑位移预测方法

基于深基坑工程位移时序的趋势类型,针对常用GM(1,1)模型不能用于描述非单调的摆动发展序列或具有饱和状态的S形序列的不足,将广泛用于经济和资源预测的Usher生长曲线运用到深基坑支护结构位移预测中,建立了Usher位移-时间预测模型,文章阐述了Usher模型参数的计算方法,并结合工程实例进行了计算分析,结果表明Usher模型的预测结果与实测结果吻合较好,具有较强的适用性,对基坑工程位移增长曲线能较好的模拟,可较准确地预测基坑支护位移。     

A Non-Proportional Hazards Model with Hazard Ratio Functions Free from Covariate Values

A brief survey on methods to handle non-proportional hazards in survival analysis is given with emphasis on short-term and long-term hazard ratio modelling. A drawback of the existing model of this nature is that except at time zero or infinity, the hazard ratio for a unit increase in the value of a covariate depends on the starting value. With two or more covariates, the hazard ratio for a unit increase in one covariate with other covariates held fixed depends in an unintended way on the values of the other covariates. We propose an alternative way to model short-term and long-term hazard ratios without the above drawbacks through a judicious choice of covariate-time interactions. Under the new model, it is easier to describe the time-varying effect of each covariate on the hazard. Nonparametric maximum likelihood estimation for the new model can be carried out in the same way as for the existing model. We also propose a product version of the existing model, which overcomes its second drawback but not the first. The advocated covariate–time interaction model provides a better fit to the Veterans Administration lung cancer data set than the original and product versions of the existing model.     

Optimal Processes Management for Over-Adjusted Process with Dependent Steps on Bank Industry

Process management is important for a company. An over-adjusted process may increase process quality variability, ultimately affecting the quality and cost of service or products. A two special-cause economic over-adjustment model is developed for controlling the service quality variation of the two-step process on a bank industry. The objective is to determine the optimal management policy for the two-step process, which minimizes the service quality variation and total quality control cost. A Markov chain approach is extended to derive the economi c adjustment model of the process, and the optimal management policy is obtained from optimization techniques. Application of the two special-cause over-adjusted model and the optimal management policy on the process management of a bank industry is demonstrated through an example.     

Cross-border mergers and acquisitions with heterogeneous firms: Technology vs. market motives

The most common form of foreign direct investment (FDI) is cross-border mergers and acquisitions (M&A). A common explanation for M&A activity identified in the industrial organization literature is that firms seek technological expertise. However, this has not been examined in the FDI literature. In this paper, I develop and estimate a model of cross-border M&A and focus on the technology seeking explanation. In particular, I develop a general equilibrium model of exporting, greenfield FDI, technology-seeking cross-border M&A, and market-seeking cross-border M&A with heterogeneous firms. The model predicts that firms from a larger country are more likely to acquire in a smaller country when M&A activity is driven by a technology-seeking motive, but the opposite is true when it is driven by a market-seeking motive. Using detailed data on worldwide M&A activity from 1985 to 2007, I find empirical evidence that cross-border M&A activity exhibits behavior consistent with this prediction.     

A simple model for predicting the number of servers necessary to cover a region

A simple regression model is developed to estimate the number of servers necessary to cover a region. Data for the model were obtained within a research design that included five replications of 180 experimental conditions. A total of 300 rectangular regions were generated, and a set covering location problem was solved for each region using three distance metrics. Statistical results established coverage radius, compactness, and the number of nodes in the region to be significant factors. The resulting regression model was applied to a South Carolina county. Its estimates are seen to be very close to the number of units needed to cover. The model is shown to be a convenient technique for quickly estimating the number of servers while exhibiting an error distribution that is conservatively biased towards overestimation. This last property is desirable for public emergency services.     

供应链环境下制造商生产能力合作与竞争模型研究

分析由两条两层供应链组成的模型,其中一条供应链中的制造商生产能力有余,而另一条供应链中的制造商生产能力不足的情况,建立了供应链环境下制造商生产能力的合作与竞合模型。通过对模型的分析,发现制造商采取竞争或合作策略的条件是随着市场需求的变化而变动的,最后通过一个算例进行验证。     

On construction of admissible quadratic estimators

A random linear model for spatially located sensors measured intensity of a source of signals in discrete instants of time is considered. A basis of a quadratic subspace useful in quadratic estimation of a function of model parameters is given. Received: December 1999     

项目组织结构复杂性风险评估及其在协作型项目组合中的扩散机制研究

探讨项目复杂性与项目风险的关系并证明了项目的组织结构复杂性是项目的风险来源。以项目组织结构的复杂性作为项目内部风险的衡量标准,建立了基于组织结构复杂性并考虑规模因素的项目风险评估模型。分析了项目组合中通常存在的项目间的相互关系以及每一种相互关系对项目组合整体风险的影响。利用Logistic映射对协作型项目组合建立了项目组织结构复杂性风险的扩散模型,以定量刻画项目组织结构复杂性风险在项目组合中的扩散机制。最后对模型进行了仿真并根据仿真结果给出了降低项目组合风险的策略。     

EWMA-GARCH模型与GARCH模型在估计收益率波动上的差异的实证及理论分析

VaR作为衡量风险的指标,其核心则在于对波动,亦即方差的估计。基于时间序列,关于条件方差的经典模型是GARCH模型,尽管后来又衍生出了EGARCH,PARCH等复杂模型,但在实务中GARCH模型仍占有重要的地位。文章分析了一种比较新的结合了EWMA模型的GARCH模型(以下称为EWMA-GARCH模型)计算VaR的参数估计方法,以检验其在估计波动上的实用性,并对实证检验结果做了理论分析。分析结果表明,尽管该结合模型缺乏完整的理论支持,但是其计算效果仍比较良好,当然这样良好的结果是建立在因缺乏理论依据而导致的对模型的其他要求之上的.至于是采用受理论支持的模型还是并不输实践价值的模型,文章也给出了一定的建议。     

Estimation of Markov regime-switching regression models with endogenous switching

Following Hamilton [1989. A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica 57, 357–384], estimation of Markov regime-switching regressions typically relies on the assumption that the latent state variable controlling regime change is exogenous. We relax this assumption and develop a parsimonious model of endogenous Markov regime-switching. Inference via maximum likelihood estimation is possible with relatively minor modifications to existing recursive filters. The model nests the exogenous switching model, yielding straightforward tests for endogeneity. In Monte Carlo experiments, maximum likelihood estimates of the endogenous switching model parameters were quite accurate, even in the presence of certain model misspecifications. As an application, we extend the volatility feedback model of equity returns given in Turner et al. [1989. A Markov model of heteroskedasticity, risk, and learning in the stock market. Journal of Financial Economics 25, 3–22] to allow for endogenous switching.     

Estimating asymptotic standard errors and inconsistencies of impact multipliers in nonlinear econometric models

This paper presents and discusses an analytic simulation procedure which can be used to estimate the asymptotic standard errors of impact multipliers in a structural, nonlinear econometric model. A stochastic simulation approach is used to obtain an approximate estimate of the inconsistencies of multipliers when computed from simulated results. A numerical example for the nonlinear Klein-Goldberger model is provided.