基于复杂网络的信用风险传染模型研究

本文从信用风险持有者的心理和行为角度对信用风险传染过程进行了分析,通过引入信用风险传染的主体行为因素,建立了信用风险传染的网络模型。借助严格随机占优理论,分别探讨了社会网络中个体之间的关联关系、个体的风险态度、个体的风险抵御能力、金融市场监管者的监控强度和个体的网络结构特征对信用风险传染的影响机制,通过仿真实验进一步验证理论推到的正确性,并直观地刻画了信用风险传染的内部性和外部性对信用风险传染行为及其演化的影响。     

基于测度变换方法的随机型创新幂式期权定价

随机型创新幂式期权以其结构简明、风险可控而受到投资者青睐。针对传统方法求解随机型期权存在的困难,提出用测度变换方法解决随机幂式期权的定价模型。受鞅定价方法的启发,推广计价单位的选取以获取相应的等价测度变换,得到随机利率情形下具有一般支付函数的测度变换公式;以此为基础选取远期债券为计价单位,并考虑债券价格波动和股价波动的相关性,可以方便地推导出随机型幂式期权定价模型。通过对模型风险特征的数值模拟分析,说明了幂型期权的优势所在。此项研究结论对金融衍生产品的发行者和投资者具有一定的理论借鉴意义。     

基于随机需求的供应链产供销计划协同模型研究

考虑随机客户需求,研究从供应商到最终客户的多层供应链网络产供销计划协同问题。根据给定的假设条件和问题的分析,首先从系统整体优化的角度,建立带有补偿问题的多周期二级随机规划模型,然后提出了优化-仿真相结合的模型求解策略。最后,给出仿真数据进行算例分析,对比采取协同和异步方式制定产供销计划在总成本方面的差异,分析基于随机需求和确定性平均需求的产供销计划在总成本方面的分布特性,计算结果表明随机需求条件下的产供销计划协同模型一方面可以显著缩减供应链总成本,另一方面可以有效控制原材料采购量、产品产量和发货量,减少库存,从而降低客户需求波动带来的市场风险。     

Topics in Microbial Risk Assessment: Dynamic Flow Tree Process

Microbial risk assessment is emerging as a new discipline in risk assessment. A systematic approach to microbial risk assessment is presented that employs data analysis for developing parsimonious models and accounts formally for the variability and uncertainty of model inputs using analysis of variance and Monte Carlo simulation. The purpose of the paper is to raise and examine issues in conducting microbial risk assessments. The enteric pathogen Escherichia coli O157:H7 was selected as an example for this study due to its significance to public health. The framework for our work is consistent with the risk assessment components described by the National Research Council in 1983 (hazard identification; exposure assessment; dose-response assessment; and risk characterization). Exposure assessment focuses on hamburgers, cooked a range of temperatures from rare to well done, the latter typical for fast food restaurants. Features of the model include predictive microbiology components that account for random stochastic growth and death of organisms in hamburger. For dose-response modeling, Shigella data from human feeding studies were used as a surrogate for E. coli O157:H7. Risks were calculated using a threshold model and an alternative nonthreshold model. The 95% probability intervals for risk of illness for product cooked to a given internal temperature spanned five orders of magnitude for these models. The existence of even a small threshold has a dramatic impact on the estimated risk.     

带有市场交易信息和随机微观噪声下的杠杆效应研究

在风险管理中杠杆效应的现象广泛存在，也是金融计量学中的重要议题。高频金融市场中蕴含着丰富的交易信息，而这些信息并不能都看作随机噪声，因此探讨利用市场交易信息并在带有随机噪声模型下研究杠杆效应具有重要意义。本文在带有市场交易信息和随机微观噪声相结合的模型下研究了杠杆效应，提出了新的杠杆效应估计，该估计具有n^1/8的收敛速度，同时给出了估计的方差和相关的定理。通过模拟分析得出利用广泛的市场微观信息可以更有效和更精确地对杠杆效应进行估计，模拟的结果表明本文提出的杠杆效应估计具有更好的渐近正态性和更小的偏差。最后将提出的估计应用到实证分析中，发现杠杆效应对未来一天波动率的预测具有显著性影响。     

Dynamic Valuation Decomposition Within Stochastic Economies

I explore the equilibrium value implications of economic models that incorporate responses to a stochastic environment with growth. I propose dynamic valuation decompositions (DVD's) designed to distinguish components of an underlying economic model that influence values over long investment horizons from components that impact only the short run. A DVD represents the values of stochastically growing claims to consumption payoffs or cash flows using a stochastic discount process that both discounts the future and adjusts for risk. It is enabled by constructing operators indexed by the elapsed time between the trading date and the date of the future realization of the payoff. Thus formulated, methods from applied mathematics permit me to characterize valuation behavior and the term structure of risk prices in a revealing manner. I apply this approach to investigate how investor beliefs and the associated uncertainty are reflected in current‐period values and risk‐price elasticities.     

公司价值的随机优化模型

本文研究了净现金流为随机过程情况下的企业价值,并建立了企业价值的随机优化模型。探讨了在一定的风险水平和其它相关约束条件下,确定企业的资本结构、企业债务的承担能力等,使得公司价值最大化,并应用于实际项目中。     

Using simulation to manage project supply chain in the offshore oil and gas industry

This paper is aimed at comparing simulation against spreadsheets as decision support tools to properly manage project supply chain in the offshore oil and gas industry. The paper presents a case study related to the problem of sizing a chain for pipeline laying from an offshore field in the Barents sea to the Russian coast. Results obtained through a spreadsheet developed by an oil and gas company have been compared to the ones gathered from an ad hoc simulation model. A simulation model with no stochastic variable has been introduced: results are quite similar to the ones of the spreadsheet, which allowed to validate the simulation model. However, the spreadsheet cannot take into account the continuous move of the pipe-lay vessel while laying the pipes and it does not consider stochastic variables whose effect in real life is not negligible. Both weaknesses above are discussed.     

基于状态空间的贝叶斯跳跃厚尾金融随机波动模型研究

针对金融市场中跳跃特征的刻画问题,提出了贝叶斯跳跃厚尾随机波动模型。通过随机波动模型的结构分析和状态空间转换,设计了模型参数估计的MCMC算法,利用Kalman滤波和高斯模拟平滑方法估计模型的潜在波动,运用贝叶斯因子对随机波动类模型进行比较分析,并利用中国和美国的股市收益数据进行实证分析。研究结果表明:在刻画中、美两国股票市场的波动特征方面,跳跃厚尾随机波动模型要明显优于厚尾随机波动模型和标准随机波动模型,并且金融危机背景下的中国和美国股票市场都具有明显的波动持续性以及跳跃特征。     

Robust Stochastic Lot‐Sizing by Means of Histograms

Traditional approaches in inventory control first estimate the demand distribution among a predefined family of distributions based on data fitting of historical demand observations, and then optimize the inventory control using the estimated distributions. These approaches often lead to fragile solutions whenever the preselected family of distributions was inadequate. In this article, we propose a minimax robust model that integrates data fitting and inventory optimization for the single‐item multi‐period periodic review stochastic lot‐sizing problem. In contrast with the standard assumption of given distributions, we assume that histograms are part of the input. The robust model generalizes the Bayesian model, and it can be interpreted as minimizing history‐dependent risk measures. We prove that the optimal inventory control policies of the robust model share the same structure as the traditional stochastic dynamic programming counterpart. In particular, we analyze the robust model based on the chi‐square goodness‐of‐fit test. If demand samples are obtained from a known distribution, the robust model converges to the stochastic model with true distribution under generous conditions. Its effectiveness is also validated by numerical experiments.     

基于随机久期缺口控制的全资产负债优化模型

资产负债管理是银行等金融机构在负债结构和总量一定的前提下,通过对资产进行优化配置,达到资产流动性、盈利性和安全性“三性”之间的平衡。本文基于CIR动态利率期限结构求解随机久期,对包括增量和存量在内的全部资产负债组合的久期缺口进行预留和约束,构建资产负债优化模型控制利率风险。本文的创新与特色有三:一是以控制CIR利率期限结构的随机久期缺口为约束条件建立非线性规划模型、对资产配置进行利率风险免疫,反映了利率随时间的动态变化,突破了Macaulay久期、FW久期等现有研究的利率随时间的变化是固定不变或平行移动的限定条件,使资产配置的利率风险免疫更加符合现实情况。二是建立了包括增量资产负债与存量资产负债的全资产负债优化配置模型,改变了现有资产负债模型大多只考虑增量资产负债、而忽略存量资产负债的弊端。三是以市场利率朝着最不利方向变动时、预留缺口损失后的资本充足率仍满足监管要求为约束条件,保证了在利率不利变动情况下损失仍在可控范围内,在利率有利变动时银行净值增加。     

基于多阶段随机规划模型的国债动态积极投资策略

本文提出国债组合投资的多阶段随机规划模型,导出基于未来利率市场不确定信息的具备动态调整特点的国债组合主动投资策略。该模型采用基于利率水平、斜率和曲率"三位一体"的离散情景树刻画未来利率期限结构动态演化过程,其中特别考虑了广义货币供给变动的影响;通过最小化国债组合收益的条件风险价值,对国债组合进行主动动态调整;同时兼顾国债投资安全性、流动性和收益性等要求,实现了国债组合投资管理中利率风险规避和收益能力的有效匹配。实证研究表明,与传统久期配比免疫模型相比,该模型确定的最优策略不仅能够为国债组合提供更强的抵御利率风险能力,而且能够稳步提升其收益空间,为金融机构实现国债投资的主动管理提供决策支持。     

STOCHASTIC COST-VOLUME-PROFIT ANALYSIS WITH A LINEAR DEMAND FUNCTION

In this paper we incorporate a linear demand function to model the price-volume causal relationship into stochastic cost-volume-profit (CVP) analysis. We assume that the objective function is to maximize expected profit; other objective functions are also discussed and compared. A linear stochastic model follows from which probabilistic statements can be easily obtained if the random variables are assumed to be multivariate normal. The basic framework is shown to be a special case of project value maximization where project value is the cash flow of the project discounted for time and risk according to the capital asset pricing model. Moreover, an intertemporal extension that considers inventory is developed. In summary, a new approach to stochastic CVP analysis that incorporates the management decision process in an uncertain environment is developed.     

On the Measurement of Perceived Consumer Risk

The role of perceived risk in consumer behavior has been studied extensively by academic researchers. This paper introduces a methodology for the measurement of the effects of product features, marketing mix components, and individual differences on perceived consumer risk based on theoretical foundations in the literature. A conjoint-type model based on paired comparison judgments is estimated to provide attribute weights. A modification of a stochastic multidimensional scaling-based vector model is then used to measure and summarize individual consumer differences with respect to the impact of brand attributes and marketing mix components on latent levels of perceived consumer risk. An illustration is provided using students’ risk perceptions of sports cars.     

随机期限结构与国债定价模型

假设债价扩散函数v(t,T)为时间t的二次函数,是利用风险中性方法建立随机期限结构模型的关键;而随机期限结构模型又是建立债券定价模型的基础。本文不但介绍了有关的理论模型,而且利用我国国债市场的价格数据进行实证研究,建立了具体的瞬态年利率随机期限和国债961的定价模型。     

养老金统筹账户与个人账户最优组合策略研究

本文使用投资组合理论对养老金统筹账户与个人账户的最优组合策略进行研究。为此,我们首先分析了确定性条件下的账户选择问题,然后,在随机假设下对不同账户的收益进行精算建模,在此基础上构建了养老金账户最优组合模型,最后,对上述模型进行了数值求解。研究表明：（1）统筹账户与个人账户的收益负相关,二者的组合能够形成一个有效的风险对冲机制;（2）混合制的有效边界在现收现付制和累积制的上方,因此,从风险-收益的角度讲,混合制优于单一养老金制度;（3）与最优账户组合相比,现行统筹账户的占比偏高,个人账户占比偏低。本文的政策含义在于,适当的降低现行统筹账户的占比,提高个人账户的占比能够降低养老金账户的风险水平,增加账户的收益。     

双随机复合泊松损失下巨灾债券定价与数值模拟

上世纪90年代出现的巨灾债券是以规避巨灾财产损失为目的的新型非传统风险转移金融创新工具之一,在我国有良好的发展前景。本文针对巨灾风险事件呈现出周期性与不规则的上升特征,构建了BDT过程用以刻画巨灾风险的抵达过程,并基于风险中性测度技术,在随机利率环境与双随机复合泊松损失条件下,导出了巨灾债券定价公式。进而结合伦敦同业银行拆借利率数据与美国保险服务所提供的PCS损失指数估计并校正了模型参数。最后,通过数值模拟检验了利率风险与巨灾风险如何影响巨灾债券的价格,同时验证了定价模型的可行性。     

多重随机环境下跨国采购和定价联合决策模型

在批发价、汇率和需求的三重随机波动环境下，考虑跨国采购与定价联合决策问题。本文主要利用随机过程来刻画批发价和汇率的随机性，并将两者的统计规律性纳入带有随机需求的决策模型的理论框架，进而给出跨国采购和定价联合决策模型及其可靠性评估机制。模型的相关结论表明:其一、不同周期的最优策略受到批发价与汇率波动的交互影响，当批发价和汇率波动性的重叠效应具有下降趋势时，销售商所采取的最优策略为增加一定的采购量，以实现系统的期望利润目标；其二、当批发价与汇率统计结构的属性为不可约遍历马氏链时，随机系统的下行风险具有良好的稳定性；其三、决策者可以通过本文提出靶向成本区间的上穿评估机制刻画随机系统的成本涨幅特征及其变化趋势，以解决供应商的最佳选择问题，从而达到了规避风险的运营目标。     

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.