基于贝叶斯Wishart波动模型的原油市场与股市动态相依性研究

针对时变相关系数矩阵在多变量随机波动模型的估计问题,构建了贝叶斯动态相关Wishart波动模型。在CC-MSV模型的基础上,设置精度矩阵服从Wishart分布,使得模型的相关系数矩阵具有时变特征。通过模型的统计结构分析,选择参数先验分布,设计相应的Gibbs-MTM-ARMS混合算法,据此估计模型参数;并利用上证综合指数、标普500指数与原油期货价格数据进行实证分析。研究结果表明：模型能够有效地刻画原油市场与股票市场的动态相依性;金融危机期间,股票市场与原油市场的相关性较强,并且难以判断正负方向;金融危机后,中国股票市场与原油市场呈现极微弱的相关性,而美国股票市场与原油市场的正相关性较为明显。     

Management of Energy Technology for Sustainability: How to Fund Energy Technology Research and Development

Operations management methods have been applied profitably to a wide range of technology portfolio management problems, but have been slow to be adopted by governments and policy makers. We develop a framework that allows us to apply such techniques to a large and important public policy problem: energy technology R&D portfolio management under climate change. We apply a multi‐model approach, implementing probabilistic data derived from expert elicitations into a novel stochastic programming version of a dynamic integrated assessment model. We note that while the unifying framework we present can be applied to a range of models and data sets, the specific results depend on the data and assumptions used and therefore may not be generalizable. Nevertheless, the results are suggestive, and we find that the optimal technology portfolio for the set of projects considered is fairly robust to different specifications of climate uncertainty, to different policy environments, and to assumptions about the opportunity cost of investing. We also conclude that policy makers would do better to over‐invest in R&D rather than under‐invest. Finally, we show that R&D can play different roles in different types of policy environments, sometimes leading primarily to cost reduction, other times leading to better environmental outcomes.     

Supplier Selection for Framework Agreements in Humanitarian Relief

In this study, we consider the supplier selection problem of a relief organization that wants to establish framework agreements (FAs) with a number of suppliers to ensure quick and cost‐effective procurement of relief supplies in responding to sudden‐onset disasters. Motivated by the FAs in relief practice, we focus on a quantity flexibility contract in which the relief organization commits to purchase a minimum total quantity from each framework supplier over a fixed agreement horizon, and, in return, the suppliers reserve capacity for the organization and promise to deliver items according to pre‐specified agreement terms. Due to the uncertainties in demand locations and amounts, it may be challenging for relief organizations to assess candidate suppliers and the offered agreement terms. We use a scenario‐based approach to represent demand uncertainty and develop a stochastic programming model that selects framework suppliers to minimize expected procurement and agreement costs while meeting service requirements. We perform numerical experiments to understand the implications of agreement terms in different settings. The results show that supplier selection decisions and costs are generally more sensitive to the changes in agreement terms in settings with high‐impact disasters. Finally, we illustrate the applicability of our model on a case study.     

Managing Demand Risk in Tactical Supply Chain Planning for a Global Consumer Electronics Company

We consider the problem of managing demand risk in tactical supply chain planning for a particular global consumer electronics company. The company follows a deterministic replenishment‐and‐planning process despite considerable demand uncertainty. As a possible way to formally address uncertainty, we provide two risk measures, “demand‐at‐risk” (DaR) and “inventory‐at‐risk” (IaR) and two linear programming models to help manage demand uncertainty. The first model is deterministic and can be used to allocate the replenishment schedule from the plants among the customers as per the existing process. The other model is stochastic and can be used to determine the “ideal” replenishment request from the plants under demand uncertainty. The gap between the output of the two models as regards requested replenishment and the values of the risk measures can be used by the company to reallocate capacity among different products and to thus manage demand/inventory risk.     

供应商管理库存环境下的分销网络连续近似模型

本文在现有连续近似(CA)模型的基础上,从供应商管理库存(VMI)角度出发,引入了PowerofTwo(POT)周期配送策略,构建了VMI环境下分销网络设计的CA模型。该模型的目标函数不仅包括了分销中心的建设 运营费用、运输费用,而且引进了实际中关注的存储费和订货费;该模型在确定分销网络结构的同时,也确定了各分销中心的库存策略和对其客户的配送策略。文中给出了模型的解法,利用此解法对算例进行求解,并分析了求解的结果,得出各参数变化对解的影响。     

中国股市波动性与成交量共同的长期记忆性研究

研究了上证30指数和深圳成分指数所含个股的成交量与收益波动性的长程相关关系.文章应用多变量频域两步半参数估计方法,辅助数据加窗技术对非平稳时间序列的长期记忆性进行了一致有效的估计.研究结果发现中国股票市场的成交量和波动性均具有显著的长期记忆性,并且对于大多数股票而言,成交量序列与波动性序列具有相同的长期记忆性.表明同时驱动成交量和收益波动性的潜在信息流本身具有长期记忆特征.     

Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location‐Specific Premiums in the Netherlands

As flood risks grow worldwide, a well‐designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood‐loss‐sharing program involving private insurance based on location‐specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS‐based flood model and a stochastic optimization procedure with respect to location‐specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile‐related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.     

Construction Safety Risk Modeling and Simulation

By building on a genetic‐inspired attribute‐based conceptual framework for safety risk analysis, we propose a novel approach to define, model, and simulate univariate and bivariate construction safety risk at the situational level. Our fully data‐driven techniques provide construction practitioners and academicians with an easy and automated way of getting valuable empirical insights from attribute‐based data extracted from unstructured textual injury reports. By applying our methodology on a data set of 814 injury reports, we first show the frequency‐magnitude distribution of construction safety risk to be very similar to that of many natural phenomena such as precipitation or earthquakes. Motivated by this observation, and drawing on state‐of‐the‐art techniques in hydroclimatology and insurance, we then introduce univariate and bivariate nonparametric stochastic safety risk generators based on kernel density estimators and copulas. These generators enable the user to produce large numbers of synthetic safety risk values faithful to the original data, allowing safety‐related decision making under uncertainty to be grounded on extensive empirical evidence. One of the implications of our study is that like natural phenomena, construction safety may benefit from being studied quantitatively by leveraging empirical data rather than strictly being approached through a managerial perspective using subjective data, which is the current industry standard. Finally, a side but interesting finding is that in our data set, attributes related to high energy levels (e.g., machinery, hazardous substance) and to human error (e.g., improper security of tools) emerge as strong risk shapers.     

The Value of Weather Information for E‐Commerce Operations

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.     

湖北省主要农产品技术效率与规模经济性的实证考察

采用超越对数生产函数形式的随机前沿模型,对湖北省2003年农产品生产的规模经济性和技术效率进行了分析比较,得出以下结论：（1）物质费用和播种面积是重要的生产投入要素,对产量的贡献基本上为正;（2）劳动投入的产出弹性有正有负;（3）各农产品的平均规模经济效果不明显,只有小麦的生产规模经济递增;（4）各种农产品的技术效率水平存在较大差距,其中棉花、蔬菜、禽肉最高,而水果、生猪最低。最后,得出两点政策建议：一是应克服技术创新的障碍因素,调动科研、推广和生产三方面的积极性,使农业科技在今后的农业增长中得到最大的发挥;二是建立新型的经营组织,以解决农业基础技术设施的投资问题。