Variable precision rough set for multiple decision attribute analysis

A variable precision rough set (VPRS) model is used to solve the multi-attribute decision analysis (MADA) problem with multiple conflicting decision attributes and multiple condition attributes. By introducing confidence measures and a β-reduct, the VPRS model can rationally solve the conflicting decision analysis problem with multiple decision attributes and multiple condition attributes. For illustration, a medical diagnosis example is utilized to show the feasibility of the VPRS model in solving the MADA problem with multiple decision attributes and multiple condition attributes. Empirical results show that the decision rule with the highest confidence measures will be used as the final decision rules in the MADA problem with multiple conflicting decision attributes and multiple condition attributes if there are some conflicts among decision rules resulting from multiple decision attributes. The confidence-measure-based VPRS model can effectively solve the conflicts of decision rules from multiple decision attributes and thus a class of MADA problem with multiple conflicting decision attributes and multiple condition attributes are solved.

Multi scale risk measurement in electricity market:a wavelet based value at risk approach

Value at risk (VaR) is adopted to measure the risk level in the electricity market. To estimate VaR at higher accuracy and reliability, the wavelet variance decomposed approach for value at risk estimates (WVDVaR) is proposed. Empirical studies conduct in five Australian electricity markets, which evaluate the performances of both the proposed approach and the traditional ARMA-GARCH approach using the Kupiec backtesting procedure. Experimental results suggest that the proposed approach measures electricity market risks at higher accuracy and reliability than the bench mark ARMA-GARCH approach, as indicated by the higher p values during the Kupiec backtesting procedure. In addition, the new approach also provides more insight into the risk evolution process over time and helps in adjusting VaR estimates to the time horizons that best suit investor interests. The distribution of risk according to investor preferences is shown by decomposing VaR across different time horizons. This also provides important information for the appropriate aggregation of risk measures based on investor investment preferences.

不确定需求下故障共享单车回收周期性车辆路径问题研究

为了及时有效地回收城市道路网络中的故障共享单车,对分散于路网边上的故障单车进行聚类形成收集点,考虑聚类收集点上回收需求呈现的不确定性特征,建立以行驶总距离最小为目标的回收周期性车辆路径选择模型.采用基约束鲁棒优化方法,利用有界区间对不确定的回收量进行描述,引入扰动系数和控制系数调节模型的鲁棒性和适应性.针对模型设计近似算法求解,证明近似算法的时间复杂性,分析算法近似比的上下界,用实例验证算法的近似比,结果表明算法性能较好.最后,通过分析回收量发生波动时,即扰动系数和控制系数对目标函数和算法近似比的影响,进一步验证了算法和模型的有效性.

An Improvement to Multiple Criteria ABC Inventory Classification Using Shannon Entropy

This paper extends the Ng-model [Ng, 2007] for multiple criteria ABC inventory classification based upon Shannon entropy. The proposed approach determines the common weights associated with all criteria importance rankings, and provides a comprehensive scoring scheme by aggregating all rankings of the criteria importance. A numerical illustration is presented to compare the model with previous studies.

Manufacturers' Channel Competition with Retailer Demand-Enhancing Service

Manufacturers’channel competition with service is examined in this paper.Specifically,the authors consider channel competition within a supply chain comprising two manufacturers and one single retailer where each manufacturer can choose to sell its products either directly to the end market(online channel,say)or through the potential retail channel,based on the profit maximization criterion,which is influenced by exogenous market conditions,such as the degree of competition,etc.Furthermore,the retailer provides additional demand-enhancing service to promote the manufacturer’s products distributed via it.If only one of the manufacturers sells products through the retailer,its products will be promoted by the additional retail service,which poaches demand of products of the manufacturer who adopts direct online channel.Products of both manufacturers are supported by the retailer’s promotional service when both distribute their product through the common retailer.Finally,some managerial implications are derived from numerical analyses of our model,which explain the phenomena in practice and conclude the paper.

Intraday Volume Percentages Forecasting Using a Dynamic SVM-Based Approach

This paper proposes a dynamic model to forecast intraday volume percentages by decomposing the trade volume into two parts: The average part as the intraday volume pattern and the residual term as the abnormal changes. An empirical test on data spanning half-a-year gold futures and S&P 500 futures reveals that a rolling average of the previous days' volume percentages shows great predictive ability for the average part. An SVM approach with the input pattern consisting of two categories is employed to forecast the residual term. One is the previous days' volume percentages in the same time interval and the other is the most recent volume percentages. The study shows that this dynamic SVM-based forecasting approach outperforms the other commonly used statistical methods and enhances the tracking performance of a VWAP strategy greatly.

A Nonlinear Interval Portfolio Selection Model and Its Application in Banks

在古典 Markowitzs 吝啬变化的模型，象内在的财产未来回来的平均数和协变性那样的参数被假定确切被知道。然而，这不总是是盒子。参数经常对应于在一个范围以内的秋天，或罐头在投资决定必须被做的时间暧昧地被知道的数量。处于如此的状况，投资者在投资和风险等等上决定回来并且基于经验和经济智慧做公事包决定。这份报纸试着在模糊集合理论使用间隔数字的概念与一个银行的流畅要求的考虑把古典吝啬变化的公事包选择模型递一个吝啬缺点的半变化模型。半变化限制被采用控制缺点风险，填基于描绘缺点风险的线性半绝对的偏差的存在间隔公事包优化模型。模拟结果证明模型与回来的最高或最低的吝啬的历史的率为危险财产要用体力地表现，最佳的投资比例有好稳定性。这建议为这些种财产，模型能减少偏差根据决定制造者经验和经济智慧引起的高偏差的风险。

Resource Allocation in Public Healthcare: A Team-DEA Model

这份报纸联合队和数据包封分析(DEA ) 的理论设计机制最佳地在公共保健分配资源。在它的统治下面的一个法令的权威和公共医院作为一个队，其成员寻求在公共保健是公众的分享的机构的限制下面高效地操作被解释好。单个公共医院利用 DEA 最大化自己发薪，到对方公众医院的发薪不从外部效果掉落并且从而减去的队条件的题目由保健的公共供应创造了。产生 team-DEA 答案，它被显示是两个一个别地有效并且 team-satisficing 平衡并且以一个会聚的算法可计算出来，然后能被权威使用在公共保健决定资源的最佳的分配。一个盒子基于中国数据被介绍说明 team-DEA 模型准备好了的 operationalization 和计算。

Copula-Based Risk Management Models for Multivariable RMB Exchange Rate in the Process of RMB Internationalization

This paper investigates the dependence of the exchange rate of onshore Renminbi(RMB)and offshore RMB against US dollar(i.e., CNY and CNH) based on copula models. Eleven different copulas were selected to construct multivariate distribution and estimate the value-at-risk for RMB exchange rate. Empirical results show that time-invariant Student-t copula is the best model to fit the sample data. The positive upper and lower dependence indicates that CNY and CNH series tend to move in the same direction. Moreover, the dependence between the two exchange rates is asymmetric,which means that traditional models, such as Pearson's correlation, are inappropriate to measure the correlations between these markets. The best fitted model is chosen to estimate the financial risk,which can help business practitioners and policymakers track risk evolution and make good decisions.

A Study on Transport Costs and China＇s Exports： An Extended Gravity Model

This paper suggests an extending conventional gravity model design to empirically analyze the effect of transport costs and port efficiency on China's export flows. It shows that factor endowment and transport costs variables affect export trade value in directions that New Trade Theory(NTT) predicted. Also, the evidence indicates that, controlling for the effects of transport costs on trade, variables in traditional gravity model are consistent with previous empirical studies in both magnitudes and directions. Moreover, more than 22% of the variation in Chinese export trade can be explained by those three variables alone. The findings reported in this paper empirically explains how seriously transport costs and port efficiency affect China's export growth by comparing effects of labour production factor costs on external trade. It suggests that the improvement of port efficiency and reduction of road transport costs play a vital role in China's export competitiveness in the global market.

Bi-Cubic B-Spline Fitting-Based Local Volatility Model with Mean Reversion Process

This paper studies the traditional local volatility model and proposes:A novel local volatility model with mean-reversion process.The larger is the gap between local volatility and its mean level,the higher will be the rate at which local volatility will revert to the mean.Then,a B-spline method with proper knot control is applied to interpolate the local volatility matrix.The bi-cubic B-spline is used to recover the local volatility surface from this local volatility matrix.Finally,empirical tests show that the proposed mean-reversion local volatility model offers better prediction performance than the traditional local volatility model.

Entrepreneurship Measurement and Comparison:Holistic Acceptability Global Entrepreneurship Index

The Global Entrepreneurship and Development Institute annually publishes the Global Entrepreneurship Index(GEI)to show entrepreneurship of each country/area.The GEI is obtained by averaging the scores of three sub-indexes,entrepreneurial attitudes,entrepreneurial abilities and Entrepreneurial aspirations.However,this GEI construction method with equal weights for three subindexes may be controversial,since the relative importance among the three sub-indexes may vary across countries and areas due to economic and social/cultural reasons.This study comprehensively considers all possible weights,and formulates an interval entrepreneurship evaluation matrix.Employing the Stochastic multicriteria acceptability analysis,the authors build an improved GEI,which the authors term the Holistic Acceptability Global Entrepreneurship Index.This method differs from the conventional wisdom that assigns exact values to corresponding weights,but explores a weight space considering all possible weight sets.Finally,the proposed method is confirmed using an empirical study measuring and comparing the entrepreneurship of the top 20 countries and areas in terms of 2017 GEI.