耐用品长期风险模型的广义矩估计和可测性研究

基于我国2002年到2012年的季度数据,本文使用广义矩估计方法检验了耐用品长期风险模型。模型参数依赖的状态变量不可观测,通过推导把状态变量表示成可以观测的指标价格红利比率,从而可以对模型参数进行估计。研究表明,投资者的风险厌恶系数和跨期替代弹性相互分离,模型能够有效刻画投资者的消费和投资行为特征。此外,模型预测成分对于红利增长率、市场收益率和股权溢价有较强的预测能力,而对消费增长率的预测能力有限。     

基于EMD-GA-BP与EMD-PSO-LSSVM的中国碳市场价格预测

由于碳交易市场价格的波动性大及相互影响关系的复杂性,本文试图构建碳价格长期和短期的最优预测模型。考虑到碳交易价格波动的趋势性和周期性特点,基于经验模态分解算法(EMD)、遗传算法(GA)—神经网络(BP)模型、粒子群算法(PSO)—最小二乘支持向量机(LSSVM)模型及由它们构建的组合预测模型,对中国碳市场交易价格进行短期预测和长期预测。实证分析中将影响碳交易价格的不同宏观经济因素和碳价格时间序列因素做为输入变量,分别代入组合模型进行预测。研究结果表明,在短期预测中,EMD-GA-BP模型预测效果优于GA-BP模型和PSO-LSSVM模型;而在长期预测中,组合模型EMD-PSO-LSSVM模型预测效果优于只考虑碳价格波动趋势性或周期性预测效果。     

基于新陈代谢和Verhulst灰色模型的山西省人口老龄化趋势预测

通过选取2005-2013年山西省常住人口及65岁以上人口数据,利用新陈代谢灰色模型对山西省未来老龄人口进行短期预测.并用灰色Verhulst模型对老龄人口进行了长期预测.新陈代谢灰色模型预测到2016年山西省常住人口为3799.10万,65岁及以上人口为323.98万,老龄化比重约为8.53%,灰色Verhulst模型预测到2020年65岁及以上人口为407.87万.模型检验结果表明:预测精度均为Ⅰ级,预测相对误差均较小,预测精度较高.     

基于新陈代谢和Verhulst灰色模型的山西省人口老龄化趋势预测北大核心

通过选取2005-2013年山西省常住人口及65岁以上人口数据,利用新陈代谢灰色模型对山西省未来老龄人口进行短期预测.并用灰色Verhulst模型对老龄人口进行了长期预测.新陈代谢灰色模型预测到2016年山西省常住人口为3799.10万,65岁及以上人口为323.98万,老龄化比重约为8.53%,灰色Verhulst模型预测到2020年65岁及以上人口为407.87万.模型检验结果表明:预测精度均为Ⅰ级,预测相对误差均较小,预测精度较高.     

基于双因子已实现GARCH模型的波动率预测研究

准确地预测金融市场的波动率对市场管理者和参与者而言都是至关重要的。本文在标准已实现GARCH模型基础上,将条件方差乘性分解为长期方差和短期方差两部分,分别构造包含杠杆函数的长期方差方程和短期方差方程,用以捕捉波动率的长记忆性和短期微观波动。运用上证综指和日经指数的日收盘价、已实现方差和已实现核波动此类高频数据进行实证分析,结果表明:与标准已实现GARCH模型相比,两指数的双因子已实现GARCH模型在样本内表现出更大的似然估计值;通过样本外误差函数分析和DM检验,双因子已实现GARCH模型也取得更好表现。     

跳-扩散过程下具有目标杠杆比率的违约风险模型

本文在研究公司债务违约风险时,假设公司价值的动态变化服从跳-扩散过程;假设公司可以根据公司价值的变化调整其债务水平,因而存在公司的目标杠杆比率,违约边界定义为公司历史价值的对数加权平均;当公司价值下降到违约边界时发生债务违约.数值模拟表明公司债务的信用利差对公司的目标杠杆比率和跳过程的强度具有高度的敏感性.本文的模型解决了在长期和短期信用利差预测时结构化模型和约化模型存在的缺陷.     

基于多种灰色模型对比的广西外贸加工贸易预测研究——灰色系统理论与应用系列论文之二

根据广西2009-2015年外贸加工贸易的数据,构建多种灰色模型,用残差检验和后验差检验计算小误差概率和均方差比,以此判断各模型的精度,并对广西外贸加工贸易额进行了预测.预测结果表明,新陈代谢模型在广西外贸加工贸易的短期预测中精度较高,Verhulst模型在广西外贸加工贸易的长期预测中精度较高.根据预测结果,提出构建并完善加工贸易数据平台,打造中国—东盟区域性制造中心,高端锁定广西-东盟加工贸易产业链,强化投资便利化与人才吸引力,加大对中小型加工贸易企业的扶持等对策建议.     

消费者信心指数与CPI分类指数的动态分析

针对消费者信心指数(CCI)与CPI、CPI分类指数构建了长期自回归分布滞后模型和短期误差修正模型.实证结果表明,一方面,CCI和CPI、各个CPI分类指数之间不仅存在时滞性的长期均衡关系,而且存在短期调整特征.另一方面,CPI和CPI分类指数与CCI的动态特征存在显著差异.因此,在分析CCI对价格预测作用时,在关注CPI和CPI分类指数的同时,也需要关注CCI与CPI分类指数的长期均衡和短期调整的时滞性,以便更好地发挥CCI预测经济走势的先行指标功能.     

经济政策不确定性与短期利率波动——基于BHK-L-MIDAS模型的实证研究

本文在BHK模型的基础上，考虑短期利率波动杠杆效应和EPU对短期利率波动的影响，构建了一个包含杠杆效应和EPU的混频短期利率模型，即BHK-L-MIDAS模型对短期利率波动进行建模与预测。采用上海银行间同业拆借利率(SHIBOR)和中国EPU指数数据对构建的BHK-L-MIDAS模型进行实证分析，结果表明：短期利率波动存在“反向杠杆效应”;EPU对短期利率波动具有显著负向的影响；BHK-L-MIDAS模型相较于竞争模型(BHK和BHK-MIDAS模型)获得了更好的样本内数据拟合效果。基于三种损失函数以及模型置信集(MCS)检验对模型样本外短期利率波动预测能力的分析表明：BHK-L-MIDAS模型相比BHK模型和BHK-MIDAS模型具有更高的样本外预测精度，且BHK-L-MIDAS模型在不同预测窗口表现出的预测能力具有稳健性。最后，VaR分析表明BHK-L-MIDAS模型在短期利率市场风险度量方面的经济价值。     

报童模型及ARMA预测在航空配餐问题中的应用

航班承载人数的不确定性,造成航空公司在配餐中利润的流失,现存的配餐模式存在较多的浪费.本文利用基于损失厌恶的报童模型和ARMA时间序列分析模型对深圳航空公司某航班的配餐份数进行了建模分析和预测,并通过对两种模型输出的比较,得出了长期预测与短期预测的模型应用理论.将实际的历史数据代人到模型中验证,其结果优于经验模式下的配餐盈利情况.本文所采用的研究方法和研究结果对航空公司的精益发展有建设性的意义.     

我国国债规模对宏观经济影响实证分析

随着以希腊债务危机为导火索的欧洲债务危机的愈演愈烈,国债对宏观经济的影响再一次成为了经济学讨论的热点.首先从直观图形着手,运用H-P滤度法去除趋势后,计算各变量的偏离趋势百分比,对比国债规模代替变量与宏观经济效应代替变量之间的偏离趋势图,从图形得到的定量关系为后面的实证分析做好准备.然后进一步进行协整分析,并在向量自回归(VAR)框架下通过脉冲响应函数考察变量之间的相互影响路径,最后通过建立误差修正模型(ECM)分析各个变量之间的长期均衡关系和短期波动特征,以量化各变量之间影响程度的大小.全面系统地研究了国债对宏观经济增长的影响程度并做出实证分析,对于深刻认识国债的本质,规避国债的风险,科学合理地制定国债政策有着重要的理论价值和实际意义.     

A Posteriori Suboptimal Error Estimates in Control Problems

For the linear quadratic control problem, a lower bound for the performance index is established by simple methods. Using this bound, two important a posteriori error estimates are obtained, the first one measuring the deviation of the performance index, while the other is for the deviation of the state and control variables from the optimal solution. Continuous-time as well as discrete-time systems described by ordinary differential and difference equations are discussed. A numerical example is given for illustration.     

Short-term booking of air cargo space

This paper proposes a stochastic dynamic programming model for a short-term capacity planning model for air cargo space. Long-term cargo space is usually acquired by freight forwarders or shippers many months ahead on a contract basis, and usually the forecasted demand is unreliable. A re-planning of cargo space is needed when the date draws nearer to the flight departure time. Hence, for a given amount of long-term contract space, the decision for each stage is the quantity of additional space required for the next stage and the decision planning model evaluates the optimal cost policy based on the economic trade-off between the cost of backlogged shipment and the cost of acquiring additional cargo space. Under certain conditions, we show that the return function is convex with respect to the additional space acquired for a given state and the optimal expected cost for the remaining stages is an increasing convex function with respect to the state variables. These two properties can be carried backward recursively and therefore the optimal cost policy can be determined efficiently.     

Modeling and adjoints for continuous systems

Approximate solution of the differential equations of state of continuous systems by various numerical integration schemes is standard practice in trajectory optimization and control work; the resulting truncation error represents the main error in many applications. Suppression of the deleterious effects of this error is of increasing interest as double-precision arithmetic becomes routinely available for roundoff error reduction, especially when high overall accuracy is needed. In numerical optimization of trajectories, the accuracy of partial derivatives is important in a special sense: compatibility of a function and its derivatives. That is, if the partial derivatives of the terminal state with respect to trajectory parameters are accurate representations of the partial derivatives of the terminal state calculated through the integration model, adverse effects on convergence of successive approximation iterations can be avoided. From previous numerical experiments, this is known to be particularly important when conjugate-direction methods are used, as they require unusually accurate first partial derivatives to realize the quadratic convergence theoretically attainable.When the mathematical model of the system consists of differential equations, it is theoretically correct to use differential equations for the adjoint variables (influence functions) as well. However, the actual numerical solution of both state and adjoint variables is obtained by using finite-difference approximations. Truncation errors in the state are inevitable; but, by suitable construction of the adjoint difference equation, it is possible to obtain the compatibility just discussed. The procedure is to recognize that, for numerical purposes, the system model consists of difference equations and directly derive compatible adjoint difference equations. The adjoint variables are then the correct influence functions for the numerically computed state variables, rather than approximate influence functions for the theoretically continuous state variables. The construction of the adjoint system for difference-equation models is straightforward. For example, if the typical integration routine involves fourth-order differences, the adjoint system also involves fourth-order differences. However, the intervals and coefficients for the adjoint system differ from those of the dynamic system. Thus, the compatible adjoint system uses difference equations of the same order in a different, although quite connected, integration routine.This paper was presented at the Second International Conference on Computing Methods in Optimization Problems, San Remo, Italy, 1968. The research reported in this paper was carried out under Contract No. NAS 9-7805 with the NASA Manned Spacecraft Center, Houston, Texas.     

政府支出结构、扭曲性税收及内生贴现因子

在一个无穷期限模型中,假设经济主体具有完全理性,通过将常数贴现因子转换为关于效用水平的内生变量,利用跨期优化方法重新考虑了政府支出结构、扭曲性税收对宏观经济变量的影响.尤其关注这两种变量的长期和短期变化对资本积累路径的影响,理论模型表明,当贴现因子内生化后,政府支出结构和扭曲性税收对宏观经济的影响会更为复杂,尤其体现在生产性支出上.     

A novel car-following inertia gray model and its application in forecasting short-term traffic flow

Real-time and accurate short-term traffic flow prediction results can provide real-time and effective information for traffic information systems. Based on classic car-following models, this paper establishes differential equations according to the traffic state and proposes a car-following inertial gray model based on the information difference of the differential and gray system, in combination with the mechanical characteristics of traffic flow data and the characteristics of an inertial model. Furthermore, analytical methods are used to study the parameter estimation and model solution of the new model, and the important properties, such as the original data, inertia coefficient and simulation accuracy, are studied. The effectiveness of the model is verified in two cases. The performance of the model is better than that of six other prediction models, and the structural design of the new model is more reasonable than that of the existing gray models. Moreover, the new model is applied to short-term traffic flow prediction for three urban roads. The results show that the simulation and prediction effects of the model are better than those of other gray models. In terms of the traffic flow state, an optimal match between short-term traffic flow prediction and the new model is achieved.     

中国人均碳排放影响因素的长期均衡与因果动态关系研究——基于结构突变ARDL-VECM模型的实证分析

为了探讨中国低碳经济的发展路径,运用BP内生结构突变点检验、考虑结构突变的ARDL模型和基于VECM模型的Granger因果关系检验方法,利用我国1985至2014年的相关数据,探讨经济增长、城镇化、技术创新、贸易开放与我国人均碳排放的长期均衡和短期动态关系,以及变量之间的因果关系。研究结果表明,中国人均碳排放与解释变量之间存在长期协整关系。长期来看,经济增长与人均碳排放之间呈倒U型关系,城市化水平的提高可以有效减少人均碳排放,技术创新与人均碳排放显著负相关,而贸易开放会引起环境恶化。短期来看,贸易开放与人均碳排放显著正相关,而其他变量对人均碳排放的影响均不显著。此外,基于VECM模型的Granger因果关系检验证实所有解释变量均为人均碳排放的Granger原因,且经济增长、贸易开放与人均碳排放之间存在双向因果关系。     

A least squares identification algorithm for a state space model with multi-state delays

A parameter estimator is presented for a state space model with time delay based on the given input–output data. The basic idea is to expand the state equations and to eliminate some state variables, and to substitute the state equation into the output equation to obtain the identification model which contains the information vector and parameter vector. A least squares algorithm is developed to estimate the system parameter vectors. Finally, an illustrative example is provided to verify the effectiveness of the proposed algorithm.     

On generating state space equations of a linear constant coefficient system

The details of the linear algebra which must be performed in order to generate state space equations from primitive equations of the linear constant coefficient ordinary differential mathematical model are presented. The applicability of the procedure is not dependent on any modeling philosophy and/or regimen. In addition to generating the state variable representation of the system, the procedure also generates equations which relate all other system internal variables to the system states and the system input variables. The treatment is complete and identifies all the operations which must be done in implementing a digital computer automation of the process. Some useful insights into the effects of ill-posed mathematical models and of modeling errors result from the treatment.The author is indebted to several reviewers and colleagues for valuable suggestions for improvement and for encouragement.