Long Memory of Financial Time Series and Hidden Markov Models with Time‐Varying Parameters

Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time‐varying behavior have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time varying. It is shown that a two‐state Gaussian hidden Markov model with time‐varying parameters is able to reproduce the long memory of squared daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time‐varying behavior of the parameters also leads to improved one‐step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations. Copyright © 2016 John Wiley & Sons, Ltd.     

船舶运动与受扰Kalman估计精度的统计分析

考察船舶水动力参数在标称值附近按均匀分布发生随机变化时,船舶纵向运动姿态及受扰Kalman估计的统计性能.针对某船,在5级海情,18节航速及45度航向常规工况下,当船舶水动力系数按均匀分布发生士10%、±20%随机变化时,给出船舶姿态及受扰Kalman估计精度的概率建模方法及应用.仿真结果表明,当水动力系数出现摄动时,估计精度服从对数正态分布,平均估计精度与未出现摄动时相比无显著变化.     

抽油机井系统效率极限值的仿真研究

以油井供产协调方程为基础,建立了抽油机井动液面、产液量与抽汲参数之间关系的仿真模型,改进了以抽油杆柱动态仿真为基础的抽油机井系统效率仿真模型,并建立了基于抽汲参数优化设计的系统效率极限值仿真模型.分析了油藏参数、油井参数、设备类型与抽汲参数对系统效率的影响.仿真结果表明:系统效率随油井产能的增加而增加;含水率与气油比对系统效率有显著影响,气油比越大、含水率越低,系统效率越低;抽汲参数组合对系统效率有显著影响.对于低气油比、高含水、高产液量的油井,在优化设计抽汲参数条件下,抽油机井系统效率极限值可以达到50%,甚至超过60%.目前现场实际测试中所出现的50%以上的高系统效率是有科学依据的.     

Robust model predictive control of continuous uncertain systems*

The authors concern robust model predictive control for linear continuous systems with polytopic uncertainties and input constraints. At each sampling time, a piecewise constant control sequence is obtained by solving a set of linear matrix inequalities. The sufficient conditions on the existence of the model predictive control are given, and the robust stability of the closed-loop systems is guaranteed. A simulation example illustrates the efficiency of the proposed method.     

THE SELF-STABLE REGION APPROACH FOR SECOND ORDER SYSTEMS

1.IntroductionThecolltrolproblemofnonlinearuncertainsystemshasbeenextensivelyresearchedformanyyears.Manymethodshavebeenproposedandsomeprogresshasbeenmade.[1]poiedsoutthatsomesecondordersystemshaveaninherelltpropertythatthereexistscertainregioninwhichalltrajectoriesofthesystemremaininginitaftercertaintimeTwillconvergetotheorigin.Basedonthisproperty,anewapproachhajsbeenputforwardtoconstructacolltinuousfeedbacklawsuchthatallsystem'strajectoriesmovetowardtheregionandeventuallyremaininit.In[2,3],a…     

随机和认知混合不确定系统的全局灵敏度分析方法

为计算具有随机不确定性和认知不确定性的混合不确定系统灵敏度,提出一种基于证据理论和条件概率理论的全局灵敏度分析方法.用证据理论对认知不确定性变量进行表征,并提出两种基于证据理论的随机采样方法,包括一次随机抽样法和二次随机抽样法.运用条件概率理论,提出存在认知不确定性条件下混合不确定系统的Sobol'全局灵敏度指标,经过理论推导给出一阶灵敏度及总灵敏度的计算公式,并设置单循环的拟蒙特卡罗方法实现灵敏度的近似数值计算.开发了灵敏度分析程序,并给出了典型应用实例.实例表明,新方法的分析结果正确,计算工作量可控.     

基于灰色关联评估的通用量化评测系统

利用灰色关联评估理论 ,提出了“通用量化评测系统”这一新概念 ,为此 ,提出了两个定理和一个推论 ,并进行了证明推导.     

综采工作面参数系统多维灰色状态模型

针对综采工作面影响因素多、系统复杂的特点,深入分析了综采工作面输入、输出参数系统。以综采工作面统计资料为基础,应用模糊数学理论、灰色关联分析方法和层次分析权重确定方法对众多输入参数进行了量化处理和综合,并进一步应用灰色建模理论,建立了综采工作面产量和效率两项输出参数与输入类参数的灰色状态模型-GM（0,4）模型。经验证,该模型具有一定的精度,对煤矿生产具有指导性作用。这为综采工作面参数系统研究提供了一条新方法。     

EVA塑料发泡倍率的影响规律实验

采用田口实验设计方法,选取模具温度、模压时间、注射压力和模压压力进行正交实验,分析工艺参数对EVA(乙烯-醋酸乙烯酯共聚物)发泡倍率的影响.结果表明,模具温度对发泡倍率的影响较为显著,模压时间次之,注射压力与模压压力的影响较小.随着模具温度的升高,发泡倍率逐渐增大,最终趋于稳定值,随着模压时间的增加,发泡倍率也逐渐最大...     

Coordinating production and recycling decisions with stochastic demand and return

In this paper, the joint production and recycling problem is investigated for a hybrid manufacturing and remanufacturing system where brand-new products are produced in the manufacturing plant and recycled products are remanufactured into as-new products in the remanufacturing facility. Both the brand-new products and remanufactured products are used to satisfy customer demands. Returns of used products that are recycled from customers are assumed to be stochastic and nonlinearly price-dependent. A mathematical model is proposed to maximize the overall profit of the system through simultaneously optimizing the production and recycling decisions, subject to two capacity constraints — the manufacturing capacity and the remanufacturing capacity. Based on Lagrangian relaxation method, subgradient algorithm and heuristic algorithm, a solution approach is developed to solve the problem. A representative example is presented to illustrate the system, and managerial analysis indicates that the uncertainties in demand and return have much influence on the production and recycling policy. In addition, twenty randomly produced examples are solved, and computational results show that the solution approach can obtain very good solutions for all examples in reasonable time.