基于小波分析的多期择时能力模型及实证研究

本文利用小波变换对基金收益率及其方差进行多尺度分解,并将小波分析引入资本资产定价模型,计算小波多尺度β。进一步地将小波分析引入到传统的H-M模型中,利用小波函数的多尺度与不同的投资期限对应,对模型进行多期改造,从而获得择时能力的多期评价模型。以我国经济背景为依托,选择14只开放式基金进行实证研究,结果表明,利用小波分析可以有效的对基金的择时能力进行多期评价。     

深市收益特征及价量关系实证研究

本文分析了深市日收益率序列和波动率序列的每周不同天效应和记忆性。认为,深市日收益率序列不存在每周不同天效应,但存在一至二星期的记忆性;波动率序列则存在每周不同天效应和持续性;同时,交易量对波动率具有很好的解释作用。     

基于时间序列分析的北京地区PM2.5浓度研究

基于中国环境监测总站公布的实时空气质量监测数据, 利用时间序列模型对PM2.5指标的数据进行了平稳性、纯随机性检验, 同时进行了模型阶数、未知参数估计以及模型显著性检验与优化. 最终在此基础上建立了指标预测的数学模型, 并对未来三天的PM2.5浓度值进行预测. 进一步地, 基于向量自回归(VAR)模型, 对北京市万寿西宫站PM2.5数据进行相关性分析, 研究空气中污染物O_{2}、NO_{2}、CO、O_{3}、PM10与PM2.5的动态影响关系. 研究发现当天的PM2.5浓度会受到前几天PM2.5、PM10、O_{3}、SO_{2}等污染物浓度的影响,其中PM10对PM2.5的影响最为明显且持续时间最长, O_{3}、SO_{2}对PM2.5浓度的影响在二、三期最为明显.     

定量分析读者群的变化趋势

运用时间序列分析和回归分析的方法 ,定量分析了读者群的变化趋势 ,并讨论了变化趋势的成因     

时序全局主成分分析在经济发展动态描绘中的应用

本文利用时序全局主成分分析简明扼要的对我国 195 2～ 1982年的经济发展历程作了动态描绘。结果表明 ,动态轨迹与客观实际能很好的吻合 ,为促进经济进一步的快速发展提供了参考依据     

基于小波分析方法的市场环境对新股发行回报率影响的实证研究

本文采用小波变换的方法,扩展了以往文献中对市场环境因素机械化的处理。我们发现股票上市前期市场环境的变化对于其初始回报率有着显著的影响,并且不同时间尺度上以及股票市场发展的不同时段中,这种变动的影响都是不同的。     

基于BOX-Jenkins方法的青南高原降水量时间序列分析建模与预测

应用基于Box-Jenkins方法的时间序列分析技术,对青南高原的四个典型地区1961-2005年降水量序列进行ARMA建模分析:验证了四地区年降水量序列的时间序列特性,研究并选择了这些序列的最佳ARMA模型,本文也通过模型对未来降水量进行了预测.模型实证分析的结果表明:在青藏高原降水量时间序列分析建模与预测方面,Box-Jenkins方法及其模型是一种精度较高且切实有效的方法模型.     

Mean-risk analysis of risk aversion and wealth effects on optimal portfolios with multiple investment opportunities

In this paper, we first define risk in an axiomatic way and a class of utility functions suitable for the so-called mean-risk analysis. Then, we show that, in a portfolio selection problem with multiple risky investments, an investor who is more risk averse in the Arrow-Pratt sense prefers less risk, in the sense of this paper, with less mean return, and an investor who displays increasing (decreasing) relative risk aversion becomes more conservative (aggressive) as the initial capital increases. The risk aversion effect for diversification on optimal portfolios is also discussed.     

基于WEGN模型对我国主要城市气温的模拟和预测

本文对我国10个主要城市气温指标建立了天气发生器模型,用Fourier分析和时间序列的方法进行建模,用统计模拟的方法分别生成了一年的气温数据,来对当地的气温指标进行了预测。在此基础上,我们对模型进行了改进,通过增加模拟次数,建立了全年日均气温的点估计和区间估计.最后,以三个实例验证了改进模型。     

基于ARIMA的油田A类物资市场价格预测

本文研究了油田A类物资的市场价格预测。采用时间序列方法中的ARIMA模型,结合油田物资历史价格数据,分析并提出了一套针对油田A类物资的市场价格预测模式。该模式包括两个模块:样本集模块和ARIMA模块。样本集模块的主要功能是样本集的输入和实时更新;ARIMA模块包括了价格预测模型的拟合、检验、预测、评价、动态反馈和调整等主要环节。在该模式的指导下,以大庆油田A类采购物资中的小螺纹钢(20-HRB335)(天津、石家庄和沈阳3个产地)为例,对2011年各月的市场价格进行了模拟预测,预测的平均相对误差分别控制在2.13%,1.64%和1.82%,该结果得到了用户的认可。该预测模式的运用对大庆油田物资集团制定合理的物资采购方案提供了依据。结论部分对该预测模式的意义及存在问题进行了分析,并给出改进建议。     

Some aspects of extreme value statistics under serial dependence

On the occasion of Laurens de Haan’s 70th birthday, we discuss two aspects of the statistical inference on the extreme value behavior of time series with a particular emphasis on his important contributions. First, the performance of a direct marginal tail analysis is compared with that of a model-based approach using an analysis of residuals. Second, the importance of the extremal index as a measure of the serial extremal dependence is discussed by the example of solutions of a stochastic recurrence equation.      

A linearization‐based approach of homotopy analysis method for non‐linear time‐fractional parabolic PDEs

In this paper, a novel approach, namely, the linearization‐based approach of homotopy analysis method, to analytically treat non‐linear time‐fractional PDEs is proposed. The presented approach suggests a new optimized structure of the homotopy series solution based on a linear approximation of the non‐linear problem. A comparative study between the proposed approach and standard homotopy analysis approach is illustrated by solving two examples involving non‐linear time‐fractional parabolic PDEs. The performed numerical simulations demonstrate that the linearization‐based approach reduces the computational complexity and improves the performance of the homotopy analysis method.     

我国人口时间序列拟合模型的比较与选择

通过对我国1990年至2007年共18年的人口数据进行实证分析,运用时间序列的三个不同模型,对我国人口的变化规律进行了拟合研究;并给出了反映各个模型拟合精度的AIC值和SBC值;最后,通过对所建模型的比较分析,对拟合模型的选择提出了相关建议.     

The analysis of evolutionary algorithms on sorting and shortest paths problems

The analysis of evolutionary algorithms is up to now limited to special classes of functions and fitness landscapes. E.g., it is not possible to characterize the set of TSP instances (or another NP-hard combinatorial optimization problem) which are solved by a generic evolutionary algorithm (EA) in an expected time bounded by some given polynomial. As a first step from artificial functions to typical problems from combinatorial optimization, we analyze simple EAs on well-known problems, namely sorting and shortest paths. Although it cannot be expected that EAs outperform the well-known problem specific algorithms on these simple problems, it is interesting to analyze how EAs work on these problems. The following results are obtained:– Sorting is the maximization of sortedness which is measured by one of several well-known measures of presortedness. The different measures of presortedness lead to fitness functions of quite different difficulty for EAs.– Shortest paths problems are hard for all types of EA, if they are considered as single-objective optimization problems, whereas they are easy as multi-objective optimization problems.     

Adaptive synchronization of new fractional‐order chaotic systems with fractional adaption laws based on risk analysis

In this paper, a new fractional‐order chaotic system and an adaptive synchronization of fractional‐order chaotic system are proposed. Parameters adaption laws are obtained to design adaptive controllers using Lyapunov stability theory of fractional‐order system. Finally, reliability of designed controllers and risk analysis of adaptive synchronization problem are formulated and, risk of using the proposed controllers in presences of external disturbances are demonstrated. Also, risk of controllers are reduced using an optimizing method. Numerical examples are used to verify the performance of the proposed controllers.     

Convergence analysis of the projective scaling algorithm based on a long-step homogeneous affine scaling algorithm

In this paper we give a new convergence analysis of a projective scaling algorithm. We consider a long-step affine scaling algorithm applied to a homogeneous linear programming problem obtained from the original linear programming problem. This algorithm takes a fixed fraction λ≤2/3 of the way towards the boundary of the nonnegative orthant at each iteration. The iteration sequence for the original problem is obtained by pulling back the homogeneous iterates onto the original feasible region with a conical projection, which generates the same search direction as the original projective scaling algorithm at each iterate. The recent convergence results for the long-step affine scaling algorithm by the authors are applied to this algorithm to obtain some convergence results on the projective scaling algorithm. Specifically, we will show (i) polynomiality of the algorithm with complexities of O(nL) and O(n ² L) iterations for λ<2/3 and λ=2/3, respectively; (ii) global covnergence of the algorithm when the optimal face is unbounded; (iii) convergence of the primal iterates to a relative interior point of the optimal face; (iv) convergence of the dual estimates to the analytic center of the dual optimal face; and (v) convergence of the reduction rate of the objective function value to 1−λ.     

Error and stability analysis of numerical solution for the time fractional nonlinear Schrödinger equation on scattered data of general‐shaped domains

In present work, a kind of spectral meshless radial point interpolation (SMRPI) technique is applied to the time fractional nonlinear Schrödinger equation in regular and irregular domains. The applied approach is based on erudite combination of meshless methods and spectral collocation techniques. The point interpolation method with the help of radial basis functions is used to construct shape functions which play as basis functions in the frame of SMRPI. It is proved the scheme is unconditionally stable with respect to the time variable in and also convergent by the order of convergence , . In the current work, the thin plate spline are used as the basis functions and to eliminate the nonlinearity, a simple predictor‐corrector (P‐C) scheme is performed. It is shown that the SMRPI solution, as a complex function, is suitable one for the time fractional nonlinear Schrödinger equation. The results of numerical experiments are compared to analytical solutions to confirm the reliable treatment of these stable solutions. © 2016 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq 33: 1043–1069, 2017