A novel LASSO – TLBO – SVR hybrid model for an efficient portfolio construction

In this study a LASSO – TLBO – SVR hybrid model is used for portfolio construction. Relevant economic parameters are determined and used for stock selection. Along with stock selection, weights for the stocks are obtained by solving a portfolio optimization problem using three methods: GRG Nonlinear, Evolutionary method based on Genetic Algorithm, and Equal weight method. The portfolio return in the proposed model is compared with the return of the Indian market portfolio (NSE and BSE). It is observed that the proposed model outperforms the market portfolio.     

拉格朗日中值定理证明中辅助函数的构造

本文应用分析法、几何法、待定系数法,分别构造出满足罗尔定理条件的函数,即拉格朗日中值定理证明中的辅助函数。     

Estimation in Two-Stage Models with Heteroscedasticity

A surprising number of important problems can be cast in the framework of estimating a mean and variance using data arising from a two-stage structure. The first stage is a random sampling of "units" with some quantity of interest associated with the unit. The second stage produces an estimate of that quantity and usually, but not always, an estimated standard error, which may change considerably across units. Heteroscedasticity in the estimates over different units can arise for a number of reasons, including variation associated with the unit and changing sampling effort over units. This paper presents a broad discussion of the problem of making inferences for the population mean and variance associated with the unobserved true values at the first stage of sampling. A careful discussion of the causes of heteroscedasticity is given, followed by an examination of ways in which inferences can be carried out in a manner that is robust to the nature of the within unit heteroscedasticity. Among the conclusions are that under any type of heteroscedasticity, an unbiased estimate of the mean and the variance of the estimated mean can be obtained by using the estimates as if they were true unobserved values from the first stage. The issue of using the mean versus a weighted average which tries to account for the heteroscedasticity is also discussed. An unbiased estimate of the population variance is given and the variance of this estimate and its covariance with the estimated mean is provided under various types of heteroscedasticity. The two-stage setting arises in many contexts including the one-way random effects models with replication, meta-analysis, multi-stage sampling from finite populations and random coefficients models. We will motivate and illustrate the problem with data arising from these various contexts with the goal of providing a unified framework for addressing such problems.     

原始及加入人民币的特别提款权作为外汇储备资产的特性分析

本文使用均值-半方差的方法,在不同条件下构建了中国、日本、英国及欧盟的外汇储备资产的有效性边界。研究表明:将特别提款权(SDR)作为外汇储备资产可以提高资产组合的表现;人民币成为特别提款权组成货币可以增强特别提款权作为外汇储备资产的功能。     

应用于自适应格型RLS滤波器的变阶数算法

提出了一种新的变阶数(或抽头长度)算法,并将之应用于变阶数自适应格型递归最小二乘(RLS)滤波器的阶数更新中,讨论了格型滤波器阶数更新时相关参数的调整方法.新算法以分贝的形式比较短滤波器与长滤波器的时平均平方误差,采用自适应的抽头长度步长,能够在滤波器权值末收敛时同时快速更新滤波器长度与权值,且在不同大小噪声条件下都能收敛到最优阶数.理论分析与不同大小噪声条件下的自适应系统辨以仿真结果验证了新算法的有效性.     

中国哲学与城市规划散论--城市规划的形上思辨

论述了中国哲学与城市规划的关系,提出了自觉运用中国哲学于我国城市规划实践中的观点.     

Mean reversion and the forecasting of country betas: a note

In 1971 and 1975, M. E. Blume found individual equity betas to have a “regression” tendency toward the grand mean of unity. His original results have been widely accepted to the extent that a literature has developed on the application of Bayesian techniques to beta estimation so as to adjust for mean reversion. The more recent literature has focused on risk estimation and the applicability of asset pricing models in the international finance setting, where the focus has been on the aggregate country level risk. Given the increasing popularity of country beta models, an interesting but, as yet, unexplored issue is whether aggregate country betas display mean reversion tendencies similar to that found for individual company betas. The examination of this issue is the central aim of the current paper. In short, this analysis reveals strong evidence of mean reversion of country betas, similar to that documented in the single country setting in the existing literature.     

基于BP神经网络算法的风电功率预测

针对风电功率的预测,从神经网络的训练仿真入手,综合运用BP神经网络、平均绝对误差MAE等多种方法,建立风电功率预测模型,运用Matlab和Excel软件编程,得到了后续7天中时隔5min和15min的风电功率预测趋势和时隔5min样本数据的预测误差水平相对于15min来说降低了6.349%等结果。     

Calendar effects in structural time series models with trend and season

Calendar effects are analysed in the class of structural time series models one of the two main model based approaches in time series decomposition. While Bell and Hillmer (1983) modeled calendar variation in the ARIMA model based approach, we represent structural models in the generalized regression form which allows to apply classical estimation and test procedures. It turns out that the expected high computaional complexity 0(T ³) in the generalized regression model can be reduced to 0(T). As all parameters are estimated by maximizing the likelihood the Likelihood Ratio statistics can be used to test effects of the calendar composition.