政府投资工程总承包项目设计优化认定与收益归属研究

工程总承包模式以设计与施工的高度融合,日益在建筑业受到青睐。但由于政府投资项目中存在有关结余资金上缴国库等规定,容易导致政府投资工程总承包项目下设计优化产生的成果是进行分成或作为结余资金上缴界定不清。鉴于此,本文通过政策文件,并结合政府投资项目特点,分析政府投资工程总承包项目设计优化的情形认定以及在不同结算依据和合同计价方式下设计优化收益归属的界定,为有效激励总承包单位积极进行设计优化奠定基础。     

航班计划优化研究概述

从航班计划优化的不同时间阶段分析,可以将航班计划优化分为航班计划静态编排优化、基于航班延误预测的航班计划动态反馈优化和基于机场协同决策(A-CDM)的航班计划动态调整角度三类;进而从航班时刻、机型指派、航班频率等编制环节分析了航班计划静态编排优化;随后利用延误波及预测与数据挖掘预测的优化方法分析了基于航班延误预测的航班计划动态反馈优化的相关研究。最后,根据航班计划优化复杂性分析,给出了航班计划优化的发展趋势和未来研究方向。     

Linear programing models for portfolio optimization using a benchmark

We consider the problem of constructing a perturbed portfolio by utilizing a benchmark portfolio. We propose two computationally efficient portfolio optimization models, the mean-absolute deviation risk and the Dantzig-type, which can be solved using linear programing. These portfolio models push the existing benchmark toward the efficient frontier through sparse and stable asset selection. We implement these models on two benchmarks, a market index and the equally-weighted portfolio. We carry out an extensive out-of-sample analysis with 11 empirical datasets and simulated data. The proposed portfolios outperform the benchmark portfolio in various performance measures, including the mean return and Sharpe ratio.     

海南岛休闲农业布局现状的实证分析

[目的]全面分析海南岛休闲农业布局现状,为海南岛休闲农业科学合理规划和均衡协调发展提供决策参考。[方法]文章利用海南岛259家休闲农业企业的地理数据,采用比较、缓冲、密度分析工具,从数量、类型、密度、距离衰减方面实证分析海南岛休闲农业的布局特征,并提出相应的优化对策。[结果](1)海南岛东部、中部和西部休闲农业数量分布比重分别为51%、29%和20%,其中国家级示范点数量分布比重分别为83%、17%和0%;(2)休闲农业主要类型有休闲农庄、观光农园、市民农园和农家乐,除休闲农庄在东部、中部、西部分布较均匀外,其他类型分布较不均衡;(3)距离市县中心越远,休闲农业分布密度越小,95%的休闲农业分布在距离市县中心30km以内,距离市县中心10~15km是休闲农业的高峰集聚区;(4)海南岛休闲农业已在海口、保亭、三亚、澄迈、琼中、琼海、定安、儋州形成8个高度集聚带。[结论]海南岛休闲农业无论在数量、类型和密度上都是东部地区最多,中部次之,西部最少。应积极推进具有农业发展优势的地区,因地制宜拓展产业休闲功能;休闲农业产品类型单一的地区,深度挖掘特色资源和文化内涵;加强休闲农业点与旅游景区、生活服务中心之间的跨区域联系,形成和谐发展的有机旅游整体,使休闲农业真正成为农业转型、农民增收的引擎。     

Portfolio optimization based on GARCH-EVT-Copula forecasting models

This study uses GARCH-EVT-copula and ARMA-GARCH-EVT-copula models to perform out-of-sample forecasts and simulate one-day-ahead returns for ten stock indexes. We construct optimal portfolios based on the global minimum variance (GMV), minimum conditional value-at-risk (Min-CVaR) and certainty equivalence tangency (CET) criteria, and model the dependence structure between stock market returns by employing elliptical (Student-$t$ and Gaussian) and Archimedean (Clayton, Frank and Gumbel) copulas. We analyze the performances of 288 risk modeling portfolio strategies using out-of-sample back-testing. Our main finding is that the CET portfolio, based on ARMA-GARCH-EVT-copula forecasts, outperforms the benchmark portfolio based on historical returns. The regression analyses show that GARCH-EVT forecasting models, which use Gaussian or Student-$t$ copulas, are best at reducing the portfolio risk.     

基于运行规划的能源综合服务系统能效管理研究

以浙江电网企业转型现代能源综合服务的具体战略与发展规划为研究背景，针对能源综合服务系统的运行规划目标，开展基于运行规划的能源综合服务系统能效管理研究。从系统工程的视角出发，以能源流为纽带，基于多尺度能源系统建模方法，构建了能源综合服务系统模型，并结合系统综合能效，采用粒子群优化算法来优化系统各设备单元的运行策略，以实现基于运行规划的最优能效管理。通过能源综合服务系统模型计算表明，大规模清洁能源和可再生能源的接入，可以明显提高系统综合能效；随着区域用户总冷量和/或总热量需求占总电力需求的比值增大，系统最优综合能效逐渐增大；与使用内燃机、燃气轮机及汽轮机为原动机的热电联产系统相比，使用燃料电池为原动机的热电联产系统可以使能源综合服务系统综合能效更优。     

改进高阶容积粒子滤波的系统状态估计算法

传统粒子滤波（PF）直接采用状态转移先验分布作为重要性密度函数来近似后验概率密度函数，使得后验概率密度函数未包含量测信息。针对此问题，提出了一种改进高阶容积粒子滤波(CPF)的系统状态估计算法。算法采用七阶正交容积卡尔曼滤波（7th-CQKF）对PF的粒子进行传递，使得先验分布更新阶段融入最新量测信息；通过7th-CQKF设计重要性密度函数，提高对状态后验概率密度的逼近程度；通过反比例函数计算粒子权重，突出大噪声粒子与小噪声粒子权重差别，提高粒子有效性。仿真结果表明，改进高阶容积粒子滤波的估计精度高于容积粒子滤波（CPF）。     

Tracing VARDI coefficients: a proposal

ABSTRACT

We propose a new approach for tracing the so-called ‘value-added-(re)distribution-important coefficients’ (in short the VARDI coefficients) in a world input–output model. From the perspective of a selected group of economies, VARDI coefficients may be defined as those elements in world input–output matrix in the case of which a small change in their levels leads to the maximization of a share of this group of economies in value added in global value chains. Due to the rapid development of the World Input Output Database, this approach may be easily applied in empirical research to different groups of countries and sectors in world IO models. In an illustrative empirical case study, we use the new approach in order to answer a question regarding what the main directions of the future macroeconomic policy of the U.S. could be in order to ensure the maximization of the country’s share in global value added.     

Diversified behavioral portfolio as an alternative to Modern Portfolio Theory

The traditional mean–variance approach has been complemented by alternative theories that use risk measures different from standard deviation of returns or involve additional distributional features of returns like skewness and kurtosis. We propose a portfolio choice model that combines different distributional characteristics of the returns in the decision-making making process, considering preferences of investors which are modeled as non-statistical uncertainties of investors using fuzzy theory. We use 20 stocks of the S&P500 from January 2013 to December 2017. We assess the obtained portfolios’ performance, and the diversified behavioral portfolios outperform than the mean–variance portfolio. This methodological proposal can be seen as a strong managerial tool to make investment portfolio decisions.     

Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?

Nonlinear, symmetric, and asymmetric dependence characteristics in energy equity sectors matter to portfolio investors and risk managers because of the risks and diversification opportunities they entail. Specifically, nonlinear dependence dynamics between assets are harder to predict, monitor, and manage, and can make investment positions go wrong unexpectedly. In this paper, we investigate whether the dependence dynamics of US and Canadian large-capitalized energy equity portfolios are nonlinear, symmetric, or asymmetric. We draw our results by implementing a robust copula approach based on time-varying parameter copulas and vine copula methods. Both time varying parameter and vine-copula methods indicate that the Canadian energy sector portfolio is driven by nonlinear negative tail asymmetric dependence during the global financial crisis and when the full sample period is employed. On the other hand, it displays nonlinear symmetric dependence during the oil price crisis, implying the need for close monitoring and rebalancing and a more continuous assessment of long investment positions. The US energy sector portfolio is driven by positive tail asymmetric dependence, and by symmetric dependence dynamics during crisis and non-crisis periods.