The evolution of world trade from 1995 to 2014: A network approach

This paper employs network analysis to study world trade from 1995 to 2014. We focus on the main connective features of the world trade network (WTN) and their dynamics. Results suggest that countries’ efforts to attain the benefits of trade have resulted in an intertwined network that is increasingly dense, reciprocal, and clustered. However, these features do not correspond to a linear aggregation of the characteristics of its constituents (trade sectors). Trade linkages are distributed homogeneously among countries, but their intensity (i.e. their value) is highly concentrated in a small set of countries. The main connective features of the WTN were not affected by the 2007–2008 international financial crisis. However, we find that the crisis marks a turning point in the evolution of the WTN from a two-group (led by the US and Germany) to a three-group (led by the US, Germany, and China) hierarchical structure.     

新疆林木种苗产业的市场结构、企业行为与市场绩效

市场结构和行为对市场绩效的影响机制是解释产业发展的重要前因。通过实地调研,分析新疆林木种苗产业组织市场结构-市场行为-市场绩效内在规律。结果表明,新疆林木种苗产业市场结构属于垄断竞争型市场结构;相当数量企业生产能力效率较低;市场种苗产业的生产能力利用率不高,市场绩效低下。基于结论,提出从优化市场结构,调整市场行为两个方面进行产业政策调整,进而提高市场绩效。     

一种加权聚类划分决策树算法

针对斜划分决策树算法普遍存在时间效率低、部分算法仅能应用于二分类问题，提出了一种基于加权距离的聚类决策树算法。通过Relief-F算法为预测属性计算权重，并将权重用于树结点中数据的聚类过程，使用分簇结果对结点进行多路划分，得到可直接用于多分类问题的决策树。理论分析和实验结果表明，该算法与经典轴平行决策树相比，拥有更好的泛化能力以及相近的算法时间复杂度，与大部分斜决策树相比，在付出更少计算代价的前提下，获得了近似的正确率以及模型简洁度。     

环境约束下中国省域旅游经济效率及其影响因素的空间计量分析

采用Super-SBM方法将环境因素作为非期望产出纳入旅游经济效率测算框架,结合空间计量经济方法分析2005—2016年我国省域旅游经济效率空间关联性及影响因素溢出效应,结果显示:环境约束下,我国省域旅游经济具有一定的空间集聚趋势,呈现出"东南热、西北冷"的分布特征,尚未实现网状结构均衡发展;我国省际旅游经济效率间存在显著的空间溢出作用。对于环境约束下旅游经济效率发展来说,人均GDP、技术创新、市场化、环境规制均有显著的正向作用,路网密度作用不显著,外国直接投资(FDI)有显著的负向作用。影响因素的溢出效应来看,市场化、经济增长、技术创新具有显著的积极间接溢出效应,但环境规制带来了显著的负向间接溢出效应,FDI与路网密度的间接溢出效应不显著。     

Uncovering the global network of economic policy uncertainty

This study uncovers the static and dynamic network of economic policy uncertainty (EPU) across 17 developed and emerging economies. We build a centrality network using the minimal spanning tree (MST) as well as a dependency network using partial correlations. Results from the MST show that EPU exhibits some degree of geographical connections with EPUs in seven countries in the sample directly linked to the US EPU. Evidence from dynamic time-varying MST reveals that the nature and dominance of the EPU network have changed significantly over time. Further, the US and German EPUs dominate a close-knit global policy uncertainty network with the highest net (To and From) transmitter of information flow in the dependency network. Greece, Russia, and Brazil are the top three net receivers of information in the global network of EPU. The policy implication of these results relates to the renewed and ongoing international debate on policy coordination.     

气候障碍因子对城市绿化适生树种选择的 影响——以上海世博公园为例

通过对上海近30年的气候因子汇总分析，结合对上 海世博公园主要绿化树种生长状况调查和年度生物量计算，通 过典型相关性分析发现，极端高低温、强风和暴雨等5个气候 因子对树木的生长产生了不同程度的影响，有些因子严重阻碍 了树木的正常生长，成为障碍因子。经过10年的绿化实践验 证，上海世博公园对骨干树种的选择，以乡土树种为主，群落 结构较为稳定，且气候障碍因子对乡土树种的影响较小。在引 种外来树种时，采用气候相似植物区系法，结合植物耐寒、耐 热带图，把种源地划分为2个气候带和3个植物区系，并确定了 最南引种线，成功引种了红花槭等20种观花色叶乔木树种。     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

智慧BIM乔木模型：从设计图纸到施工 现场

现有的BIM应用软件提供的乔木模型多为RPC或高 精度3D模型等3D CAD类型。这些模型着重于表达美感或进 行展示，无法反映根系情况。虽然可能包含一定附加属性，但 表达乔木生长和空间需求的功能有限。因而，冲突检查、工序 调度等BIM的优势功能无从应用。风景园林实践领域已就此问 题开始构建自己的模型库，但能够准确反映现状树木真实尺寸 体量，以及现状树木和规划树木未来空间需求的模型仍未广泛 出现。提出一种基于树冠、树干和根系构型与生长功能的实体/ 网面封装建模方法构建BIM乔木模型。模型形态通过一组参数 调整，并根据树龄和反映环境限制因子的值来反映其变化。所 包含的数据和参数数量随后期设计阶段所需的LoD(详细层级) 及专业实践的具体要求而增加。该模型可以与提供本地区内外 苗木商品信息的植物数据库连接使用。     

二叉树期权定价模式评估林业碳汇项目的价值

基于黑龙江省林业局和中国林业统计年鉴的数据,运用修正的Faustmann模型和二叉树期权定价方法分析黑龙江省黑河造林林区的碳汇价值及该项目的经济可行性。研究结果表明:经营成本负向影响项目的最终价值;碳汇价格和木材价格正向影响项目的最终价值;初始价值正向影响项目的最终价值;黑龙江省黑河造林林区项目具有较高的经济效益和生态效益。因此,相关部门应建立完善的碳汇交易市场,实施激励措施和制定林地产权制度。     

基于量子三叉树的量子Black-Scholes期权定价

将量子概率引入到期权定价是最近几年一个新的研究趋势,也称为量子金融.为了期权定价更方便,文章建立了量子三叉树模型,同时利用量子概率建立了连续量子Black-Scholes(B-S)模型。实例应用和Matlab期权敏感性分析都验证了量子B-S优于经典B-S,从而为连续期权定价提供量子决策的途径。