最小平均VaR套期保值比率计算模型及实证研究

针对传统的套期保值模型只考虑最小化套期保值组合在到期日的价格风险,而且没有充分利用资产历史价格样本数据所提供的收益率信息的特点,本文提出了考虑套期保值期内不同期限价格风险的最小平均VaR套期保值比率计算模型。基于我国外汇市场及股票市场数据,本文对最小平均VaR套期保值模型进行了实证分析,并与常用的最小方差及最小VaR套期保值模型进行了对比,得出了最小平均VaR模型在套期保值过程中的效果要优于其他两种模型,能更有效地降低投资者提前终止套期保值可能面临额外风险的结论。     

定额系统计算方法及与EAM系统接口程序的实现

文章简述了进口生产储备定额管理系统的运行数据和预测结果、订货量计算公式、月平均消耗量计算公式及与EAM系统接口程序的实现方法。     

土性参数的相关距离研究

在自然过程中形成的土,其物理力学性质指标具有自相关的特性,这种特性可用相关距离来衡量。对于岩土工程参数的统计计算应考虑相关距离的影响,这样能更真实、准确的反映地基土的特性。以西安市地铁一、二号线勘察的静力触探数据,根据Vanmarcke提出的土层概率模型、土性相关距离的定义以及方差折减函数Γ(2h)的基本性质,采用递推空间法计算得出各地基土层的相关距离。     

Hip‐hop and Urban Studies

How can urban studies research engage fruitfully with hip‐hop? This contribution responds to the essays by David Beer and Martin Lamotte on ‘street music’, urban ethnography and ghettoized communities. It discusses how a social science engagement with hip‐hop texts might differ from cultural studies approaches, and how the study of hip‐hop culture can contribute to social movements studies. The essay argues that academics can utilize this form of ‘urban’ culture in various ways when undertaking urban research, teaching urban studies and engaging a broader public in academic research.     

中国服务进出口与汇率波动的相关性分析--基于1982-2011年的数据分析

以1982-2011年的相关指标的数据为基础,通过Stata12、Excel软件,把我国服务进出口量分别与中国、美国的国内生产总值和每年平均汇率进行多元回归,建立var模型,实证分析发现：中国历年服务出口额和历年平均汇率、中国及美国国内生产总值有显著的正相关。中国服务进口额和历年平均汇率有显著的负相关,服务进口额和中国及美国国内生产总值有显著的正相关,但是滞后一到三阶的平均汇率对我国服务进出口均没有显著影响。我国GDP对本国服务进出口的影响比美国GDP对此的影响更大。     

2010年4月银行间市场运行报告

2010年4月份,银行间外汇、货币、债券、利率和汇率衍生品市场整体运行平稳,主要特点是：货币市场利率以小幅波动为主,短端Shibor各期限品种普遍上扬,中长端Shibor走势平稳;银行间国债指数大幅上升;人民币对美元汇率月末中间价与上月末持平,掉期价格显示人民币对美元升值预期有所增强。     

交易量大幅增长,人民币持续走强——2008年2月银行间外汇市场运行简报

2008年2月,银行间外汇即期和衍生品市场运行平稳。与2007同期相比,2月人民币外汇远期交易量增长14.01%;人民币外汇掉期交易量增长73.37%;外币对交易量下降7.04%;外币拆借交易量上升216.96%。2008年2月,人民币兑美元和港币继续保持升值趋势,兑日元贬值,兑欧元贬值,兑英镑升值。与2008年1月末中间价比,2月末人民币兑美元汇率中间价累计升值1.11%。与2005年汇改当日中间价比,2月末人民币累计升值16.48%。     

分布未知情形下基于Burr近似的VSSI EWMA图多目标优化设计

为了提高过程质量监控效率和降低过程质量控制成本,针对过程质量特性分布未知情形,利用Burr分布近似未知分布,研究可变样本容量和抽样间隔(VSSI)的指数加权移动平均(EWMA)控制图的统计经济多目标优化设计问题。首先,建立基于Burr近似的未知分布VSSI EWMA图,采用平均产品长度、单位产品质量成本分别作为统计和经济指标,构造该图的统计经济多目标优化设计模型 。之后,采用NSGA-Ⅱ算法对模型进行算例求解和灵敏度分析。最后,将该方案与已有几种EWMA图设计方案比较。结果表明,在总体分布未知时,该方案在统计监控效率和过程监控成本两方面都要优于VSSI EWMA图的单一性设计,以及EWMA图多目标优化设计。     

Group heterogeneity and the economic effect of farmer organisation participation: Empirical evidence from Taiwan

We explore the effects of different farmer organisations on smallholder farmers' economic performance. The average treatment effect of switching between different farmer organisations is examined. In addition, based on the premise that a higher level of social capital is accumulated through participation in multiple farmer organisations, we also investigate how the economic consequences of farmer organisation membership vary with the intensity of participation. Our conceptual model explicitly includes social capital to provide a micro-foundation and a theoretical justification for the linkage between farmer organisation participation and the economic outcome. This indicates that participating in different types of farmer organisations is beneficial for farm households only when the returns from social capital investment outweigh the time cost of participation. Our empirical results suggest that membership of farmer organisations that are more homogeneous in terms of member specialty and similarity in production and marketing activities results in a significant increase in farm sales revenue and net returns. This result supports the view that technological proximity accentuates knowledge spillovers within the farmer organisations, and thus leads to better economic outcomes. In line with the prediction of the theoretical model, the average treatment effect of participation is found to increase with the number of organisations that farmers belong to. Moreover, results from the quantile regression provide empirical evidence supporting increasing returns to social capital accumulated through participation in several farmer organisations.     

Multivariate time series analysis of traffic congestion measures in urban areas as they relate to socioeconomic indicators

Traffic congestion has significant adverse implications for the environment and economy. Many state and local transportation agencies have implemented traffic congestion management practices to alleviate the negative implications of urban traffic. One of the major drawbacks of traffic congestion management practices is that they do not account for socio-demographic and economic factors, which have a significant impact on traffic congestion. Understanding the influence of these factors is very crucial because they can help to communicate the system's performance management and target setting. Only a few studies analyzed the relationship between traffic conditions (e.g., traffic demand and vehicular traveling speed) with a limited number of socio-economic factors. Moreover, most of the existing models ignore the temporal and spatial autocorrelations of traffic congestion, which may significantly limit their reliability and effectiveness. This study is developed with the purpose of identifying the most relevant external factors that affect traffic congestion performance measures. To conduct the research, we have used three urban congestion performance measures collected from 51 metropolitan areas across the U.S. over a four-year period, 2013–2016: travel time index, planning time index, and congested hours. We have used multivariate time series models to account for the complex inter-relationships among the performance measures and socioeconomic factors to identify the most influential factors affecting system performance. We have finally developed predictive models to estimate the traffic congestion measures using these factors. The results of rigorous modeling show that the factors influencing the traffic congestion measures are monthly average daily traffic (MADT), the number of employed, rental vacancy rate, building permits, fuel price index, and Economic Conditions Index (ECI). The prediction models indicated that the effects of these factors are statistically significant and could be used to forecast future trends in three performance measures accurately.