基于LINGO优化的灰色模型在旅游需求预测中的应用

提出了一种基于LINGO优化的灰色模型（简称LINGOGM），并将LINGOGM模型运用于桂林市的旅游需求预测。与传统的GM（1，1）模型相比，LINGOGM模型在旅游需求预测中具有较高的预测精度和较广的应用范围。     

The accuracy of long-term earnings forecasts in the electric utility industry

This paper examines the accuracy of various methods of forecasting long-term earnings growth for firms in the electric utility industry. In addition to a number of extrapolative techniques, Value Line analyst forecasts are also evaluated. Value Line analyst forecasts for a five-year time horizon are found to be superior to many of the extrapolative models. Among the extrapolative models examined, implied growth and historical book value per share growth rate models performed best. These results provide strong support for using Value Line growth forecasts in cost of capital estimates for electric utilities in the context of utility rate cases. Value Line forecast errors could be explained by changes in dividend payout ratios, the firm's regulatory environment and bond rating changes.     

区域物流需求预测的LaOR方法

目前回归函数中普遍存在的泛化能力得不到保证的缺点,结合统计学习理论的研究成果,建立了基于最小一乘准则的最优回归模型(LaOR模型)。与以往回归模型相比较,新模型综合考虑了回归误差和置信范围,可望有效地降低回归模型的期望风险。上海市将LaOR应用到物流需求的短期预测中,取得了可以接受的预测效果。     

回归模型异方差性分析

介绍了预测模型的异方差性的概念，产生的原因以及常用的对模型的异方差性的检验方法。并介绍了模型异方差性消除的方法和程序。     

钢筋混凝土板在内爆荷载作用下的反应分析

本文对内爆荷载作用下钢筋混凝土板进行数值模拟,并对不同炸药量和爆炸距离作用下产生的爆炸峰值压力及脉冲压力大小进行数值模拟计算,然后分析板破坏过程及破坏形式,给出安全等级评估,从而为板的防爆设计加固提供一些有益的参考。     

栈桥钢管桩浮冰冲击作用下的有限元分析

本文运用有限元分析软件Midas civil和ANSYS分别建立了栈桥钢管桩的整体及局部有限元模型,分析了在浮冰冲击荷载作用下钢管柱的受力情况,为栈桥检算提供理论依据,同时优化设计方案,保证了栈桥在使用中的安全可靠。     

Housing and the Macroeconomy: Inflation and the Financial Accelerator

Three themes connecting housing and the macroeconomy are discussed. First, evidence is presented for the property market as one of the drivers of U.S. consumer price inflation. Second, key drivers of house prices are explained to account for the remarkable diversity of international experience. Finally, three potential links between housing, credit, and the financial accelerator are discussed. These are the consumption channel, the investment channel, and feedback between bad loans and risk‐spreads via the financial system—and how institutional differences between countries can explain the presence, absence and magnitudes of these linkages.     

海南国内生产总值的统计预测模型

国内生产总值(GDP)是衡量一个国家或地区经济实力的指标。建立了海南建省以来的GDP预测模型,并通过时间序列模型得到自变量的预测年度数据,进而对海南"十一五"与"十二五"期间的国内生产总值进行了预测,为制订经济发展规划提供参考。     

Epistemological foundations for the assessment of risks in banking and finance

This article presents the epistemological and conceptual foundations on which current attempts to model crises and assess financial risks are based. It draws a distinction between two research programs, in Lakatos' sense: on the one hand, crises understood as structural events within a cycle; on the other hand, crises seen as statistical tail events. The methodological, theoretical and practical consequences of such a dichotomy are exposed. A crucial difference lies in the assumptions about change in the causal processes generating economic outcomes, especially asset returns. Furthermore, this article insists on providing conceptual definitions of key terms that have distinct meanings within the two research programs.     

Using diffusion models to forecast market size in emerging markets with applications to the Chinese car market

Marketing managers have to forecast the market size and this forecast guides strategic decisions whether to continue exporting, open new factories or expand existing production operations. Forecasting sales and the market size is a challenging task; even more so in emerging markets where data is limited and the market demand is changeable. This research proposes a novel approach that applies diffusion models using car ownership data to forecast car sales. Car ownership data may be easier to access than sales data in emerging markets but marketing managers are more interested in the sales forecast. Researchers propose using diffusion models to forecast the adoption of new products or products which are new to consumers in a market. This research demonstrates that marketing managers can use diffusion models to predict car sales in China where cars are new products to most consumers in this market. Since the majority of car buyers in China are first time buyers, car manufacturers and retailers must also forecast when the market composition will change. This effectively means predicting when first time car buying will start to slow down and repeat/replacement purchase or second hand car purchase will become more important. To forecast both sales and market composition change, marketing managers must choose a robust model. Managers want insights from models that have been tested robustly especially in less stable market conditions. In this context, this study illustrates the value of using a rolling forecast instead of a fixed horizon approach when comparing and choosing which model to use to forecast both sales and market composition change for the Chinese car market.