Using neural network to forecast stock index option price: a new hybrid GARCH approach

This study aims to apply a new hybrid approach to estimate volatility in neural network option-pricing model. The analytical results also indicate that the new hybrid method can be used to forecast the prices of derivative securities. Owing to combines the grey forecasting model with the GARCH to improve the estimated ability, the empirical evidence shows that the new hybrid GARCH model outperforms the other approaches in the neural network option-pricing model.     

CPFR中的联合预测研究

文章研究了联合计划、预测和补货（CPFR）中的联合预测流程,并建立了相关的预测模型。在建模的过程中,使用了状态空间方程来描述实际市场需求和观测到的市场需求（销售量）,并通过卡尔曼滤波来预测零售商下期的销售量．结合零售商库存策略,预测出零售商下期的订单量。     

安徽省能源需求的组合预测

根据预测理论,结合安徽省历年能耗的数据,在建立能源需求单项预测模型的基础上,建立组合预测模型,对2008～2014年的能源需求量进行预测。结果表明:组合预测模型的精度高于单项预测模型;安徽省能源需求量正以较快的速度在增长。     

Outside the box: using synthetic control methods as a forecasting technique

We introduce synthetic control methods (SCM) as a forecasting technique. Using (i) as economic predictors solely the outcome itself, i.e. lagged values of the dependent variable, and (ii) lagged time series of the outcome to build the donor pool, we let SCM choose and weight appropriate values in order to come up with a sensible forecast of the US GDP growth. This procedure performs competitively viable compared with alternative forecasting methods.     

Forecasting MBT technologies using DEA and LR

First, this paper explores Main Battle Tank (MBT) data set with different statistical methods in order to decide the most appropriate variables as reliable yardsticks in applying technology forecasting (TF) using data envelopment analysis (TFDEA) technique. It then applies TF using DEA method to forecast MBT technologies. This article attempts to predict technology development year of MBT commercialised from 1941 to 1994. This article presents the processes of TFDEA in detail and identifies some issues to search for appropriate input and output variables to forecast MBT technologies. The purpose of this study is to address some issues and identify an appropriate data to predict future trends of MBT technologies when using TFDEA and multiple linear regression tools. Finally, the study provides an understanding of the technological advances being sought in MBT technologies and information for use in making decisions regarding development strategy.     

Taxi,Takeoff and Landing: Behavioural Patterns of Capital Flows to Emerging Markets

This paper analyses volatility, persistence, predictability, correlation, comovement (or contagion risk) and sudden stop (reversibility) of capital flows (foreign direct investment (FDI), foreign portfolio equity investment, long-term and short-term debt flows) using time series econometric techniques for 24 emerging economies over 1970–2014. This is informative on the pattern and relationship between capital inflows, with implications for accommodating macroeconomic policies in countries receiving inflows. The paper also addresses the predictions of conventional theory, that differences are associated with the maturity of the capital (long-term vs. short-term), with the information-based trade-off model of Goldstein and Razin [(2006). An information-based trade off between foreign direct investment and foreign portfolio investment. Journal of International Economics, 70(1), 271–295], that differences are associated with the structure of the capital (equity vs. debt). In line with the latter, equity flows (FDI and portfolio) are less volatile and persistent, more predictable and less susceptible to sudden stops than debt flows. Contrary to conventional theory, short-term flows are not more volatile, but there is evidence that correlations and risks of contagion are strong within all capital flow components.     

Big losses in ecosystem niches: how core firm decisions drive complementary product shakeouts

This study examines shakeouts in the context of business ecosystems. Market turbulence generated by core firm decisions in competing differentiated ecosystems can generate financial losses and exit for complementary niche market firms. I develop hypotheses predicting which niche markets will suffer larger losses and be more susceptible to shakeouts, and how core firm decisions will drive complementor performance and survival. I then apply these hypotheses to brand‐based differentiated ecosystems in the automotive industry, where networks of suppliers, customers, and complementors surround car manufacturers. More specifically, I study the complementary niche market of automotive leasing, where manufacturers sway leasing markets through product change, entry, and subsidization. To test the hypotheses, I use a proprietary dataset of 200,000 individual car leases between 1997–2002 to identify how manufacturer product design and niche market entry drive complementor losses and exit. These data allow a unique opportunity to understand how the strategic choices of core firms can have substantial and often devastating effects on niche markets in their ecosystem. Further, the results suggest how the dynamic capabilities to adapt to core firm behavior might improve performance for certain niche market complementors. Copyright © 2008 John Wiley & Sons, Ltd.     

基于Copula函数特征筛选的电力物资供应商投标价格预测

分析电力物资供应商投标价格特征是招标企业估计投标价格并制定合理采购策略的基础.传统的Spearmen秩相关系数特征筛选方法只单纯考虑了特征的数值排列顺序,不能挖掘特征变量与目标的内在关联关系,会导致预测效果差.本文在电力企业招标价格预测建模中引入Copula函数,通过特征变量与目标变量的联合概率分布来分析变量间的相依关系.首先确定特征变量与目标变量的边缘分布,进行Copula参数估计,选取合适的Copula函数并计算相关系数来筛选供应商投标价格的特征,并以多种预测方法进行预测来验证引入Copula函数后预测精度是否提升.结果表明,引入Copula函数进行特征筛选后,预测精度更高、效果更好.     

长江上游坡耕地降雨径流蓄集利用效果评价

通过建立反映坡面降雨径流调控工程技术措施、拦截季节性降水、补充作物需水高峰期用水效果的综合评价指标体系,利用模糊多因素层次评价数学模型,对坡面降雨径流调控技术及其降雨径流蓄集和利用状况进行评价分析。计算结果表明,在具有季节性干旱缺水的坡耕地灌溉区域,在不同设计代表年份的降雨情况下均表现出良好的降雨径流蓄集利用效果。因此,通过修建雨水蓄集工程,实施坡面径流调控和水系的合理配置是很有必要的,同时也能为长江上游坡耕地整治与坡地高效生态农业的可持续发展提供科学依据和决策支持。