作者机构：
[Xiao Yi] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.;[Xiao Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.;[Liu John] City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.;[Wang Shouyang] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China.
通讯机构：
[Liu John] C;City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.
会议名称：
1st International Conference on Forecasting Economic and Financial Systems (FEFS) / 5th International Workshop on Singular Spectrum Analysis and its Applications (SSA)
会议时间：
MAY 17-20, 2012
会议地点：
Beijing, PEOPLES R CHINA
会议主办单位：
[Xiao Yi] Cent China Normal Univ, Sch Informat Management, Wuhan 430079, Peoples R China.^[Xiao Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.^[Liu John] City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.^[Wang Shouyang] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China.
摘要：
The financial market volatility forecasting is regarded as a challenging task because of irregularity, high fluctuation, and noise. In this study, a multiscale ensemble forecasting model is proposed. The original financial series are decomposed firstly different scale components (i.e., approximation and details) using the maximum overlap discrete wavelet transform (MODWT). The approximation is predicted by a hybrid forecasting model that combines autoregressive integrated moving average (ARIMA) with feedforward neural network (FNN). ARIMA model is used to generate a linear forecast, and then FNN is developed as a tool for nonlinear pattern recognition to correct the estimation error in ARIMA forecast. Moreover, details are predicted by Elman neural networks. Three weekly exchange rates data are collected to establish and validate the forecasting model. Empirical results demonstrate consistent better performance of the proposed approach.
作者机构：
[Zhang, Tingting; Wang, Weijun; Liu, Kai; Cao, Wenjun] School of Information Management, Central China Normal University, Wuhan, 430079, China;[Zhang, Tingting; Wang, Weijun; Liu, Kai; Cao, Wenjun] Key Laboratory of Adolescent Cyber psychology and Behavior, Ministry of Education, Central China Normal University, Wuhan, 430079, China
通讯机构：
School of Information Management, Central China Normal University, Wuhan, China
作者机构：
[Liu, Kai; Fang, Lu; Liu, Qiping; Wang, Yuzhu; Bao, Liqian; Wang, Weijun] School of Information Management, Central China Normal University, Wuhan, China;[Liu, Kai; Fang, Lu; Liu, Qiping; Wang, Yuzhu; Bao, Liqian; Wang, Weijun] Key Laboratory of Adolescent Cyber Psychology and Behavior, Ministry of Education, Central China Normal University, Wuhan, China
通讯机构：
School of Information Management, Central China Normal University, Wuhan, China
期刊：
International Journal of Business and Economics Research,2014年3(1):15-28 ISSN：2328-7543
作者机构：
[Nuran Ally Mwasha] School of Economics & Business Administration, Central China Normal University, Wuhan, China;[Zabibu Kweka] College of Information Management, Central China Normal University, Wuhan, China
摘要：
Tanzania is the most promising current and the destination market for the world trade due to its copious resources and strategic location. It is well known in the region as the trade hub as it provides the influential and suitable trade solutions and investments. The aspiration of this paper is to analyse the Revealed Comparative Advantage (RCA) for the topmost export sectors and commodities in Tanzania from 2009 to 2012 by inspecting and evaluating its potency and competence in the world market compared to exports from other countries. Balassa’s index of Comparative advantage (RCA) was utilized to demonstrate the competitive sectors and commodities comparative advantage together with export data from UN com-trade and International Trade Centre (ITC). The outcomes show that Tanzania has significantly strong comparative advantages in sectors of traditional cash crops such as coffee, tea and spices and commodities found in mineral resources as the leading export sector and commodities for the period of four years with RCA greater than one. However, many sectors demonstrated lower RCA compared to individual commodities and the export products have been waning every year, the situation that needs the government to initiate the immediate measures to overcome such problem.
期刊：
Environment, Energy and Sustainable Development - Proceedings of the 2013 International Conference on Frontier of Energy and Environment Engineering, ICFEEE 2013,2014年2:1167-1171
作者机构：
[Xiong, Hui-Xiang; Deng, Min] School of Information Management, Central China Normal University, Wuhan, China;[Guo, Si-Yuan] Economic and Management School, Wuhan University, Wuhan, China
