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We studied empirically the relations among the CHIBOR, CPI, and PPI with a vector error correction model which is available through various kinds of statistics tests. There is at least a cointegration relation among CHIBOR, CPI, and PPI. Negative rate periods of actual CHIBOR are much more than positive rate periods' based on the cointegrating equation curve. Although the CPI and PPI affect the CHIBOR,...
The price of crude oil is tied to major economic activities in all nations of the world, as a change in the price of crude oil invariably affects the cost of other goods and services. This has made the prediction of crude oil price a top priority for researchers and scientists alike. In this paper we present an intelligent system that predicts the price of crude oil. This system is based on Support...
Gross Domestic Product (GDP) is a benchmark for economic production conditions of a country. Estimates of economic growth in the coming year in a country has important roles, among others as a benchmark in determining business plans for business entities, and the basis for devising government fiscal policy. Artificial Neural Network (ANN) has been increasingly recognized as a good forecasting tool...
The establishment financial crisis early warning system has the very vital significance to national economy's construction, the financial crisis is a complex non-linear problem, the present model is based on the linear method, but the neural network is suitable to the processing non-linear problem. This paper improves the BP algorithm with the simulation annealing algorithm, effectively overcomes...
We propose a new approach for analyzing the Japanese government bond (JGB) market using text-mining technology. First, we extracted the feature vectors of the monthly reports from the Bank of Japan (BOJ). Then, the trends in the JGB market were estimated by a regression analysis using the feature vectors. As a result of comparison with support vector regression and other methods, the proposal method...
In this paper, we consider fuzzy variable weight combining forecasting which based on optimal combining forecasting and integrate those two modeling methods. Studies show that: optimal combining forecasting combines forecasting methods in a period of time and makes forecast through fixing the weight of forecasting methods that in the combination. But it does not consider that the weight will vary...
The ARMA forecasting model of time-series have established by using Liaoning province per capita GDP data from 1978 to 2008 In this paper. The economics increasing for the period of “the twelfth five years plan” has been forecasted and analyzed by using this model. the conclusions will provide with the help for Liaoning economics further development.
The value of forecast lies in the prophet of future, and having an important impact on decision-making, Therefore, from the relevant of taxation and economic angle, using analytical methods integrating qualitative and quantitative analysis, based on macroeconomic indicators data of Heilongjiang Province since 1999, through the building of combined forecast model, It is going to forecast revenue organized...
A verification model of coal price (VEC) is established by using cointegration analysis method in this article, and an empirical study is carried on the corresponding statistics from the year 1985 to 2008. It shows that the main factors affecting coal prices are the output value of industry, GNP, retail price index, coal cost and coal supply. Considering the factors, the proposed verification model...
Accurate forecasting of some economic indicators such as GDP is very useful. Aiming at the problem of modeling and forecasting of the nonlinear and complex economic system, an improved least square support machine model is proposed in this paper. A multi-scale chaotic search algorithm combined with GA is proposed for the optimum selection of model parameters. Time series data of the indicator to be...
The combined forecasting and the way of improving such forecasting methodology through optimized combination and recursion is the focus of this paper; the GMDH is applied to select variables relevant to economic forecasting models before establishing a single forecasting model such as regression model and neural network model; and the final step is to establish a combined forecasting model through...
This paper presents a neuro-based approach for Iran annual gasoline demand forecasting by several socio-economic indicators. In order to analyze the influence of economic and social indicators on the gasoline demand, the gross domestic product (GDP), the population and the total number of vehicles are selected. This approach is structured as a multi-level artificial neural network (ANN) based on supervised...
Financial crisis in 2008 has uncovered the failure of financial risk management, while calculating and fighting back financial risks has been a widespread concern. This paper picks up financial data from 1997 to 2006 as sample data for empirical analysis, uses the methods of factor analysis and extracts three factors representing the risk of economic and financial environment, the risk of foreign...
Macro-economic system is a multi-factor, multi-level, multi-aim typical grey system possessed of indefinite. It's running process is a grey dynamic one composed of many relations of many complex structures and interlaced functions. By using the grey systematic theory model, this paper studies two major problems in China's macro-economic system during the reform and opening up. Firstly, it obtains...
During the last three decades since the implementation of the Open Door policy, the tourism industry in Hubei Province has experienced rapid development with the great support and emphasis from government. The year of 2009 is the final year to implement the ??Eleventh Five-Year Plan?? and also the most critical year for government to increase 4 trillion yuan investment in infrastructure to expand...
Based on the theory of complex system brittleness, this paper focuses on analyzing the causes of financial system's brittleness and holds the idea that the outbreak of brittleness is the root cause of financial crisis. By analyzing the financial brittleness potential function model and studying the brittleness critical points on which catastrophe of the financial system was triggered in quantitative...
The port plays an irreplaceable role both in the development of national economy and regional economy at present. Port throughput is an important basis for the construction of port. Grey forecast theory could reveal features of the development and changes in the throughput of the port. So it is an effective tool in research the port throughput .This article conducts the research to the throughput...
In this paper, we propose a vector input neural network model. The architecture of this network is composed by two parts: single vector immutiply and mix (de-mix) matrix process. The model can be described as a high dimension neural network operator. Simplify this model bring to a high dimension array as the kernel of the network. The high dimension neural network is usable in many fields especially...
The economic system, especially the macroeconomic system, is a complex system with nonlinear, time-varying and coupling characteristics. Aiming at the macroeconomic modeling and forecasting problem, a support vector machine method is proposed in this paper. The modeling method of least square support vector machine is mathematically analyzed first, and then an improved multi-scale chaotic optimization...
The regression analysis forecast is one quantitative analysis method in the commonly used economical forecast, it is in the observation and analysis of economy development history and in the present situation foundation, according to certain way to establish the mathematical model which reflected its relation, then will calculate and forecast the change of dependent variable according to the change...
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