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The interest of both investors and researchers in stock market behaviour forecasting has increased throughout the recent years. Despite the wide number of publications examining this problem, accurately predicting future stock trends and developing business strategies capable of translating good predictions into profits are still great challenges. This is partly due to the nonlinearity and the noise...
This paper presents a new kind of nonlinear combination method to predict the exchange rate. The method possesses several characters as follows: (1) the short, medium and long-term influences are considered comprehensively; (2) the different singular methods are nonlinearly combined according to their characteristics; (3) Some original data is taken as the inputs of network with the forecasted values;...
Inflation forecasts becomes a key input of monetary policy decision. CPI is a measure of inflation, however, an important economic indicator. Based on the monthly CPI data from January 2000 to December 2009, the thesis firstly statistically indentifies the correlation function and the partial correlation function of consumer price index, tests the stationarity of ADF, then uses ARIMA model to test...
In this paper a novel neural network architecture for medium-term time series forecasting is presented. The proposed model, inspired on the Hybrid Complex Neural Network (HCNN) model, takes advantage of information obtained by wavelet decomposition and of the oscillatory abilities of recurrent neural networks (RNN). The prediction accuracy of the proposed architecture is evaluated using 11 economic...
This paper mainly carried out assessment about the "11th Five-Year Plan" early progress regarding structural energy-saving. It analyzed the main problem of the "11th Five-Year Plan" structural energy-saving work, and applied GM(1,1) and other models to carry on the forecast to structural Energy-saving potential in the later period of "11th Five-Year Plan". Based upon...
Forecasting currency exchange rates is an important issue in finance. This topic has received much attention, particularly in econometrics and financial selection of variables that influence forecasts. In this paper, a new forecasting model is constructed: we adopt a Genetic Algorithm (GA) to provide the optimal variables weight and we select the optimal set of variables as the input layer neurons,...
In this paper, a economic data analysis model is been proposed. There are three step in the mode. First, the economics data is decomposed by wavelet analysis. Second, some of the data is combined according to the cycle of the data. At last. The ARIMA model is been used to analysis.
Scientific forecast is of great importance to the economic phenomenon research and economic decision-making. Therefore, the research about economic forecast theory and method is always a hot topic. This paper proposed an algorithm combined with the grey model, least square method and topology model, which can be a new advanced algorithm for forecasting. Using this new algorithm, the paper forecasts...
There are a number of predictive methods available to forecast market changes. Nevertheless, most of these methods require a large amount of historical data and sophisticated input factors to support the forecasting process. To overcome this limitation, grey theory has been developed. The core mathematical basis is the grey differential equation, GM(1,1), which has similar characteristics to the differential...
Accompany by the rapid changes of the world, the funds on technology programs invested by the country are increasing year by year with the growing demand. This paper introduces the theory of continuous ant colony optimization algorithms and support vector machine to analyze, predicts the financial situation of enterprises and sets up the financial forecast model CACO-SVM. Financial datas of some companies...
This paper proposes an improved Grey-Markov forecasting dynamic method based on unbiased grey system theory and fuzzy classification. The new forecasting method is named unbiased Grey-fuzzy-Markov Chain method, which can take advantage of the prediction power of conventional Grey-Markov forecasting method and at the same time eliminate grey bias and improve anti-jamming performance. As an example,...
The non-existence of triangular arbitrage in an efficient foreign exchange markets is widely believed. In this paper, we deploy a forecasting model to predict foreign exchange rates and apply the triangular arbitrage model to evaluate the possibility of an arbitrage opportunity. Surprisingly, we substantiate the existence of triangular arbitrage opportunities in the exchange rate forecasting market...
In This work the procedures of an estimation of forecasting models adequacy on foreign exchange market are given. A forecasting model was built by ARIMA method. Forecasting model to the complex diagnostic verification through the analysis of autocorrelation functions, hollow-charge peridogram of residual errors and confidence intervals of forecasting values are suggested. The problem of adequacy estimation...
Based on the statistical data during the period from 2003 to 2008 released by Henan Statistical Bureau in China, this paper focused on forecasting the amount of the scientists and technicians of Henan province in China, using GM (1, 1) model and regression model. The result of this empirical study is that the grey prediction theory can fit the scientists and technicians amount development precisely...
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