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Stock index forecasting is an important issue for investors and financial researchers as the movements of stock indices are nonlinear and subject to multiple factors. In this paper, we try to forecast the movements of Shanghai Composite Index using Generalized Autoregressive Condition Heteroskedasticity model. In order to increase accuracy, we introduced data mining technique and carried out forecast...
ARIMA model is widely-range used in forecasting analysis area. The paper establishes an ARIMA model on the employment information of computer industry from 2002 to 2007 in China, and using the model, gives a prediction of situation in 2008. The study will be an exploration for subsequent researches on employment situation forecasting, or other related work.
This paper, taking the Shanghai Stock Exchange (SSE) Composite Index as the sample, constructs ARCH models under the assumptions of normal residuals and non-normal residuals and compares the forecast performances of volatility of normal and non-normal ARCH models and the performance of VaR measure to demonstrate the effects of the distribution assumptions on GARCH model's forecasting ability and risk...
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