Nonlinear Study And Forecasting In Shanghai And Shenzhen 300 Stock Index Futures

Effective market theory which is one of the classical theories is the cornerstone of modern finance, but the efficient market theory based on linear thinking has been a great challenge with the financial market development and research in depth. Since then, the nonlinear research began to be applied to the study of financial markets by the majority of scholars, and the complex nature of financial markets is caused by the nonlinear characteristics. Stock index futures in China launched in April 16,2010 has played an increasingly important role in financial markets. Therefore, the research on analysis and forecasting of the stock index futures market has important theoretical significance and application value. In this paper, fractal, chaos and wavelet analysis are used in the research of the nonlinear analysis and forecasting methods for the time series of stock index futures prices, which provides an effective methods and tools for the capital market analysis and policy-making.The contents are summarized as follows:The first chapter is introduction which introduces the current market conditions and research situation at home and abroad on stock index futures. In the second chapter, the characteristics and nonlinear characteristics of Shanghai and Shenzhen 300 stock index futures are analyzed. The characteristics of stock index futures, the efficient market theory, fractal market theory are introduced, and the fractal characteristics and nonlinear of stock index futures are researched in depth by fractal R/S analysis and chaos. In the third chapter, the inherent laws and forecast of the trend of stock index futures are researched by wavelet analysis theory. I introduced the wavelet theory and studied the self-similarity and mutation of stock index futures using the wavelet theory and the empirical research, which analyzed and summarized the inherent laws of stock index futures volatility. Meanwhile, wavelet decomposition was used to forecasting the stock index futures trend. In the fourth chapter, study of forecasting of the stock index futures based on chaos theory and wavelet analysis. The theory of chaotic time series were introduced and applied to the forecasting of the stock index futures by empirical research. And the research methods based on wavelet analysis theory and chaotic time series prediction of stock index futures was proposed. The noise of the stock index futures in time sequence was removed by the multi-resolution analysis of wavelet analysis before making a chaotic time series prediction. The empirical results show that chaotic time series prediction based on wavelet denoising is better than the prediction of chaotic time series itself.