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Financial Time Series Analysis Based on Wavelet Method

Author: LiuJingTao
Tutor: WangShaoPing
School: Huazhong University of Science and Technology
Course: Quantitative Economics
Keywords: Wavelet Time series Data fitting Singular point Forecast
CLC: F830
Type: Master's thesis
Year: 2009
Downloads: 151
Quote: 0
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Abstract


This paper first explains the purpose and significance of the wavelet and financial time series , the basic theory of financial time series model and wavelet method are reviewed , and wavelet Research in the field of financial time series analysis . Second, on January 18, 2008 - April 10 293 Shanghai Composite Index closing price data with the ARIMA model data fitting, regression analysis using the wavelet method using MATLAB software , confirmed the wavelet method for time series regression analysis, we can get better results . Regression analysis , the singular points of the data series using the wavelet method to detect and detected singular point and the actual political and economic policies combined effect of the impact of various policies on the stock market . In addition, the article also ARIMA model and ARIMA model based on wavelet method data for short-term forecasting , and compared with the real stock index data to prove the effectiveness of the wavelet method in the short-term time series prediction . The innovation of the article there are two main points : First, the regression results of the wavelet method compared to the ARIMA model , which estimated the parameters of said sequence with lags correlation wavelet coefficients obtained by the wavelet method indicates projection values ??of the sequence at each resolution , the contrast between reference to help analyze serial correlation ; wavelet method is to predict the sequence , combined with the ARIMA models , to thereby obtain the prediction results are significantly better than the simple with ARIMA model predictions .

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CLC: > Economic > Fiscal, monetary > Finance, banking > Finance, banking theory
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