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基于EEMD的上證綜合指數(shù)時間序列的多尺度分析

發(fā)布時間:2018-06-09 11:08

  本文選題:上證綜合指數(shù) + 整體經(jīng)驗?zāi)B(tài)分解 ; 參考:《長春工業(yè)大學(xué)》2014年碩士論文


【摘要】:非線性、非平穩(wěn)信號處理是近年來數(shù)據(jù)分析領(lǐng)域的熱點問題和難點問題。本文系統(tǒng)總結(jié)希爾伯特-黃變換理論,闡述了經(jīng)驗?zāi)B(tài)分解(Empirical Mode Decomposition, EMD)流程,為了有效地解決數(shù)據(jù)模態(tài)混疊現(xiàn)象,構(gòu)建整體經(jīng)驗?zāi)B(tài)分解(Ensemble Empirical Mode Decomposition, EEMD)算法。本文以我國上證綜合指數(shù)為研究對象,利用EEMD方法對其進行波動性和周期性分析。首先,利用EEMD方法分析上證綜合指數(shù),將原始時間序列分解為多個固有模態(tài)函數(shù)和趨勢項,對分解后的固有模態(tài)函數(shù)進行統(tǒng)計分析和分布擬合,得到其分布的特點。其次,針對上證綜合指數(shù)序列中的兩個典型階段,即上漲階段和下跌階段,分別采用EEMD方法進行分析。最后,通過對各階模態(tài)函數(shù)進行波動性和周期性分析,揭示上證綜合指數(shù)在不同尺度上的波動特點,以及典型上漲和下跌時間段的波動周期和波動特點。引入EEMD算法實現(xiàn)上證綜合指數(shù)序列的多尺度分析,將給股票數(shù)據(jù)處理提供一種新的、有效的分析方法,把握股價波動的規(guī)律,具有重要的理論意義和應(yīng)用價值。
[Abstract]:Nonlinear and non-stationary signal processing is a hot and difficult problem in the field of data analysis in recent years. In this paper, the Hilbert-Huang transform theory is systematically summarized, and the empirical Mode decomposition (EMDM) process is expounded. In order to solve the data mode aliasing effectively, the whole empirical Mode decomposition (EEMDM) algorithm is constructed. In this paper, the volatility and periodicity of Shanghai Composite Index are analyzed by EEMD method. Firstly, the composite index of Shanghai Stock Exchange is analyzed by EEMD method, and the original time series is decomposed into several inherent modal functions and trend terms. The statistical analysis and distribution fitting of the decomposed intrinsic modal functions are carried out, and the distribution characteristics of the original time series are obtained. Secondly, the EEMD method is used to analyze the two typical stages of the Shanghai Composite Index sequence, namely, the rising stage and the falling stage. Finally, by analyzing the volatility and periodicity of various modal functions, the volatility characteristics of Shanghai Composite Index on different scales, as well as the fluctuation periods and volatility characteristics of typical rising and falling periods are revealed. The introduction of EEMD algorithm to the multi-scale analysis of Shanghai Composite Index sequence will provide a new and effective analysis method for stock data processing and grasp the law of stock price fluctuation, which has important theoretical significance and application value.
【學(xué)位授予單位】:長春工業(yè)大學(xué)
【學(xué)位級別】:碩士
【學(xué)位授予年份】:2014
【分類號】:F830.9

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