本文選題：股票板塊　切入點：相關性　出處：《重慶大學》2012年碩士論文　論文類型：學位論文

【摘要】：目前，人們的金融意識的日益增強，引起越來越多的投資者對股票投資的青睞。因此，對股票市場的分析和預測的研究就越有其必要性，研究者們也一直致力于利用各種方法對某支股票、某股票指數(shù)或不同板塊股票的走勢的預測研究。雖然股票的波動可能為投資者們帶來不確定的收益，可由于其影響的因素較多，使得投資者們難以并且也不可能完全掌握股票確切的漲跌規(guī)律。但若能估計股票的基本漲跌情況，一定程度上也可以給投資者一些建議。對板塊內的所有股票數(shù)據(jù)間的研究，有利于在了解板塊整體的漲跌情況以及板塊內是否存有漲勢情況異于其他的股票后，為投資者對該板塊的后期發(fā)展的分析提供一些參考信息。因此，有關估計板塊股票漲跌趨勢的研究具有一定的價值。 投資者一直都希望能夠掌握變化莫測的股市的漲跌規(guī)律，從而出現(xiàn)了很多技術分析方法以及股票預測方法，其中技術分析方法包含主觀成分較多，不同的研究者的結論可能會有一定的出入。股票預測方法主要有數(shù)學模型和無模型兩類。傳統(tǒng)的關于股票數(shù)據(jù)分析預測的研究，主要是側重對單支股票某些股票的研究，通過指定的模型對數(shù)據(jù)做實證分析。在建立數(shù)學模型時，主要選取適當?shù)淖兞浚员ＷC做實證分析預測時有一定的可靠性和準確性，但是建立數(shù)學模型時要檢驗各個變量的顯著性以及考慮變量的合適性，從而計算量比較大，并不具有直觀性。 本文的研究內容是結合圖像處理方法對股票數(shù)據(jù)進行分析。首先將收集到的某板塊股票數(shù)據(jù)做歸一化處理，，再形成灰度圖，圖像的豎直方向表示板塊中的不同股票，而水平方向表示處理后的股票不同日期的收盤價格數(shù)據(jù)。由于各支股票間的相關性強弱將影響圖像在豎直方向上的連貫性和光滑性，因此需對該板塊內的股票重新排列。投資者主要關注股票的大致走勢，忽略股票間那些小的波動，這些小的波動可視為噪聲。在分析由股票板塊數(shù)據(jù)形成的灰度圖時，噪聲將影響圖像的清晰度。文章中結合股票數(shù)據(jù)圖像的特點，將均值濾波法、中值濾波法和自適應維納（Wiener）濾波法分別對圖像進行豎直方向上去噪。將實驗結果進行對比，同時結合處理后的股票數(shù)據(jù)圖像對該板塊的漲勢進行了分析，進而能得出該板塊是否具有明顯的板塊效應。最后，對去噪后的圖像分別進行水平方向和豎直方向的邊緣提取。提取的豎直方向邊緣主要是反映了該股票板塊在某時刻的漲跌幅度的極大值或極小值；而水平方向的邊緣主要反映了該板塊內某支股票漲勢的奇異性。提取邊緣所用的方法主要是利用小波變換，找到數(shù)據(jù)中的極值，從而找到對應方向上的邊緣。結合這些邊緣所處的位置間隔分析該板塊的大致漲跌周期。與既往的方法相比，本文從二維的角度來分析股票數(shù)據(jù)且能夠較直觀的反映該板塊股票的整體漲跌趨勢。
[Abstract]:At present, with the increasing of people's financial consciousness, more and more investors prefer to invest in stocks. Therefore, it is necessary to study the analysis and prediction of stock market. Researchers have also been using a variety of methods to predict the movements of a particular stock, a stock index, or a different sector, although volatility in stocks can bring uncertain returns to investors. However, because of its many factors, it makes it difficult and impossible for investors to fully grasp the exact rise and fall rules of the stock. But if we can estimate the basic rise and fall of the stock, To a certain extent, some suggestions can also be given to investors. The study of all the stock data in the plate is helpful in understanding the overall rise and fall of the plate and whether there is a rise in the plate that is different from that of other stocks. This paper provides some reference information for investors to analyze the late development of the plate. Therefore, the research on estimating the trend of stock price rise and fall of the plate is of certain value. Investors have always hoped to be able to master the fluctuating rules of the stock market. As a result, there have been many technical analysis methods and stock forecasting methods, among which the technical analysis methods contain more subjective elements. The conclusions of different researchers may be different. There are two main methods of stock prediction: mathematical model and no model. The traditional research on stock data analysis and prediction mainly focuses on the research of some stocks in a single stock. When establishing the mathematical model, the appropriate variables are selected to ensure the reliability and accuracy of the empirical analysis and prediction. But it is necessary to test the significance of each variable and the appropriateness of considering the variable when establishing the mathematical model so that the calculation is large and not intuitive. The research content of this paper is to analyze the stock data with image processing method. Firstly, the stock data collected from a certain plate is normalized, and then a gray map is formed, and the vertical direction of the image represents different stocks in the block. The horizontal direction represents the closing price data of the processed stocks on different dates. Because the correlation between the stocks will affect the coherence and smoothness of the image in the vertical direction, Investors focus on the general trend of stocks, ignoring the small fluctuations between stocks, which can be regarded as noise. When analyzing grayscale maps formed by stock plate data, The noise will affect the sharpness of the image. In this paper, mean filter, median filter and adaptive Wiener filter are used to de-noise the image in vertical direction according to the characteristics of stock data image, and the experimental results are compared. At the same time, combined with the processed stock data image, we analyze the rise of the plate, and then we can find out whether the plate has obvious plate effect. Finally, The edge of the image after denoising is extracted in horizontal direction and vertical direction respectively. The extracted vertical edge mainly reflects the maximum or minimum value of the stock plate's rise and fall at a certain time. The edge of the horizontal direction mainly reflects the singularity of a stock rise in the plate. The method to extract the edge is to use wavelet transform to find the extreme value in the data. In order to find the corresponding edge in the direction. Combined with the position interval of these edges to analyze the roughly rising and falling cycles of the plate. Compared with the previous methods, This paper analyzes the stock data from a two-dimensional perspective and can directly reflect the overall trend of the stock market.
【學位授予單位】：重慶大學
【學位級別】：碩士
【學位授予年份】：2012
【分類號】：F224;F830.91

【參考文獻】

相關期刊論文 前10條

1 杜偉錦;何桃富;;我國證券市場的板塊聯(lián)動效應及模糊聚類分析[J];商業(yè)研究;2005年22期

2 劉娜;鄭小洋;李為平;;基于小波分析的經濟數(shù)據(jù)預測[J];重慶工學院學報(自然科學版);2009年11期

3 王強;;基于馬氏鏈的股票價格預測模型[J];江蘇技術師范學院學報(自然科學版);2008年02期

4 楊永;趙玉珍;;一種圖像邊緣保持的去噪平滑算法[J];大慶石油學院學報;2008年05期

5 韋艷華,張世英;金融市場的相關性分析——Copula-GARCH模型及其應用[J];系統(tǒng)工程;2004年04期

6 張開華;周文罡;張振;鄭孝娟;;一種改進的C-V主動輪廓模型[J];光電工程;2008年12期

7 李萌萌;張宇;;中國股票市場“周內效應”的實證分析[J];北方經貿;2009年06期

8 尹越安;;基于RBF神經網(wǎng)絡的股市預測研究[J];硅谷;2008年14期

9 張磊;;中國股市板塊輪動現(xiàn)象簡析[J];經營管理者;2010年07期

10 平麗;;圖像平滑處理方法的比較研究[J];信息技術;2010年01期

相關碩士學位論文 前5條

1 王英華;基于C-V模型的工業(yè)CT三維圖像曲面面積與內腔體積測量算法研究[D];重慶大學;2011年

2 榮伏梅;基于斜變換的小波設計及其應用[D];華中科技大學;2007年

3 劉慧;湖北省工業(yè)行業(yè)資本配置效率研究[D];華中科技大學;2007年

4 趙潔;基于自適應最優(yōu)化小波變換算法的焊縫缺陷檢測[D];重慶大學;2008年

5 楊冰梅;基于圖像處理的鐵路道口視頻監(jiān)控系統(tǒng)算法設計[D];西南交通大學;2008年

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