本文關(guān)鍵詞： 統(tǒng)計(jì)時(shí)間長(zhǎng)度 股價(jià)波動(dòng) 成交量 相關(guān)性　出處：《貴州財(cái)經(jīng)大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：中國(guó)證券市場(chǎng)經(jīng)歷了二三十年的快速發(fā)展,股票、期貨等金融交易行為逐步規(guī)范化,各項(xiàng)金融操作也向成熟市場(chǎng)化前進(jìn),這是社會(huì)文明的表現(xiàn)。對(duì)于國(guó)家而言,證券市場(chǎng)的發(fā)展極大地推動(dòng)國(guó)民經(jīng)濟(jì)的發(fā)展,對(duì)于中國(guó)老百姓而言,股票已經(jīng)深入尋常百姓的日常生活當(dāng)中,并成為普通大眾重要的投資理財(cái)方式之一。在這種背景下,研究股票技術(shù)分析有極其重要的理論價(jià)值與現(xiàn)實(shí)意義。 采用技術(shù)分析的投資者投資決策買(mǎi)點(diǎn)和賣(mài)點(diǎn)時(shí),主要依據(jù)成交量與價(jià)格之間的關(guān)系,經(jīng)過(guò)長(zhǎng)時(shí)間的驗(yàn)證,量?jī)r(jià)分析成為影響投資者進(jìn)行技術(shù)分析可靠分析方法之一。成交量與價(jià)格都是投資者對(duì)市場(chǎng)信息反應(yīng)的描述,然而,由于信息不對(duì)稱,成交量的價(jià)格對(duì)市場(chǎng)信息反應(yīng)的速度必然有所不同,這將會(huì)造成成交量與價(jià)格波動(dòng)的低相關(guān)性,對(duì)于一定的股價(jià)波動(dòng),異常放大的成交量往往伴隨了隱藏的市場(chǎng)信息。 本文以量?jī)r(jià)關(guān)系作為議題,從不同的時(shí)間長(zhǎng)度中得到的成交量與股價(jià)波動(dòng)的相關(guān)性來(lái)發(fā)現(xiàn)在多長(zhǎng)的時(shí)間長(zhǎng)度內(nèi),更容易出現(xiàn)異常放大的成交量,使用參數(shù)兄來(lái)分辨出異常放大的成交量,并驗(yàn)證這種成交量對(duì)未來(lái)股價(jià)波動(dòng)的解釋作用,本文從大盤(pán)指數(shù)分析、行業(yè)指數(shù)分析和個(gè)股分析三個(gè)方面進(jìn)行了研究,最終得出了使用多長(zhǎng)時(shí)間內(nèi)的成交量和股價(jià)波動(dòng)進(jìn)行量?jī)r(jià)分析可以得到最好的技術(shù)分析效果,并對(duì)如何使用量?jī)r(jià)關(guān)系提出方法和建議。 根據(jù)分析最終得到結(jié)論：第一,對(duì)于不同的指數(shù)和不同類型的股票,在統(tǒng)計(jì)時(shí)間長(zhǎng)度為5分鐘和一個(gè)月時(shí),成交量與股價(jià)波動(dòng)均體現(xiàn)出較高的相關(guān)性,而在統(tǒng)計(jì)時(shí)間長(zhǎng)度為一天,一周時(shí),則體現(xiàn)出較低的相關(guān)性。也就是說(shuō)在一天或者一周中,相對(duì)于一定的股價(jià)波動(dòng)更容易出現(xiàn)過(guò)量放大或者過(guò)量縮小的成交量,其中這種異常放大的成交量對(duì)未來(lái)的股價(jià)波動(dòng)具有較強(qiáng)的預(yù)測(cè)作用。第二,對(duì)于上證指數(shù),深圳成指,上證50等受大盤(pán)股影響較大的大盤(pán)指數(shù),日成交量與周成交量與股價(jià)波動(dòng)的相關(guān)性較低,月成交量則與股價(jià)波動(dòng)具有較高的相關(guān)性,而對(duì)于創(chuàng)業(yè)板,中小板受小盤(pán)股影響較大的大盤(pán)指數(shù),則只有在短期內(nèi)成交量與股價(jià)波動(dòng)具有較高相關(guān)性,在較長(zhǎng)時(shí)間內(nèi)股價(jià)波動(dòng)與成交量的相關(guān)性都較低。第三,對(duì)于不同的行業(yè)指數(shù),指數(shù)波動(dòng)與成交量的相關(guān)性相似。指數(shù)波動(dòng)與成交量相關(guān)性較高,成交量的較少出現(xiàn)異常放大。第四,相對(duì)于小盤(pán)股,大盤(pán)股的日成交量或者周成交量放大后,在未來(lái)短期內(nèi)的更有可能出現(xiàn)股價(jià)運(yùn)動(dòng)趨勢(shì),因此投資者對(duì)更適合對(duì)大盤(pán)股使用成交量來(lái)發(fā)現(xiàn)股票的買(mǎi)點(diǎn)和賣(mài)點(diǎn)的成功概率更高。因此投資者更適合使用日K線與周K線,進(jìn)行技術(shù)分析。當(dāng)其他技術(shù)指標(biāo)獲得反轉(zhuǎn)或者上攻信號(hào)時(shí),日成交量或者周成交量的明顯放大,是對(duì)未來(lái)走勢(shì)的有力支持。
[Abstract]:China's securities market has experienced 20 or 30 years of rapid development, stock, futures and other financial transactions gradually standardized, all financial operations are also moving towards mature market-oriented, this is the performance of social civilization. For the country. The development of the securities market has greatly promoted the development of the national economy. For the Chinese people, the stock market has penetrated into the ordinary people's daily life. Under this background, it is of great theoretical value and practical significance to study the stock technology analysis. When investors use technical analysis to make investment decisions, they are mainly based on the relationship between turnover and price, and have been verified for a long time. Volume price analysis has become one of the reliable analysis methods that affect investors' technical analysis. Both volume and price are the description of investors' response to market information, however, because of information asymmetry. The speed of the price response to the market information will be different, which will lead to the low correlation between the volume and the price fluctuation, for a certain stock price volatility. Abnormal volume amplification often accompanied by hidden market information. In this paper, the relationship between volume and price is considered as the topic, and the correlation between the volume and the stock price fluctuation is found to be more likely to occur in the long period of time. The parameter brother is used to distinguish the abnormal enlarged trading volume, and to verify the effect of this volume on the future stock price volatility. This paper studies from three aspects: large market index analysis, industry index analysis and individual stock analysis. Finally, it is concluded that the best technical analysis effect can be obtained by using the volume price analysis of how long the trading volume and stock price fluctuate, and the methods and suggestions on how to use the price relation are put forward. First, for different indices and different types of stocks, when the statistical time is 5 minutes and a month, the volume and stock price volatility reflect a high correlation. When the statistical time is one day and one week, the correlation is lower. That is to say, it is more likely to overamplify or shrink the trading volume in a day or a week than a certain stock price fluctuation. This abnormal volume of trading has a strong predictive effect on the future volatility of stock prices. Second, for the Shanghai Stock Exchange Index, Shenzhen Cheng Index, Shanghai Stock Exchange 50 and so on by the impact of large-cap stock index. The correlation between daily turnover and weekly turnover and stock price volatility is low, while monthly turnover has a higher correlation with stock price volatility. Only in the short term trading volume and stock price volatility has a high correlation, in a longer period of time, the correlation between stock price volatility and trading volume is lower. Third, for different industry indices. The correlation between index fluctuation and turnover is similar. The correlation between index fluctuation and trading volume is high, and the volume of trading volume is very small. 4th, compared with small-cap stocks, the daily turnover or weekly turnover of large-cap stocks is enlarged. Stock price movements are more likely to occur in the short term. Therefore, investors are more suitable for large-cap stocks to use trading volume to find the stock's buying point and selling point. Therefore, investors are more suitable to use day K line and weekly K line. Technical analysis. When other technical indicators get the signal of reversal or upswing, the obvious amplification of daily turnover or weekly turnover is a strong support for the future trend.
【學(xué)位授予單位】：貴州財(cái)經(jīng)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.51;F224

【引證文獻(xiàn)】

相關(guān)博士學(xué)位論文 前2條

1 方媛;中國(guó)股市波動(dòng)問(wèn)題研究[D];華中科技大學(xué);2010年

2 周觀君;基于量?jī)r(jià)分析的中國(guó)股票市場(chǎng)價(jià)格行為研究[D];首都經(jīng)濟(jì)貿(mào)易大學(xué);2005年

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本文編號(hào)：1447677