本文選題：價(jià)格偏差　切入點(diǎn)：異質(zhì)信念　出處：《湖南大學(xué)》2012年碩士論文

【摘要】：現(xiàn)代行為金融學(xué)認(rèn)為，由于市場(chǎng)存在多種有限理性且持有互異先驗(yàn)信念的投資者，從而形成市場(chǎng)價(jià)格的偏差。本文討論了在異質(zhì)信念理論下，市場(chǎng)價(jià)格與價(jià)格偏差的方程形式。在此基礎(chǔ)上，本文引入適應(yīng)度函數(shù)來(lái)衡量任一種信念的收益能力，引入選擇強(qiáng)度來(lái)衡量投資者在不同信念之間轉(zhuǎn)換的速度，通過(guò)這兩個(gè)變量的引入，建立了投資者占比與價(jià)格偏差的聯(lián)動(dòng)方程。該方程表明，一種信念的適應(yīng)度函數(shù)越高，則其對(duì)應(yīng)的投資者市場(chǎng)占比也就越大；如果這種信念是基準(zhǔn)價(jià)值信念，則持有該信念的投資者有助于穩(wěn)定市場(chǎng)，價(jià)格偏差將得到修復(fù)；如果這種信念是趨勢(shì)追逐類信念，則持有該信念的投資者會(huì)擴(kuò)大市場(chǎng)的不穩(wěn)定與波動(dòng)，價(jià)格偏差會(huì)被放大。數(shù)值模擬的結(jié)果顯示，在由多種信念組合而成的市場(chǎng)中，價(jià)格偏差的運(yùn)動(dòng)軌跡較為復(fù)雜，基準(zhǔn)價(jià)值投資者占比、趨勢(shì)投資者占比、投資者的信念強(qiáng)度、市場(chǎng)選擇強(qiáng)度都會(huì)影響價(jià)格偏差的修復(fù)路徑和修復(fù)速度，甚至在某些參數(shù)取值下，價(jià)格偏差無(wú)法得到修復(fù)。最后，本文以基準(zhǔn)價(jià)值信念和趨勢(shì)追逐信念組合作為中國(guó)股票市場(chǎng)投資者所使用的代表性信念組合，利用遺傳算法，，考察了異質(zhì)信念定價(jià)理論對(duì)上證A股指數(shù)、深圳A股指數(shù)、深圳成分指數(shù)與深圳中小板指數(shù)等在2002-2011年內(nèi)市場(chǎng)波動(dòng)與市場(chǎng)偏差的解釋力.結(jié)果顯示：對(duì)于四個(gè)指數(shù)，異質(zhì)信念模型對(duì)數(shù)據(jù)的擬合優(yōu)度顯著高于同質(zhì)信念模型；市場(chǎng)的波動(dòng)與平均市場(chǎng)情緒之間存在正向聯(lián)系。深圳成分指數(shù)的趨勢(shì)投資信念強(qiáng)度顯著低于其他指數(shù)，這意味著與其他指數(shù)相比，深圳成分指數(shù)的波動(dòng)和偏差程度是這四個(gè)樣本中最小的。此外，四個(gè)指數(shù)的風(fēng)險(xiǎn)厭惡系數(shù)均值約為3，這意味著中國(guó)股票市場(chǎng)的投資者呈現(xiàn)風(fēng)險(xiǎn)厭惡�？偟脕�(lái)說(shuō)，異質(zhì)信念模型刻畫了投資者占比與市場(chǎng)價(jià)格偏差的聯(lián)動(dòng)過(guò)程，對(duì)中國(guó)股票市場(chǎng)的波動(dòng)有較好的解釋力。
[Abstract]:Modern behavioral finance holds that there are many investors with limited rationality and different transcendental beliefs in the market, which leads to the deviation of market price. In this paper, we discuss the theory of heterogeneous belief. On this basis, the fitness function is introduced to measure the earning ability of any belief, and the selection intensity is introduced to measure the speed of investors' conversion between different beliefs. Through the introduction of these two variables, the linkage equation of investor's share and price deviation is established. The equation shows that the higher the fitness function of a belief, the greater the proportion of investors' market. If this belief is a benchmark value belief, the investors who hold it will help stabilize the market and the price bias will be fixed; if it is a trend-chasing belief, The investors holding this belief will expand the instability and volatility of the market, and the price deviation will be magnified. The numerical simulation results show that in a market composed of multiple beliefs, the trajectory of the price deviation is more complex. The proportion of benchmark value investors, trend investors, the strength of investors' belief, the strength of market selection will affect the repair path and repair speed of the price deviation, even if some parameters are selected, the price deviation will not be fixed. In this paper, the benchmark value belief and trend chasing belief combination are used as representative belief combinations for Chinese stock market investors. By using genetic algorithm, we investigate the heterogeneity belief pricing theory for Shanghai A-share index and Shenzhen A-share index. The explanatory power of Shenzhen component index and Shenzhen small and medium-sized board index to explain market fluctuation and market deviation in 2002-2011. The results show that the heterogeneity belief model has significantly higher goodness of fit than homogeneous belief model for the four indices. There is a positive correlation between market volatility and average market sentiment. The Shenzhen component index has significantly lower trend investment beliefs than other indices, which means that compared with other indices, The volatility and deviation of the Shenzhen component index is the smallest of the four samples. In addition, the average risk aversion coefficient of the four indices is about 3, which means that investors in the Chinese stock market have a risk aversion. The heterogeneous belief model depicts the linkage process between investor share and market price deviation, which can explain the fluctuation of Chinese stock market.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類號(hào)】：F832.51;F224

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 吳世農(nóng),許年行,蔡海洪,陳衛(wèi)剛;股市泡沫的生成機(jī)理和度量[J];財(cái)經(jīng)科學(xué);2002年04期

2 黃興,張維;中國(guó)股市泡沫的檢驗(yàn)[J];石家莊經(jīng)濟(jì)學(xué)院學(xué)報(bào);2002年03期

3 張維;張永杰;;異質(zhì)信念、賣空限制與風(fēng)險(xiǎn)資產(chǎn)價(jià)格[J];管理科學(xué)學(xué)報(bào);2006年04期

4 張維;趙帥特;;認(rèn)知偏差、異質(zhì)期望與資產(chǎn)定價(jià)[J];管理科學(xué)學(xué)報(bào);2010年01期

5 李佳;王曉;;中國(guó)股票市場(chǎng)有效性的實(shí)證研究——基于方差比的檢驗(yàn)方法[J];經(jīng)濟(jì)經(jīng)緯;2010年01期

6 周愛民;股市泡沫及其檢驗(yàn)方法[J];經(jīng)濟(jì)科學(xué);1998年05期

7 俞喬;市場(chǎng)有效、周期異常與股價(jià)波動(dòng)——對(duì)上海、深圳股票市場(chǎng)的實(shí)證分析[J];經(jīng)濟(jì)研究;1994年09期

8 賈權(quán),陳章武;中國(guó)股市有效性的實(shí)證分析[J];金融研究;2003年07期

9 劉晉華;姚益龍;;基于異質(zhì)信念演化的資產(chǎn)市場(chǎng)波動(dòng)研究[J];南方經(jīng)濟(jì);2011年04期

10 陳占鋒;上海股票市場(chǎng)A股泡沫問題:市盈率測(cè)量與綜合解釋[J];世界經(jīng)濟(jì);2002年07期

相關(guān)博士學(xué)位論文 前1條

1 張群;中國(guó)股票市場(chǎng)噪聲交易行為研究[D];中國(guó)科學(xué)技術(shù)大學(xué);2009年

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