基于前景理論的收益率分布特征研究
發(fā)布時(shí)間：2018-08-26 06:59
【摘要】：金融資產(chǎn)的收益率一直是投資者最為關(guān)注的信息之一，它與投資者的切身利益息息相關(guān)。因此作為金融市場(chǎng)上的可觀測(cè)變量之一的收益率分布成為了眾多學(xué)者們的重點(diǎn)研究對(duì)象。充分了解收益率分布的特征和規(guī)律也有助于廣大投資者合理的做出投資決策，在瞬息萬(wàn)變的股市中獲得最佳收益。目前對(duì)收益率分布的研究工作主要是從以下兩個(gè)方面展開(kāi)的：一個(gè)方面是基于傳統(tǒng)金融學(xué)理論的視角，使用現(xiàn)有的單個(gè)統(tǒng)計(jì)分布，或者多個(gè)統(tǒng)計(jì)分布的混合分布來(lái)對(duì)收益率的分布特征進(jìn)行描述;另一個(gè)方面是從行為金融學(xué)角度入手，將投資者的某些心理因素作為解釋收益率分布特征的成因。上述方法雖然可以對(duì)收益率分布的部分特征進(jìn)行描繪，但并不能完整刻畫(huà)出投資者所有非理性因素對(duì)收益率分布影響的全過(guò)程。 本文在行為金融理論的視角下，以前景理論為理論基礎(chǔ)，通過(guò)引入概率權(quán)重函數(shù)來(lái)描述投資者的投資行為對(duì)收益率分布的影響，構(gòu)建了一個(gè)新的收益率分布模型，并在新模型的基礎(chǔ)上，采用國(guó)際上具有代表性的10個(gè)股市綜合指數(shù)數(shù)據(jù)，對(duì)股市收益率分布特征及其概率權(quán)重函數(shù)形式進(jìn)行了實(shí)證研究。同時(shí)還嘗試放寬收益率分布模型的假設(shè)條件，將前景理論中的價(jià)值函數(shù)概念引入到模型中來(lái)，，對(duì)新模型進(jìn)行了合理擴(kuò)展，并利用同樣的樣本數(shù)據(jù)對(duì)擴(kuò)展模型也進(jìn)行了實(shí)證研究，且對(duì)新模型及其擴(kuò)展模型的實(shí)證結(jié)果做了對(duì)比分析。 本文的主要結(jié)論有：新的收益率分布模型從投資者非理性行為的角度出發(fā)，能合理的刻畫(huà)市場(chǎng)真實(shí)收益率的形成過(guò)程，通過(guò)對(duì)模型進(jìn)行數(shù)值分析發(fā)現(xiàn)，新的模型能對(duì)真實(shí)收益率的“尖峰厚尾”特征做出合理的解釋。新模型的理論分析和實(shí)證結(jié)果都表明，無(wú)論收益率為正還是為負(fù)，投資者都會(huì)高估小概率事件發(fā)生的概率，而低估中、高概率事件發(fā)生的概率，完整的概率權(quán)重函數(shù)是由兩個(gè)相似的反S型曲線連接而成的。對(duì)新模型進(jìn)行非線性最小二乘回歸的結(jié)果表明，雙參數(shù)概率權(quán)重函數(shù)都能夠很好的刻畫(huà)收益率的分布特征，且不同的概率權(quán)重函數(shù)在正、負(fù)收益條件下的參數(shù)估計(jì)值都是不相同的。通過(guò)對(duì)adjR2值進(jìn)行比較發(fā)現(xiàn)，采用GE形式概率權(quán)重函數(shù)的收益率分布模型通常能夠更好的刻畫(huà)出市場(chǎng)上真實(shí)收益率的分布特征。本文對(duì)收益率分布擴(kuò)展模型也進(jìn)行了實(shí)證分析，結(jié)果發(fā)現(xiàn)擴(kuò)展模型和新模型所得到的結(jié)論大致相同，這也從另一個(gè)角度證明了新構(gòu)建的收益率分布模型的合理性和穩(wěn)定性。
[Abstract]:The rate of return on financial assets is one of the most concerned information for investors, and it is closely related to the vital interests of investors. Therefore, as one of the observable variables in the financial market, the yield distribution has become the focus of many scholars. Fully understanding the characteristics and rules of yield distribution is also helpful for investors to make reasonable investment decisions and obtain the best return in the rapidly changing stock market. The current research work on the yield distribution is mainly from the following two aspects: one is based on the traditional financial theory perspective, using the existing single statistical distribution, Or the mixed distribution of multiple statistical distributions to describe the characteristics of the distribution of return; another aspect is from the perspective of behavioral finance some psychological factors of investors as the reasons for explaining the characteristics of the distribution of returns. Although the above methods can describe some characteristics of the yield distribution, it can not completely describe the whole process of the investors' influence of all irrational factors on the return distribution. In this paper, from the perspective of behavioral finance theory, based on prospect theory, a new model of return distribution is constructed by introducing probability weight function to describe the influence of investor's investment behavior on return distribution. On the basis of the new model, this paper makes an empirical study on the characteristics of the stock market return distribution and the form of the probability weight function by using the international representative 10 stock market composite index data. At the same time, we try to relax the assumptions of the return distribution model, introduce the concept of value function in the foreground theory into the model, and expand the new model reasonably, and use the same sample data to make an empirical study on the extended model. The empirical results of the new model and its extended model are compared and analyzed. The main conclusions of this paper are as follows: the new model of return distribution can reasonably depict the forming process of market real return rate from the angle of investors' irrational behavior. The new model can reasonably explain the "peak and thick tail" feature of real yield. The theoretical analysis and empirical results of the new model show that investors overestimate the probability of occurrence of small probability events regardless of whether the return rate is positive or negative, while underestimating the probability of occurrence of high probability events. The complete probabilistic weight function is connected by two similar inverse S-shaped curves. The results of nonlinear least square regression for the new model show that the probability weight functions with two parameters can well describe the distribution characteristics of the yield, and the different probability weight functions are positive. Under the condition of negative return, the parameter estimates are different. Through the comparison of the adjR2 value, it is found that the GE probability weight function model can better describe the distribution characteristics of the real return rate in the market. This paper also makes an empirical analysis of the extended model of return distribution, and finds that the extended model and the new model have the same conclusion, which also proves the rationality and stability of the new model from another angle.
【學(xué)位授予單位】：長(zhǎng)沙理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：F830.9
本文編號(hào)：2204085
[Abstract]:The rate of return on financial assets is one of the most concerned information for investors, and it is closely related to the vital interests of investors. Therefore, as one of the observable variables in the financial market, the yield distribution has become the focus of many scholars. Fully understanding the characteristics and rules of yield distribution is also helpful for investors to make reasonable investment decisions and obtain the best return in the rapidly changing stock market. The current research work on the yield distribution is mainly from the following two aspects: one is based on the traditional financial theory perspective, using the existing single statistical distribution, Or the mixed distribution of multiple statistical distributions to describe the characteristics of the distribution of return; another aspect is from the perspective of behavioral finance some psychological factors of investors as the reasons for explaining the characteristics of the distribution of returns. Although the above methods can describe some characteristics of the yield distribution, it can not completely describe the whole process of the investors' influence of all irrational factors on the return distribution. In this paper, from the perspective of behavioral finance theory, based on prospect theory, a new model of return distribution is constructed by introducing probability weight function to describe the influence of investor's investment behavior on return distribution. On the basis of the new model, this paper makes an empirical study on the characteristics of the stock market return distribution and the form of the probability weight function by using the international representative 10 stock market composite index data. At the same time, we try to relax the assumptions of the return distribution model, introduce the concept of value function in the foreground theory into the model, and expand the new model reasonably, and use the same sample data to make an empirical study on the extended model. The empirical results of the new model and its extended model are compared and analyzed. The main conclusions of this paper are as follows: the new model of return distribution can reasonably depict the forming process of market real return rate from the angle of investors' irrational behavior. The new model can reasonably explain the "peak and thick tail" feature of real yield. The theoretical analysis and empirical results of the new model show that investors overestimate the probability of occurrence of small probability events regardless of whether the return rate is positive or negative, while underestimating the probability of occurrence of high probability events. The complete probabilistic weight function is connected by two similar inverse S-shaped curves. The results of nonlinear least square regression for the new model show that the probability weight functions with two parameters can well describe the distribution characteristics of the yield, and the different probability weight functions are positive. Under the condition of negative return, the parameter estimates are different. Through the comparison of the adjR2 value, it is found that the GE probability weight function model can better describe the distribution characteristics of the real return rate in the market. This paper also makes an empirical analysis of the extended model of return distribution, and finds that the extended model and the new model have the same conclusion, which also proves the rationality and stability of the new model from another angle.
【學(xué)位授予單位】：長(zhǎng)沙理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：F830.9
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