本文選題：定價(jià)函數(shù) + 變量�。� 參考：《中國計(jì)量學(xué)院》2013年碩士論文

【摘要】：價(jià)格作為買賣雙方最重要的信號(hào)，是市場(chǎng)的靈魂，因此構(gòu)建合理的股票定價(jià)函數(shù)顯得尤為重要。定價(jià)函數(shù)形式的研究也日益受到眾多學(xué)者的青睞，提出了各種定價(jià)方法。但是，目前的研究成果仍有許多待改進(jìn)的地方，如選取變量單一、函數(shù)形式多為線性等。結(jié)合股票價(jià)格存在噪聲等問題，本文在已有文獻(xiàn)基礎(chǔ)上，主要研究了以下三方面的內(nèi)容： （1）本文通過股票定價(jià)機(jī)制的分析，認(rèn)為目前定價(jià)函數(shù)所使用的每股收益、每股凈資產(chǎn)等公司層面的變量有改進(jìn)的空間，提出公司層面應(yīng)該與市場(chǎng)層面相結(jié)合，通過分析將Beta值與流通股本選為市場(chǎng)層面變量，并進(jìn)行了實(shí)證分析。結(jié)果表明，綜合考慮公司與市場(chǎng)層面變量比僅考慮公司層面變量在模型的預(yù)測(cè)精度上更有優(yōu)勢(shì)。 （2）通過多種形式的生產(chǎn)函數(shù)對(duì)比分析，本文認(rèn)為由于股票定價(jià)機(jī)制的復(fù)雜性，股票定價(jià)函數(shù)形式應(yīng)該是非線性的。綜合比較，，本文將柯布-道格拉斯生產(chǎn)函數(shù)選為定價(jià)函數(shù)。同時(shí)，介紹了對(duì)回歸模型的統(tǒng)計(jì)檢驗(yàn)方法，為后面的實(shí)證分析做理論依據(jù)。在實(shí)證部分，本文將線性形式的定價(jià)函數(shù)與非線性形式的定價(jià)函數(shù)進(jìn)行了對(duì)比研究，結(jié)果顯示，非線性模型的預(yù)測(cè)精度明顯好于線性模型的預(yù)測(cè)精度。 （3）股票價(jià)格作為金融時(shí)間序列的代表，其噪聲問題不可回避，因此去噪問題的研究十分重要。在此基礎(chǔ)之上，本文提出了基于小波分析的去噪方法，并進(jìn)行實(shí)證研究，結(jié)果表明，經(jīng)過去噪之后的模型預(yù)測(cè)精度明顯得到提升。
[Abstract]:Price, as the most important signal between buyer and seller, is the soul of market, so it is very important to construct reasonable stock pricing function. The research of pricing function form has been increasingly favored by many scholars, and various pricing methods have been put forward. However, there are still many improvements in the present research results, such as single variables and linear functions. Based on the existing literature, this paper mainly studies the following three aspects: 1) through the analysis of stock pricing mechanism, this paper thinks that there is room for improvement in the variables of company level such as earnings per share, net assets per share and so on, which are used in the current pricing function, and puts forward that the company level should be combined with the market level. Through the analysis, the Beta value and the circulating stock are selected as the market level variables, and the empirical analysis is carried out. The results show that the prediction accuracy of the model is better when considering the variables at the firm and market level comprehensively than only the variables at the firm level. 2) based on the comparative analysis of various production functions, this paper holds that due to the complexity of stock pricing mechanism, the form of stock pricing function should be nonlinear. In this paper, Cobb-Douglas production function is selected as the pricing function. At the same time, the statistical test method of regression model is introduced, which is the theoretical basis for the later empirical analysis. In the empirical part, we compare the linear pricing function with the nonlinear pricing function. The results show that the prediction accuracy of the nonlinear model is obviously better than that of the linear model. As the representative of financial time series, the noise problem of stock price can not be avoided, so it is very important to study the problem of de-noising. On this basis, this paper proposes a method of denoising based on wavelet analysis, and carries out an empirical study. The results show that the prediction accuracy of the model is obviously improved after denoising.
【學(xué)位授予單位】：中國計(jì)量學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F224;F830.91

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

1 龍洋;游勇華;于偉臣;鄢波;;基于MATLAB小波去噪方法及應(yīng)用研究[J];數(shù)字技術(shù)與應(yīng)用;2012年08期

2 蒲會(huì)蘭;丁世文;魯懷偉;吳六愛;楊喜娟;;小波變換及其在信號(hào)去噪中的應(yīng)用[J];現(xiàn)代電子技術(shù);2012年19期

本文編號(hào)：1974406