發(fā)布時(shí)間：2018-08-20 14:06

【摘要】：部分線性單指標(biāo)模型是由線性模型和單指標(biāo)模型組合成的一類半?yún)?shù)統(tǒng)計(jì)模型。該模型能夠在參數(shù)統(tǒng)計(jì)推斷與非參統(tǒng)計(jì)推斷之間取得某種平衡，具有良好的統(tǒng)計(jì)性質(zhì)并且在經(jīng)濟(jì)、生物、醫(yī)學(xué)等領(lǐng)域都有廣泛的應(yīng)用。 隨著我國(guó)經(jīng)濟(jì)和投資市場(chǎng)的不斷發(fā)展，股票投資也受到人們的極大關(guān)注，且有越來(lái)越多人參與到股票市場(chǎng)中。股市在一個(gè)國(guó)家的金融領(lǐng)域扮演著至關(guān)重要的角色，而股票價(jià)格的波動(dòng)是投資者最為關(guān)心的事情。由于股票交易市場(chǎng)存在著許多不定因素，這給投資者合理投資選股造成了一定困難，因此人們渴望能夠?qū)蓛r(jià)進(jìn)行科學(xué)分析與預(yù)測(cè)。為此相關(guān)領(lǐng)域的許多學(xué)者作了大量的探索工作，并取得了一些行之有效的辦法。 基于部分線性單指標(biāo)模型的靈活性，針對(duì)股價(jià)預(yù)測(cè)這一熱點(diǎn)研究問(wèn)題，本文考慮從上市公司公布的財(cái)務(wù)數(shù)據(jù)出發(fā)，利用部分線性單指標(biāo)模型預(yù)測(cè)股價(jià)與財(cái)務(wù)指標(biāo)之間的關(guān)系，進(jìn)而對(duì)未來(lái)股價(jià)進(jìn)行預(yù)測(cè)。本文主要完成以下幾方面工作： 第一，本文介紹了股票的相關(guān)概念及知識(shí)，包括股票的主要特征，股價(jià)的影響因素，影響股價(jià)的財(cái)務(wù)指標(biāo)等。其中，對(duì)財(cái)務(wù)指標(biāo)的介紹有助于選擇合適的財(cái)務(wù)變量進(jìn)行模型應(yīng)用及股價(jià)預(yù)測(cè)。在此基礎(chǔ)上，介紹了一些現(xiàn)有的關(guān)于股票價(jià)格預(yù)測(cè)的方法，并對(duì)每種方法的特點(diǎn)、優(yōu)勢(shì)、不足等進(jìn)行了描述。 第二，闡述了單指標(biāo)模型及部分線性單指標(biāo)模型的發(fā)展，概況，研究現(xiàn)狀等，此外給出了模型中的未知參數(shù)和未知函數(shù)的估計(jì)值。 第三，，實(shí)證分析。首先對(duì)所選財(cái)務(wù)指標(biāo)進(jìn)行降維處理，簡(jiǎn)化模型。然后應(yīng)用部分線性單指標(biāo)模型預(yù)測(cè)出降維后財(cái)務(wù)指標(biāo)與股票價(jià)格之間的函數(shù)關(guān)系，并且與線性模型的預(yù)測(cè)結(jié)果進(jìn)行對(duì)比，發(fā)現(xiàn)部分線性單指標(biāo)模型的預(yù)測(cè)結(jié)果優(yōu)于線性模型，因此本文提出的方法具有一定的應(yīng)用價(jià)值。
[Abstract]:Partial linear single-parameter model is a kind of semi-parametric statistical model which is composed of linear model and single-parameter model. The model can achieve a certain balance between parametric statistical inference and non-parametric statistical inference. It has good statistical properties and is widely used in economic, biological, medical and other fields. With the development of our country's economy and investment market, people pay more and more attention to the stock investment, and more people participate in the stock market. The stock market plays a vital role in the financial sector of a country, and the volatility of stock prices is a matter of most concern to investors. There are many uncertain factors in the stock market, which makes it difficult for investors to make reasonable investment in stock selection, so people are eager to make scientific analysis and prediction of stock price. For this reason, many scholars in related fields have done a lot of exploration and made some effective methods. Based on the flexibility of partial linear single index model and aiming at the hot research problem of stock price forecasting, this paper considers the relationship between stock price and financial index by using partial linear single index model from the financial data published by listed companies. Then predict the future stock price. The main work of this paper is as follows: first, this paper introduces the related concepts and knowledge of stock, including the main characteristics of stock, the influencing factors of stock price, the financial index of stock price and so on. Among them, the introduction of financial indicators is helpful to select suitable financial variables for model application and stock price prediction. On this basis, some existing methods of stock price prediction are introduced, and the characteristics, advantages and disadvantages of each method are described. Secondly, the development, general situation and research status of single index model and partial linear single index model are described. In addition, the estimated values of unknown parameters and unknown functions in the model are given. Third, empirical analysis. First of all, the selected financial indicators are reduced to simplify the model. Then the partial linear single index model is used to predict the functional relationship between the financial index and the stock price after dimensionality reduction, and compared with the prediction result of the linear model, it is found that the prediction result of the partial linear single index model is better than that of the linear model. Therefore, the method proposed in this paper has certain application value.
【學(xué)位授予單位】：遼寧師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F830.91;F224;O212.1

【參考文獻(xiàn)】

相關(guān)期刊論文 前2條

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本文編號(hào)：2193885