發(fā)布時間：2018-07-14 18:42

【摘要】：隨著網(wǎng)絡(luò)在國內(nèi)普及率飛速增長，網(wǎng)絡(luò)信息量呈幾何級數(shù)增長，其傳播的速度更是其它渠道難以匹敵的，成為人們最重要的信息來源之一。網(wǎng)絡(luò)也成為金融領(lǐng)域信息重要的集散地，尤其是WEB2.0技術(shù)的發(fā)展，論壇、博客、聊天室等可以提供互動的技術(shù)不斷涌現(xiàn)，使投資者可以參與到網(wǎng)絡(luò)信息的創(chuàng)造、傳播及獲取的各個環(huán)節(jié)。論壇是最受歡迎的網(wǎng)絡(luò)社區(qū)之一，眾多的投資者在股票論壇中交流信息，分享經(jīng)驗以輔助投資決策，因此對其中信息的獲取是了解投資者心理及行為的重要途徑。 相比國外上百年歷史的成熟的金融市場，成立僅二十余年的中國金融市場還處于發(fā)展階段，監(jiān)管制度不完善，投機者居多。眾多投資者通過各種途徑獲取信息進行交易，作為獲取信息的重要方式之一，對股票論壇的研究具有重要意義。 行為金融理論認為投資者的心理及行為能夠影響股票市場的表現(xiàn)，基于這一理論，本文對國內(nèi)的股票市場進行了研究。本文提出了自動剔除領(lǐng)域無關(guān)評論的方法，成功剔除了84%的股票市場無關(guān)評論，并保留了90%以上的股票市場相關(guān)信息。本文對比了語義分析方法、機器學(xué)習(xí)方法及N-Gram方法三種情感分析方法，支持向量機結(jié)合信息增益的方法能夠獲得良好的實驗結(jié)果。通過單只股票價格影響因素分析，建立股票價格預(yù)測模型，能夠比較準確地預(yù)測股票市場的價格。 我們分析了股票價格影響因素，并建立回歸模型對其進行預(yù)測。結(jié)果顯示，滯后股票收盤價，情感指數(shù)，機構(gòu)評分、滯后新聞數(shù)量能投對股票收盤價格進行解釋。通過對通訊行業(yè)進行單因素方差分析，，情感指數(shù)能夠影響收益率及波動率。通過對上證指數(shù)及情感指數(shù)進行領(lǐng)先滯后分析發(fā)現(xiàn)，投資者情緒與滯后綜合指數(shù)相關(guān)，與領(lǐng)先個股收盤價相關(guān)。
[Abstract]:With the rapid growth of the popularization rate of the network in China, the amount of network information is increasing in geometric series, and the speed of its dissemination is even more difficult to compete with other channels, so it has become one of the most important sources of information for people. The network has also become an important distribution center for information in the financial field, especially the development of Web 2.0 technology, forums, blogs, chat rooms, and other technologies that can provide interaction, so that investors can participate in the creation of network information. All aspects of dissemination and acquisition. Forum is one of the most popular online communities. Many investors exchange information and share experiences in stock forums to assist in investment decisions. Therefore, the acquisition of information is an important way to understand the psychology and behavior of investors. Compared with the mature financial market with a history of more than one hundred years abroad, the Chinese financial market, which has only been established for more than 20 years, is still in the developing stage, the supervision system is not perfect, and the speculators are mostly. As one of the most important ways to obtain information, it is of great significance to the research of stock forum. Behavioral finance theory holds that investors' psychology and behavior can affect the performance of stock market. Based on this theory, this paper studies the domestic stock market. In this paper, a method of automatically eliminating domain-independent reviews is proposed, which successfully removes 84% of stock market independent reviews and retains more than 90% of stock market related information. In this paper, three affective analysis methods, semantic analysis method, machine learning method and N-Gram method, are compared. The support vector machine combined with information gain method can obtain good experimental results. Through the analysis of the influencing factors of a single stock price, a forecasting model of stock price is established, which can accurately predict the price of the stock market. We analyze the influencing factors of stock price and establish a regression model to predict it. The results show that the closing price of the stock can be explained by lagging stock closing price, affective index, agency score and lagging news quantity. By analyzing the single factor ANOVA, the affective index can affect the yield and volatility. Through the leading lag analysis of Shanghai stock index and emotion index, it is found that investor sentiment is related to lagging composite index and to closing price of leading stock.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2012
【分類號】：F832.51;F224

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