本文關(guān)鍵詞： 投資者情緒 股市危機(jī) 預(yù)警系統(tǒng) Logit模型 KLR信號(hào)分析法　出處：《華南理工大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：股市危機(jī)在當(dāng)今世界經(jīng)濟(jì)一體化和金融自由化的趨勢(shì)下頻繁出現(xiàn)，它所帶來(lái)的經(jīng)濟(jì)成本以及社會(huì)成本是異常巨大的，加之我國(guó)股票市場(chǎng)發(fā)展的特殊性，對(duì)股市危機(jī)的預(yù)警顯得更為重要和迫切。 本文從行為金融學(xué)的視角切入，通過(guò)篩選程序選定了上證基金指數(shù)、新增基金開戶數(shù)、上證指數(shù)、上證指數(shù)成交量和上證A股市盈率為投資者情緒代理變量，使用主成分方法構(gòu)建投資者情緒。使用單變量Logit模型對(duì)滬市在2005年1月至2012年6月之間發(fā)生危機(jī)的可能性進(jìn)行了預(yù)測(cè)。實(shí)證結(jié)果表明，投資者情緒對(duì)股市危機(jī)的發(fā)生概率有顯著的正向影響作用，情緒高漲時(shí)觸發(fā)股市危機(jī)的概率大約是情緒低落時(shí)發(fā)生股市危機(jī)概率的7倍，，是預(yù)測(cè)股市危機(jī)的顯著預(yù)測(cè)因子，并且通過(guò)了深圳市場(chǎng)的穩(wěn)定性檢驗(yàn)。 選出文獻(xiàn)中常用的金融危機(jī)預(yù)警變量，同樣使用單變量Logit方法，選出對(duì)我國(guó)股市危機(jī)具有預(yù)測(cè)作用的宏觀變量。實(shí)證結(jié)果顯示，投資者情緒的引入能夠提高以常用宏觀變量為主的預(yù)警模型對(duì)股市危機(jī)的預(yù)測(cè)準(zhǔn)確度。通過(guò)KLR信號(hào)分析和閾值遍歷方法計(jì)算出基于投資者情緒的股市危機(jī)預(yù)警模型的最佳信號(hào)閾值，并統(tǒng)計(jì)得本文模型的噪音-信號(hào)比率為0.022，信號(hào)總體正確率為93.7%，并且樣本外測(cè)試穩(wěn)定。說(shuō)明本文設(shè)計(jì)的基于投資者情緒的股市危機(jī)預(yù)警系統(tǒng)對(duì)股市危機(jī)具有顯著的預(yù)測(cè)作用。 最后，本文嘗試構(gòu)建混頻投資者情緒和周度投資者情緒并對(duì)其預(yù)警能力進(jìn)行了檢驗(yàn)，結(jié)果顯示混頻情緒比同頻情緒的信息量更大、預(yù)警能力更強(qiáng)；周度情緒對(duì)股市危機(jī)具有顯著的中短期預(yù)警能力。實(shí)證結(jié)果為今后構(gòu)建多時(shí)標(biāo)、多頻度的綜合性預(yù)警系統(tǒng)提供了可行性證明。
[Abstract]:The stock market crisis appears frequently under the trend of economic integration and financial liberalization in the world today. The economic and social costs brought by the crisis are enormous and the particularity of the development of China's stock market. The warning of stock market crisis is more important and urgent. From the perspective of behavioral finance, this paper selects the Shanghai Stock Exchange Fund Index, the number of new fund accounts, the Shanghai Stock Exchange Index, the Shanghai Stock Exchange Index turnover and the Shanghai A-share price / earnings ratio as the proxy variables of investor sentiment through the screening process. The principal component method is used to construct investor sentiment. The univariate Logit model is used to predict the possibility of Shanghai stock market crisis from January 2005 to June 2012. The empirical results show that. Investor sentiment has a significant positive effect on the probability of stock market crisis. The probability of triggering stock market crisis when the mood is high is about 7 times the probability of the stock market crisis when the mood is low. It is a significant predictor of stock market crisis, and has passed the stability test of Shenzhen market. Select the commonly used financial crisis warning variables in the literature, the same use of univariate Logit method, select the macro variables that can predict the stock market crisis in China. The empirical results show that. The introduction of investor sentiment can improve the prediction accuracy of stock market crisis based on common macro variables. The stock market crisis prediction based on investor sentiment can be calculated by KLR signal analysis and threshold traversal method. The optimal signal threshold of the alarm model. The results show that the ratio of noise to signal is 0.022, and the overall correct rate of signal is 93.7%. The results show that the stock market crisis warning system based on investor sentiment has a significant predictive effect on stock market crisis. Finally, this paper tries to construct mixed investor sentiment and Zhou du investor emotion and test its warning ability. The results show that mixed frequency emotion has more information than the same frequency emotion and has stronger warning ability. Zhou du mood has significant ability of short and medium term early warning for stock market crisis. The empirical results provide feasibility proof for the construction of multi time scale and multi frequency comprehensive early warning system in the future.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：F832.51;F224

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